Other jobs in AI & developer tooling

## Role Overview * **Job Title:** Data Science Intern * **Location:** Remote (Europe) * **Duration:** 2–3 Months (Flexible schedule) * **Target Audience:** Motivated students and recent graduates across Europe passionate about data science, machine learning, and AI. --- ## Key Responsibilities * **Data Processing & EDA:** Collect, clean, and preprocess structured and unstructured datasets; execute exploratory data analysis (EDA) to identify trends and business insights. * **ML Model Development:** Assist in developing, training, evaluating, and documenting machine learning models for real-world applications. * **Visualization & Reporting:** Design dashboards, reports, and data visualizations to communicate analytical findings to project stakeholders. * **Technical Execution:** Utilize Python data libraries (Pandas, NumPy, Scikit-learn, Matplotlib) and SQL for data querying and analysis. * **Collaboration & Documentation:** Document methodologies, project findings, and technical recommendations while working collaboratively across remote teams. --- ## Qualifications & Skills ### Qualifications * Currently pursuing or recently completed a Bachelor's or Master's degree in **Data Science, Computer Science, AI, Statistics, Mathematics, Engineering, IT**, or a related quantitative field. * Strong interest in Data Science, Machine Learning, and Artificial Intelligence. * Ability to work independently and collaboratively in a 100% remote setting. ### Key Skills (Required & Preferred) * **Programming:** Basic to intermediate proficiency in **Python** (Pandas, NumPy, Scikit-learn, Matplotlib). * **Data & SQL:** Understanding of relational databases, SQL querying, and dataset manipulation. * **Fundamentals:** Solid grounding in statistics, probability, and core machine learning algorithms. * **Tools & Visualization:** Familiarity with Jupyter Notebooks, Git/version control, and BI tools (**Power BI, Tableau**, or Matplotlib). * **Soft Skills:** Analytical thinking, problem-solving mindset, and clear written and verbal communication. --- ## Who Can Apply * Undergraduate and postgraduate students looking for practical industry experience. * Recent graduates seeking hands-on exposure to build an industry-ready portfolio. * Self-motivated learners eager to transform real-world data into predictive models and actionable insights. --- ## Perks & Benefits * **Certificates & Endorsements:** Certificate of Internship upon completion + performance-based **Letter of Recommendation** and top-performer recognition awards. * **Career Development:** Resume review, LinkedIn profile optimization, and mock interview preparation sessions. * **Portfolio & Experience:** Build a tangible portfolio of industry-relevant Data Science and ML projects. * **Flexibility:** 100% remote working environment with flexible hours to accommodate academic commitments. * **Learning & Community:** Access to case studies, technical workshops, curated learning resources, and networking opportunities.

## About PlusAI **PlusAI** is a Physical AI company pioneering AI-based virtual driver software for factory-built autonomous trucks. Headquartered in Silicon Valley with operations in the United States and Europe, Plus was named by *Fast Company* as one of the World’s Most Innovative Companies. Plus collaborates with global partners—including **TRATON GROUP (Scania, MAN, International), Hyundai Motor Company, Iveco Group, Bosch, and DSV**—to accelerate the real-world deployment of next-generation autonomous trucks. --- ## About The Role This internship role focuses on **3D/4D Digital Twin Reconstruction & Neural Rendering** within the Simulation and Perception teams. You will build and optimize pipelines that reconstruct high-fidelity, multi-modal 3D representations of driving routes from real vehicle data, applying cutting-edge view-synthesis techniques to stress-test autonomous driving stacks against complex edge cases. --- ## Core Focus & Key Responsibilities * **Construct Digital Twins:** Develop pipelines to reconstruct high-fidelity multi-modal 3D representations using recorded sensor data (camera, LiDAR, IMU, and GPS). * **Next-Gen Neural Rendering:** Apply state-of-the-art view-synthesis techniques—such as **3D Gaussian Splatting (3DGS)** and **NeRFs**—to model complex real-world lighting, weather, and dynamic objects. * **3D/4D Scene Simulation:** Work on generating 3D/4D scene reconstructions to simulate driving environments while