Build and evolve the distributed training framework and tooling powering frontier-scale language models. The role focuses on large-scale ML systems, HPC infrastructure, performance optimization, reliability, and developer tooling across multi-node GPU clusters.

Build and optimize synthetic data and inference pipelines for large language models, combining research and software engineering to improve data quality, throughput, and model performance. The role requires strong Python and data-pipeline experience, familiarity with LLM inference frameworks, and experience with large-scale datasets.

Builds and leads the development of large-scale distributed data systems and pipelines that power products and organizational decision-making. The role requires 7+ years of data engineering experience, cloud expertise, and strong technical leadership.

Owns full data stack including database architecture, ETL/ELT pipelines, integrations, and product/GTM reporting. Requires 4+ years experience, expert SQL/Python, ETL tools, data modeling, and statistics. Based in SF or NYC.

Develops and deploys ML models for parsing unstructured enterprise data like PDFs, focusing on training vision models, experimenting with LLMs, building data pipelines, and integrating into products. Requires 2+ years in production ML, Python proficiency, and computer vision expertise.

Builds and optimizes backend APIs and pipelines for document parsing using LLMs, handling PDFs/spreadsheets at scale. Requires 2+ years experience, exceptional Python, and high agency in production AI systems.

Build and optimize Cerebras’s production GPU prefill and inference stack across APIs, serving runtimes, ROCm, distributed systems, and hardware. The role requires 5+ years of software engineering experience, strong C++ and Python skills, and hands-on experience operating high-performance model-serving systems.

Data Scientist embedded across Product, Finance, Marketing, and Platform teams to build models, design experiments, develop data pipelines, and drive strategic insights using Python, SQL, and distributed systems. Requires 4+ years experience and cross-functional collaboration.

Builds and deploys fine-tuned LLMs and AI agents for real-time voice interactions in consumer lending, ensuring compliance and scalability. Requires 2+ years production ML/AI experience with Python, PyTorch/TensorFlow, and LLM frameworks.

Partners with customers to design, prototype, and scale AI-enhanced coding workflows using OpenAI Codex. Serves as technical expert, leads workshops, builds demos, and influences product direction. Requires 5+ years in technical consulting or solutions engineering.

Build scalable AI platforms and infrastructure for Figma's design tools, including model training, agentic features, and APIs. Requires 5+ years software engineering experience with backend/infrastructure and 3+ years in AI or developer platforms.

Build and productionize ML models for search, RAG, and generative AI features at Figma. Requires 5+ years software engineering with 3+ years in applied ML, Python proficiency, and experience with scalable data pipelines.

Develops machine learning models to predict and optimize organoid growth and differentiation protocols using biological data. Requires Master's/PhD in CS/engineering/math, Python/R proficiency, and ML frameworks like TensorFlow/PyTorch, with biology lab experience.

Pioneers innovative ML techniques and builds foundation models for clinical information extraction and synthesis from medical records. Requires PhD in CS/math with NLP/ML focus, high-impact publications, and experience with large-scale model training using PyTorch/JAX.

Analyzes user behavior and product experiments to drive insights for growth, retention, and enterprise strategy at Replit. Requires 5+ years in product analytics, strong SQL/Python skills, and expertise in A/B testing and causal inference.

Designs, develops, and deploys scalable ML systems using LLMs to process clinical data for healthcare applications. Requires 5+ years backend/cloud experience, Python fluency, and familiarity with ML frameworks; works onsite in Boston or NYC.

Designs and scales distributed data infrastructure for large-scale multimodal training and evaluation at OpenAI. Collaborates with researchers to build reliable, high-performance systems handling massive data volumes in a fast-paced environment.

Designs and implements LLM orchestration frameworks and agent reasoning systems for adaptive mission planning in multi-domain unmanned systems. Optimizes AI models for edge deployment on autonomous vehicles, integrating with ROS autonomy stack for mission-critical operations.

Build and scale agentic AI systems for mission-critical public-interest applications while researching and shipping state-of-the-art models. The role requires strong software engineering, Python and ML framework expertise, LLM experience, distributed GPU training knowledge, and Canadian citizenship with security-clearance eligibility.

Develops high-performance audio inference systems, optimizing latency, throughput, and quality for real-time streaming workloads. Requires expertise in C++, Python, and deep learning models for audio/speech, with collaboration across training and serving teams.

Develops and deploys techniques to enhance LLM inference efficiency, focusing on architecture optimization, decoding algorithms, and GPU acceleration. Requires PhD in ML, expertise in LLM optimization, strong software skills, and top-tier publications.

Engineers on this team optimize LLM inference for lower latency and higher throughput by identifying bottlenecks, developing optimizations across the execution stack, and collaborating with modeling teams. Requires 5+ years high-performance coding in C++/Python and LLM inference experience.

Designs and develops large-scale data applications and pipelines using Java, Spark, Scala, Kafka, Hadoop, and AWS. Requires at least six years of Java development experience focused on data engineering and streaming platforms.

Trains frontier LLMs on semiconductor design/verification data (RTL, netlists, PDKs) for automated chip development. Develops synthetic data generation, model distillation, evals, and scales training across thousands of GPUs.

Post-trains frontier AI models using reinforcement learning to autonomously handle semiconductor design tasks like chip architecture optimization, RTL code generation, simulations, and verification. Collaborates with hardware experts to build RL environments, reward functions, and evaluation frameworks.