generating realistic multi-view camera and LiDAR sensor data. * **Validation & Verification (V&V):** Integrate reconstructed environments into the perception testing framework to stress-test object detection, tracking, and edge-case scenarios. * **Multi-Modal Accuracy:** Evaluate alignment and geometric consistency across different sensor modalities within the digital twin. * **Scale & Collaborate:** Turn research prototypes into robust, scalable tooling alongside the Simulation and Perception teams to accelerate production deployment. --- ## Qualifications ### Required Skills * **Education:** Currently pursuing an **MS or PhD** in Computer Science, Electrical Engineering, Mathematics, Statistics, or a related technical field. * **Machine Learning Fundamentals:** Deep understanding of core ML principles and methodologies. * **Deep Learning Frameworks:** Practical experience implementing deep learning models in at least one major framework (**PyTorch, TensorFlow, or JAX**). ### Preferred Skills * Project experience in deep learning for **object detection, motion tracking, or semantic segmentation**. * Hands-on experience with **3D Computer Vision**. * Strong publication record in relevant top-tier venues (*CVPR, ICLR, ICCV, ECCV, NeurIPS, AAAI, SIGGRAPH*). --- ## Compensation & Perks ### Hourly Pay Range * **$19 – $65 per hour** *(Standard hourly rate determined based on degree level [MS vs. PhD], location, academic year, and relevant experience).* ### Perks & Benefits * **Food & Snacks:** Free catered lunches, along with unlimited snacks and beverages. * **Financial Benefits:** Competitive salary and 401(k) plan. * **Growth Opportunities:** Hands-on experience in dynamic, high-impact fields including Neural Rendering, Physical AI, and Autonomous Systems.

## About PlusAI **PlusAI** is a Physical AI company pioneering AI-based virtual driver software for factory-built autonomous trucks. Headquartered in Silicon Valley with operations across the United States and Europe, Plus was named by *Fast Company* as one of the World’s Most Innovative Companies. Plus collaborates with global OEM and logistics partners—including **TRATON GROUP (Scania, MAN, International), Hyundai Motor Company, Iveco Group, Bosch, and DSV**—to accelerate the real-world deployment of next-generation autonomous trucking technology. --- ## About The Role As a **Perception Intern**, you will join Plus’s dynamic perception team to work on real-world autonomous vehicle (AV) challenges. You will work within a state-of-the-art simulation pipeline, collaborating with industry experts to train, fine-tune, and deploy multimodal deep learning models into production. --- ## Key Responsibilities * **Emergency Vehicle Detection:** Develop state-of-the-art technologies to detect emergency vehicles using temporal sequences of camera images. * **Algorithm Development & Benchmarking:** Design, implement, and benchmark cutting-edge deep learning techniques for perception tasks. * **Production Stack Integration:** Collaborate with engineering teams to optimize models and seamlessly integrate developed algorithms into the production perception and AV stack. --- ## Qualifications ### Required Skills * **Education:** Currently pursuing an **MS or PhD** in Computer Science, Electrical Engineering, Robotics, or a related technical field (or equivalent practical experience). * **Software Development:** Strong software design and development experience in **Python**. * **Machine Learning:** Solid background and hands-on experience in **Machine Learning and Deep Learning**. * **Computer Vision:** Practical experience in **3D computer vision**. ### Preferred Skills * Past project experience involving **object detection, motion tracking, or semantic segmentation**. * Advanced background in 3D vision systems. * Publication record in top-tier venues (*CVPR, ICLR, ICCV, ECCV, NeurIPS, AAAI, SIGGRAPH*). --- ## Compensation & Perks ### Hourly Pay Range * **$19 – $65 per hour** *(Standard hourly rates are determined based on degree program [MS vs. PhD], year in school, prior experience, position location, and candidate background).* ### Perks & Benefits * **Food & Snacks:** Catered free lunches, along with unlimited snacks and beverages in the office. * **Financial Benefits:** Highly competitive compensation package, including a **401(k) plan**. * **Professional Development:** Opportunity to build, learn, and grow in a high-impact, future-oriented field of physical AI and autonomous driving.

## About Brain Co. **Our Mission:** Rebuild how the world works, to make institutions work better for the people they serve. Brain Co. builds **AI-native operating systems** for large, regulated institutions. Each system is built for a specific industry, powered by agents that push real workflows forward. Underneath it all is **Atlas**, our proprietary platform that keeps customers in control, secure by design, and never locked into one model. We are entering our next phase of production deployments on a national scale with an elite team built from Palantir, Google, Meta, and Nvidia. --- ## The Role You'll join the team that builds and enables agentic workflows across Brain Co. This is a **platform role** at the center of the company's agent-first strategy. You'll build the foundational AI systems used by every engineering, operations, and business team internally, as well as the production systems we deploy to governments, healthcare systems, and critical industries. ### What You’ll Work On * **Own the foundations** of how LLMs are used across the company: cost visibility, data privacy, identity and access, routing, and security posture. * **Design the agent architecture:** Build the sandboxing, orchestration, audit, and guardrail layers that product teams build their agents on. * **Solve hard security & infrastructure problems:** Prompt-injection defenses, scoped credentials, kill switches, multi-tenant isolation (including VM-level pod isolation), and runaway-cost controls. * **Resource & orchestration modeling:** Manage cold-start vs. always-on tradeoffs, credential lifecycles, fan-out/fan-in patterns, and quota enforcement across tenants. * **Make AI-assisted development a first-class platform layer:** Build coding agents that review and ship code, automate CI, and refactor at scale as background workers. * **End-to-end ownership:** Handle architecture, implementation, rollout, observability, on-call duties, and iteration based on internal feedback. --- ## What You’ll Bring ### Required Qualifications * **5+ years** building backend systems in production, with deep proficiency in **Python, TypeScript, Go, or Rust**. * Strong fundamentals in **distributed systems**: consistency, idempotency, retries, failure modes, queueing, and scheduling. * Proven track record of designing and operating APIs, shared infrastructure, internal platforms, or developer-facing services that real users adopted. * Strong intuition for **developer experience**, long-term maintainability, and where to draw abstraction boundaries. * Experience owning services with real uptime and operational responsibility, including observability stacks, incident response, and SLOs. * Cloud-native experience: **Kubernetes, infrastructure-as-code, OAuth/OIDC, and secrets management**. ### Ways You Might Stand Out * Experience building or operating **LLM infrastructure**: gateways, inference systems, prompt routing, cost attribution, or evaluation harnesses. * Experience with **agent frameworks, tool-use systems**, or sandboxed code execution. * Strong security instincts around **prompt injection, supply-chain risk**, and credential scoping for autonomous systems. * Background in multi-tenant, **regulated, or government deployments (HIPAA, SOC2)**. * **Open-source contributions** to AI infrastructure, agent tooling, or developer platforms. --- ## Why Join Us & Benefits Join a culture built on speed, curiosity, and impact, and collaborate with industry veterans from Tesla, DeepMind, Databricks, and more. We offer: * **Competitive salary plus meaningful equity** * **Medical, Dental, and Vision** insurance * **401(k)** plan * **Unlimited PTO** * Daily lunches and commuter benefits

> ⚠️ **Application Deadline:** July 31, 2026 *(Posting may close earlier if filled).* > 📍 **Location / Model:** Hybrid — Onsite 3 days per week in **Raleigh (Research Triangle Park), NC** or **San Jose, CA**. --- ## Meet the Team Our team is part of the **Cisco AI and Automation portfolio**, responsible for the **"Circuit" platform**—the central AI engine that powers productivity and process automation across all of Cisco. We are a rapidly expanding, high-impact group operating at the intersection of applied research and production, delivering performance, reliability, and functional quality for **80,000+ monthly users**. --- ## Your Impact As an **Automation AI Ops Engineer**, you will serve as a modern-day functional and performance evaluation leader, driving the transformation of our regression testing ecosystem. You will move beyond manual processes to implement **AI-driven agents** that generate, validate, and maintain regression suites for both new and legacy features. By leveraging advanced AI coding tools (**Cursor, Copilot, Claude Code**), you will bridge the gap between AI-generated code and production-ready software, ensuring the Circuit platform remains a reliable, scalable vehicle for process automation across Cisco. --- ## Key Responsibilities * **AI-Driven Regression:** Architect and drive AI-based automation strategies to replace manual QA, ensuring comprehensive regression coverage for the entire Circuit platform. * **Modernizing Legacy Features:** Utilize AI agents to modernize existing features, generating and maintaining accurate regression suites for legacy codebases. * **Agentic Workflow Development:** Build