Develop and prototype AI-driven solutions for GTM, Finance, and People teams, translating business problems into impactful prototypes using ML/AI and LLMs. Requires 4-8 years as Software Engineer or Data Scientist with production AI familiarity.

Build and maintain scalable backend infrastructure for Fireworks AI's generative AI platform, including LLM CI/CD pipelines, control planes, and model serving systems. Requires 5+ years software engineering experience focused on ML/infrastructure, strong Python/Go skills, and familiarity with PyTorch, Kubernetes, and LLM concepts.

Lead technical development of ML algorithms for next-generation ML Planner. Drive innovations in imitation learning, reinforcement learning, and model scaling while mentoring ML developers.

Build and deploy LLM-powered agents and production AI/NLP pipelines, focusing on RAG, agentic systems, model optimization, and scalable deployment. The role requires 3+ years of machine learning or applied AI experience, strong Python skills, and experience with modern ML frameworks and infrastructure.

Develops agentic AI platforms for triaging, debugging, and resolving production issues using Sentry's error datasets. Requires 5+ years experience, Python/TypeScript proficiency, PyTorch, and expertise in scalable ML deployment.

Researches, develops, evaluates, and optimizes machine learning models across the full research lifecycle, with a focus on novel methods, scalable training, and efficient inference. Requires strong Python, software engineering, machine learning fundamentals, and experience with GPUs or TPUs and distributed training.

Develops and optimizes internal distributed ML training framework to boost hardware efficiency and enable researchers to experiment with new AI models. Requires strong Python skills, systems understanding, and passion for performance tuning.

Machine Learning Engineer optimizes ML models for speed and efficiency through low-level CUDA kernel tuning, GPU scheduling, and hardware-aware systems design. Requires 2+ years in ML infrastructure with Python/C++/Rust and distributed frameworks like PyTorch.

Advances small, high-performance language models for retrieval, application, and code generation. Requires 2+ years ML research/production experience, Python/PyTorch/JAX fluency, optimization expertise, and advanced degree.

Builds and productionizes LLM-powered agent workflows, focusing on orchestration, evaluation, reliability, safety controls, and product iteration. Requires strong agentic systems expertise and engineering skills for scalable AI systems.

Designs and runs massive-scale data pipelines for ingestion, normalization, enrichment, and delivery across 80M+ companies and 800M+ people. Manages data operations, BPO vendors, partnerships, monitoring, and cost optimization using Python, Dagster, and DuckDB.

Build scalable data infrastructure to ingest and process millions of hardware telemetry data points per second. Requires 7+ years in data engineering, streaming systems like Flink/Kafka, databases like PostgreSQL/Druid, and languages like Go/Rust/Python.

Build and productionize AI-powered product features for scientific communication, spanning full-stack development, LLM applications, and machine learning infrastructure. The role requires 7+ years of full-stack experience, strong JavaScript and Python skills, and hands-on experience deploying AI systems in production.

AI Enablement Engineers guide enterprise teams in adopting Devin AI software engineer, leading workshops, pair programming on real projects, and scaling enablement programs globally. Requires 3+ years software engineering experience in Python/JS, strong communication, and customer-facing skills.

Builds and optimizes LLM-driven features, agentic workflows, and proprietary AI models for Bubble's visual app development platform. Requires Master's/PhD + 2+ years or 5+ years ML/software experience with transformers, RAG, and AI tools.

Lead AI research defining the agenda for trustworthy agentic systems, memory, retrieval, and evaluation frameworks. PhD required with 5+ years focused on LLMs/agents and a strong publication record; work ships directly to production for high-stakes financial users.

Builds production machine learning capabilities for autonomous vehicle perception, prediction, and planning systems. The role requires deep learning expertise, strong C++ or Python skills, and at least three years of production software experience.

Conducts research and builds benchmarks, methods, and infrastructure to evaluate the capabilities and progress of large language models. The role requires strong software engineering, prototyping, data-quality review, and rigorous measurement skills.

Develops, productionizes, and deploys end-to-end ML models for real-time clinical predictions using production Python/SQL. Owns model performance from prototyping to real-world impact, collaborating cross-functionally. Requires PhD + 3+ years shipping ML products.

Develop and optimize real-time multi-sensor fusion and state estimation algorithms (Kalman/particle filters, IMUs, radar, cameras) for autonomous X-BAT VTOL drone operation in contested environments on the GNC team.

Leads end-to-end applied ML research in NLP, LLMs, retrieval, and multimodal models for healthcare AI, driving from experimentation to production deployment with rigorous evaluation and clinician collaboration. Requires 7+ years experience, MS/PhD, and depth in ML areas like PyTorch tooling.

Applied AI Researcher on System Discovery team explores new AI system architectures, prototypes human-AI collaborations, and draws cross-domain insights to redefine enterprise workflows. Requires proven research track record, expertise in compound AI systems and agentic techniques, strong programming for rapid prototyping.

Designs self-constructing AI systems that autonomously generate, assemble, and refine subsystems using meta-learning, program synthesis, and evolutionary methods. Requires proven research in modular AI architectures, daily AI tool usage, and strong prototyping skills.

Designs feedback-driven AI architectures for system self-improvement, enabling autonomous evolution through reflection, retraining, and adaptation. Requires proven research in compound AI systems, daily AI tool usage, and strong prototyping skills.

Designs and researches compound AI systems integrating LLMs, agents, and execution components for reliable enterprise workflows. Requires proven AI research track record, daily AI tool usage, strong prototyping skills, and expertise in agentic techniques.