and refine workflows where AI agents generate code that passes automated validation and is successfully merged into the main production branch. * **Quality Validation:** Establish robust validation frameworks to ensure that AI-generated artifacts meet Cisco’s high standards for functional quality, security, and performance. * **Cross-Functional Leadership:** Act as a "Team Captain" for automation initiatives, influencing peers and collaborating with engineering teams to integrate automated testing into the core development lifecycle. --- ## Qualifications ### Minimum Qualifications * **Education & Experience:** * Bachelor’s degree with **6+ years** of related experience * Master’s degree with **4+ years** of related experience * PhD with **1+ year** of related experience in Computer Science, AI/ML, or a related technical field * **Automation Expertise:** Proven experience in test automation and regression framework development, with a deep understanding of functional quality assurance. * **AI-Assisted Coding:** Hands-on experience using tools like **GitHub Copilot, Cursor, or Claude Code** to build, validate, and deploy production-level software while auditing auto-generated code for stability and security standards. * **Software Engineering:** Solid conceptual and practical knowledge of the SDLC, including **CI/CD pipelines** and automated testing best practices. * **Critical Thinking:** Strong ability to evaluate technical trade-offs between manual and automated testing strategies. ### Preferred Qualifications * Experience in **AI Ops, MLOps**, or building/fine-tuning custom LLMs. * Proven track record of leading technical projects and mentoring junior engineers. * Experience applying **Design Thinking** principles to AI-driven user experiences. * Hands-on experience with **real-time AI workload management** and **token optimization strategies**. * Experience building and productizing agentic applications with a focus on evaluation and business acceptance. --- ## Compensation & Benefits ### Base Salary Ranges * **Projected Starting Base Salary:** **$199,700 – $254,600** *(Excludes bonuses, equity, or location-based adjustments)* * **New York City Metro Area:** **$199,700 – $292,800** * **Non-Metro NY & Washington State:** **$174,500 – $260,500** ### Featured Benefits * **Health & Financial:** Medical, dental, vision insurance, 401(k) with company matching contribution, restricted stock units (RSUs), and annual incentive bonus program. * **Paid Time Away:** * **Exempt Employees:** Flexible vacation time off program (no defined limit). * **Holidays & Shutdowns:** 10 paid holidays + 1 floating holiday, birthday off, year-end holiday shutdown, and 4 personal wellness days. * **Sick & Care Leave:** 80 hours of sick time provided upon hire (up to 80 hours carryover annually). * **Volunteer Time:** 10 paid days per year for volunteer work. --- ## About Cisco At Cisco, we’ve been innovating for 40 years to connect and protect organizations in the AI era and beyond. We work as a team, collaborating with empathy to make big things happen on a global scale. *Cisco is an Equal Opportunity Employer and an E-Verify employer.*

## Company Overview **Accordion** is the value creation partner for private equity, sitting at the intersection where sponsors and CFOs meet. Through financial consulting rooted in data, technology, and AI, Accordion supports the office of the CFO to drive end-to-end value creation alongside 1,600+ finance & technology experts across 11 global offices. ### Accordion Intelligence Lab The AI Lab is composed of leading software and AI engineers designing agentic-AI solutions. The group builds and operationalizes the AI systems that power Accordion’s consulting capabilities—from agentic architectures and RAG pipelines to evaluation frameworks and production observability. --- ## Role 1: Data Specialist (AI-Augmented Delivery Pods) ### About The Role As a Data Specialist in an AI-augmented delivery pod (combining AI engineering, data science, and product management), you make data work in practice. You move fluidly between messy source systems and production-ready pipelines at high speed, working directly alongside AI engineers and product managers to scope data requirements, diagnose quality issues, and build the data foundations that AI systems depend on. ### What You’ll Do * **Build & Maintain Infrastructure:** Construct data pipelines, models, and integrations that AI systems depend on, from raw source data to production-ready outputs * **Custom ML Modeling:** Scope, design, and write custom ML models tailored to client problems, from feature engineering through evaluation and deployment * **Exploratory Data Analysis:** Explore unfamiliar datasets rapidly to identify structure, surface anomalies, and form clear points of view * **Diagnose Data Quality:** Catch quality issues quickly, quantify their impact, and drive resolution proactively * **Client Engagement & Storytelling:** Run client working sessions (source system walkthroughs, model findings, quality assessments) and translate complex data findings into plain language for CFOs and non-technical stakeholders * **Navigate Enterprise Data Environments:** Work fluently within ERP systems, BI platforms, and financial data infrastructure ### Success in the First 6 Months * Own end-to-end data delivery across multiple AI engagements * Establish a reputation for finding data problems before they impact the team * Run direct client working sessions on data scope, quality, or access with confidence * Demonstrate faster, higher-quality output by weaving AI tools into your daily workflow ### What You’ll Bring * **Full-Stack Data Skills:** Deep expertise in **SQL, Python, machine learning, data modeling, and pipeline development** with messy, real-world source systems * **Data Quality Instincts:** Ability to find issues, quantify impact, and communicate findings proactively * **Fast-Paced Delivery:** Comfort operating in fast-moving, sprint-based consulting environments with shifting requirements * **Client-Facing Communication:** Ability to translate technical findings into plain language and build credibility quickly * **Finance / PE Context:** Familiarity with ERP systems, FP&A data, financial close processes, or portfolio company data infrastructure * **AI Tool Integration:** Daily use of AI tools across exploration, modeling, documentation, and communication --- ## Role 2: AI Engineer (AI-Augmented Delivery Pods) ### About The Role As an AI Engineer in an AI-augmented delivery pod, you design and build the AI systems that power client engagements: agentic workflows, RAG pipelines, evaluation frameworks, and production-grade tools operating in real PE environments. You will work directly with clients and cross-functional pod teammates from day one at sprint pace. ### What You’ll Do * **Agentic Systems & RAG:** Design and build multi-agent systems and RAG pipelines that automate financial workflows for PE-backed portfolio companies * **Full-Stack Ownership:** Own the pipeline from prompt engineering and tool design through deployment and monitoring * **Eval-Driven Development:** Define success metrics and evaluation methodologies *before* building * **Architectural Defense:** Present and defend architectural decisions to technical and non-technical audiences, including CFOs and PE operators * **Observability & Infrastructure:** Build observability and evaluation infrastructure to continuously track and improve production AI system quality ### Success in the First 6 Months * Ship at least one end-to-end agentic solution in a client engagement from scoping through production * Establish evaluation infrastructure for your pod’s systems to measure quality and catch regressions early * Demonstrate materially faster delivery cycles through daily use of AI tools * Build a reputation with clients and teammates as a trusted owner of complex problems ### What You’ll Bring * **Experience:** **3–8+ years** of software engineering experience with a significant focus on AI/ML systems, agent development, or applied LLM engineering * **Production LLM Applications:** Hands-on experience building RAG systems, agentic workflows, tool calling, and multi-agent orchestration * **Tech Stack:** Proficiency in **Python**; experience with frameworks like **LangChain, LangGraph, AutoGen, DSPy**, or equivalents * **Evaluation & Data Engineering:** Strong grasp of eval methodologies (catching regressions, output quality scoring) and data engineering fundamentals (ETL, SQL/NoSQL, vector databases, pipelines) * **AI Tool Mastery:** AI tools woven into your daily workflow with concrete, demonstrable speed improvements ### Nice to Have * Open-source contributions in the AI/ML space * Domain experience in finance or private equity (FP&A, GL data, NetSuite, SAP) * Experience building multi-tenant architectures or tools for cross-client reuse * Prior consulting, professional services, or client-facing delivery experience --- ## Compensation, Location & Key Details * **Base Salary Range:** **$144,500 – $230,000 USD** + significant bonus + benefits * **Location:** Based in any US Accordion office location (Hybrid: flexibility to work remotely 2 days a week; must be local to office) * **Immigration:** Position is **not eligible** for visa sponsorship

## About Human Longevity, Inc. (HLI) **Human Longevity, Inc. (HLI)** is a leader in precision health, combining genomics, advanced imaging, biomarker testing, and artificial intelligence to transform the future of proactive healthcare. Our mission is simple: help people live longer, healthier lives through earlier detection, personalized insights, and data-driven healthcare. --- ## About The Role We believe AI will fundamentally reshape healthcare over the next decade. We are looking for an exceptional **Applied AI Engineer** who can help build that future. This is not a traditional data science role. This is a **hands-on engineering role** focused on building, deploying, and scaling real-world AI applications that create measurable impact across clinical, operational, and member experiences. --- ## What You'll Do * **Build AI Products:** Design, rapidly prototype, and deploy AI-powered applications from concept to production, partnering directly with clinicians and business stakeholders * **Build AI Agents:** Design and deploy autonomous and semi-autonomous AI agents, implementing multi-agent workflows to automate complex healthcare processes * **Develop LLM Applications:** Build state-of-the-art Large Language Model applications and **Retrieval-Augmented Generation (RAG)** systems across structured and unstructured healthcare data * **Engineer AI Infrastructure:** Build scalable data pipelines, AI services, and reusable APIs while improving the reliability, observability, and security of AI systems * **Own End-to-End Delivery:** Take full ownership from idea through production deployment, continuously evaluating and improving AI solutions based on real-world outcomes --- ## Required Qualifications * **Healthcare Experience (Required):** **4+ years** of experience building software, AI, or data-driven applications within healthcare, life sciences, genomics, diagnostics, or clinical environments * **Healthcare Data Experience:** Direct experience working with clinical records, laboratory data, genomics data, imaging reports, or healthcare operational workflows * **AI Engineering Experience:** Proven track record building and deploying production AI applications, with hands-on expertise in **LLMs, RAG, agentic AI systems**, and prompt engineering * **Technical Skills:** Strong proficiency in **Python, SQL**, APIs, and modern database technologies * **Software Architecture:** Familiarity with cloud platforms, distributed systems, testing, and modern software engineering practices --- ## Preferred Qualifications & Tech Stack * Experience with **genomics, precision medicine, longevity medicine**, radiology, or advanced diagnostics * Familiarity with healthcare interoperability standards (**FHIR and HL7**) and healthcare privacy/compliance requirements * Experience building **clinician-facing** or **patient-facing** AI products * Hands-on experience with foundation models (**OpenAI, Anthropic, Gemini**, etc.) * Experience with agent frameworks and orchestration platforms like **LangGraph, LangChain, CrewAI, AutoGen, or PydanticAI** * Familiarity with vector databases and enterprise search systems --- ## Who Thrives Here & Why Join * **You are a builder:** You love shipping products quickly, prefer real-world impact over academic research, and can move from concept to production with minimal oversight * **You love solving messy problems:** You are energized by startup environments, rapid iteration, and the future of AI agents * **Mission-Driven Impact:** You want to work at the cutting-edge intersection of AI, genomics, and diagnostics to advance HLI’s mission of extending healthy human lifespans

## About the Role **Zof AI** is seeking a **Machine Learning Engineer** for the traditional ML discipline: training, fine-tuning, and evaluating models rather than only building on top of them. This role owns datasets, training pipelines, and the applied models that power verification and quality systems inside our products. The ideal candidate is rigorous about evaluation, comfortable owning the full model lifecycle, and pragmatic about when a trained model beats an API call. --- ## Responsibilities * **Train, fine-tune, and evaluate models** for production use * **Build and maintain datasets**, labeling pipelines, and data quality checks * **Own training infrastructure** and experiment tracking * **Develop applied models** that power verification and quality features * **Establish rigorous evaluation** and regression testing for models * **Make architectural decisions** on when to train, when to fine-tune, and when to call an API * **Collaborate** with AI and product engineers to ship models into features * **Own the model lifecycle** from data gathering through production monitoring --- ## Requirements * Hands-on experience **training and fine-tuning models** * Strong grounding in **ML fundamentals and evaluation methodology** * Experience with **Python** and the modern ML stack * Experience building **datasets and data pipelines** * Strong **software engineering discipline** * Clear written and verbal communication * Comfort operating in a fast-moving environment * Evidence of **models shipped to production** or rigorous applied work --- ## Nice to Have * Experience **fine-tuning LLMs** or working with embeddings at scale * Experience with **PyTorch, JAX**, or similar frameworks * Experience with **model serving and inference optimization** * Published work, competition results, or strong open-source contributions in **Machine Learning, Model Training, Fine-Tuning, Datasets, or Evaluation**

## About Tessera Labs Tessera Labs is redefining how enterprises adopt and operationalize Artificial Intelligence. Backed by **Foundation Capital** and led by a world-class founding team, we build **multi-agent AI systems** that can automate complex business workflows across platforms like SAP, Salesforce, Workday, Snowflake, MuleSoft, and more. Our mission: Bring real AI automation to the enterprise — with speed, precision, and measurable impact. We move fast, operate with extreme ownership, and build at the frontier of applied AI. --- ## The Role As we build to the next level, we’re looking for a **top-quality AI engineer** with a strong focus on AI agents—someone who knows how to leverage LLMs, both open-source and closed, in combination with complex tool-calling hierarchies and operational patterns. This is an opportunity to build scalable, secure, and high-impact AI technologies for the future of enterprise. We're looking for someone who enjoys building reliable, scalable systems that help teams move faster. If you take pride in cutting-edge AI, value clear ownership, and want to have a meaningful impact in a high-growth, fast-moving environment, you’ll fit right in. --- ## Key Responsibilities * **AI Agent Building (60%):** Develop complex multi-step agentic pipelines around open- and closed-source LLMs. Build tools enabling AIs to interact with critical enterprise software platforms. Ensure AI designs align with business objectives and industry best practices. * **ML Development & Fine-Tuning (30%):** Create data generation and processing pipelines to train and fine-tune custom ML models. Implement and manage training and evaluation pipelines for LLMs. * **Deployment & AI Systems Infrastructure (10%):** Manage AI infrastructure across platforms such as AWS, Azure, or GCP. Deploy inference endpoints and serve AI and LLM technologies as part of our core product infrastructure. --- ## Qualifications ### Required * **Education:** Bachelor’s degree, Master's degree, or Ph.D. in Computer Science, Engineering, or a related field * **Experience:** 5+ years of experience in software engineering, platform engineering, or related roles * Proven expertise in **AI model building and agent development** * Strong background in **ML and LLM-driven systems development** * Experience with **compound AI systems, vector databases, and tool-calling AIs** * Excellent problem-solving skills and the ability to work in a fast-paced, collaborative environment ### Preferred * Experience building and deploying **production-grade, large-scale AI applications** * Familiarity with **AI deployment, evaluation, and monitoring practices** * Strong communication skills with the ability to articulate complex technical concepts to non-technical stakeholders --- ## Compensation & Additional Details * **Compensation Range:** **$150,000 - $230,000** * *Recruitment Notice:* No third party may recruit, solicit candidates, publish job opportunities, use Tessera Labs’ name or branding, or represent that they are acting on behalf of Tessera Labs without prior written authorization. Any such activity conducted without explicit written consent is strictly prohibited.

## The Role & Impact You'll own the core AI systems that power **Gamma**: the models, prompts, and pipelines behind text, image, and layout generation. With over **1 million AI-generated presentations** and **6 million AI images** created every day, this work operates at massive scale. Your job is to elevate quality, evaluate new frontier models, and push into new capabilities and modalities. This role is about productizing existing foundation models, not training new ones. You'll focus on prompting, evaluating, and fine-tuning for maximum performance across Gamma's product surface. You'll also launch new modalities like voice and video, build the evaluation infrastructure to measure what "good" looks like, and own uptime, latency, and cost across our AI stack. You'll work closely with engineering and product to ship improvements that millions of users feel immediately. You'll thrive here if you're a tinkerer who loves pushing foundation models to their limits and you're equally comfortable writing prompts and writing production code. If you get excited about mixing **prompt engineering with software engineering** to unlock new AI capabilities, this is your role. --- ## Work Culture & Environment Our team has a **strong in-office culture** and works in person **4–5 days per week in San Francisco**. We love working together to stay creative and connected, with flexibility to work from home when focus matters most. --- ## What You'll Do * **Own Gamma's LLM and image prompts**, measuring and continuously improving quality at scale across text, layout, and visual generation * **Develop complex prompts** for new features using AI JSX, balancing creativity with reliability * **Build evaluation frameworks** for prompts and models, combining quantitative metrics with qualitative feedback to create better test sets * **Drive the AI roadmap** based on quality gaps, constantly evaluating new frontier models and methods * **Curate datasets** for fine-tuning open-source models and launch new modalities like voice and video * **Own analytics**, tracking, uptime, latency, and cost across Gamma's AI infrastructure --- ## What You'll Bring * **Proven track record** pushing foundation models to their limits, with hands-on experience building and evaluating prompts at scale * **Proficiency in TypeScript and Python**, with a software engineering foundation that lets you move fluidly between prompt engineering and production development * **Strong data instincts:** experience writing evals, designing metrics, and translating qualitative feedback into measurable, actionable improvements * **Self-sufficient** in gathering and cleaning data to inform prompt improvements and model evaluations * Experience with modern LLMs and image models such as **Flux and Imagen** *(Nice to have)* * Familiarity with AI tooling like **AI JSX** for prompting and **Braintrust** for evaluations *(Nice to have)* *If you're interested in this role but you don't meet every requirement, we encourage you to apply anyway! We're always excited about meeting great people.* --- ## Compensation * **Base Salary Range:** **$180,000 - $300,000** * **Benefits:** Plus comprehensive benefits & equity. Final offer amounts are determined by multiple factors, including but not limited to experience and expertise in the requirements listed above.