Optimizes and builds production inference systems for large language models at scale using PyTorch and high-performance tooling. Requires 3+ years experience in production code, OS concepts, and AI inference systems.

Develops and optimizes GPU-accelerated kernels and algorithms for ML/AI applications, co-designing with modeling, hardware, and software teams. Requires strong GPU programming expertise in CUDA/Triton and knowledge of ML models.

Develops and deploys state-of-the-art GenAI models and systems for Databricks products like Assistant and Genie. Requires 2-8 years ML engineering experience, proficiency in Python/PyTorch/TensorFlow, and expertise in LLMs.

Develops and deploys ML-based perception algorithms for robot object detection, pose estimation, tracking, and scene understanding. Integrates sensor fusion from cameras, LiDAR, IMUs; requires MS/PhD in ML/CS/robotics, expertise in computer vision, PyTorch/TensorFlow, and real-world robotics hardware.

Designs and deploys reinforcement and imitation learning algorithms for robotic manipulation tasks in dynamic environments. Requires MS/PhD, deep RL/IL expertise, PyTorch proficiency, and real-world ML deployment experience in a fast-paced startup.

Designs, builds, and owns core cognitive architectures for enterprise AI agent platform, blending AI research with production systems. Requires 7+ years engineering with 2+ years AI/ML production experience and deep Python backend expertise.

Leads a team of data scientists to deliver data-driven solutions for infrastructure capacity planning, performance optimization, reliability, and efficiency at Databricks. Requires 10+ years in infrastructure data science/ML and 5+ years management experience.

Build AI agent systems for legal workflows, optimizing performance via prompt engineering, model selection, tools, and evals. Requires 3+ years experience, Python proficiency, and LLM/agent framework expertise for mid/senior/staff levels.

Designs, implements, and optimizes high-performance GPU kernels for GenAI inference stack. Leads performance improvements, mentors engineers, and collaborates with ML and systems teams. Requires deep kernel programming and GPU architecture expertise.

Leads architecture, development, and optimization of GenAI inference engine for high-throughput, low-latency LLM serving. Requires 6+ years in performance-critical systems, deep ML inference expertise, CUDA/GPU programming, and distributed systems.

Designs and builds scalable, low-latency model serving infrastructure for AI/ML models across CPU/GPU workloads. Requires 10+ years in large-scale distributed systems and deep expertise in inference systems, architecture, and cross-team collaboration.

Designs and builds scalable, low-latency systems for serving frontier AI models on GPUs. Requires 10+ years in large-scale distributed systems, strong system design skills, and leadership in operational excellence; no prior AI experience needed.

Designs and builds scalable infrastructure for high-throughput, low-latency AI/ML model serving on CPU/GPU. Requires 5+ years in distributed systems, inference expertise, and strong system design skills.

PhD intern researches and develops techniques to adapt LLMs and AI systems for enterprise domains, including method design, evaluation, and efficient post-training. Requires deep learning proficiency, PyTorch skills, and ongoing PhD studies.

Leads technical direction and development of Unity Catalog's governance features for secure data and AI asset management at scale. Requires 15+ years in large-scale distributed systems, deep CS expertise, and strong leadership.

Develops distributed data systems like Apache Spark and Delta Lake at massive scale, ensuring high performance and reliability for exabyte-scale workloads. Requires 8+ years in Java/Scala/C++ and deep distributed systems expertise.

Leads data science initiatives to inform business decisions, generate strategic insights for engineering priorities, and build production ML tooling. Requires 7+ years experience, strong Python/SQL/Spark skills, and MS/PhD in quantitative field.

Develops ML models for fraud/abuse detection and anomalous activity on Databricks platform. Analyzes security features, collaborates cross-functionally, and deploys production solutions. Requires 7+ years experience, MS in quantitative field, Python/SQL/Spark expertise.

Develop distributed data systems including Apache Spark and Delta Lake to handle big data workloads efficiently. Requires 5+ years in Java/Scala/C++ and expertise in distributed systems.

Senior engineer building distributed data systems like Apache Spark and Delta Lake to handle big data processing, ETL, and data science workloads. Requires 5+ years in Java/Scala/C++ and expertise in distributed systems.

Staff Data Scientist drives data-driven decisions through segmentation, recommendations, forecasting, and product analytics. Collaborates cross-functionally, mentors juniors, and requires 7+ years experience with Python/Scala, Spark, SQL, and MS/PhD.

Analyze player behavior data for ChessKid to drive growth and monetization through insights on retention, engagement, and experiments. Collaborate with product and business teams using Amplitude, BigQuery, SQL, and Python.

Builds high-performance infrastructure for brain reverse-engineering via large-scale AI models and neuroscience-informed simulations. Architects systems, optimizes RL environments, and scales research prototypes to production.

Leads development of Airbnb's conversational AI Automation Platform and agent provisioning systems. Drives backend optimization, prompt engineering, and LLM integrations with 9+ years experience in scalable architectures.

Builds and owns customer data integrations for hospital systems, designing production ETL pipelines and reusable connectors. Requires 4+ years experience with Python, SQL, AWS, and direct customer collaboration in ambiguous environments.

Build evaluation infrastructure for AI systems at Sentry, designing datasets, benchmarks, and test harnesses to measure accuracy and reliability of debugging agents. Requires 5+ years experience, Python/TypeScript proficiency, and AI/ML background.

Leads establishment of measurement practice for creator marketing, defining ROI frameworks, advising top brands on MMM/incrementality/attribution, and driving product roadmap for scalable analytics.

Builds large-scale ML infrastructure including GPU clusters, training frameworks, and workload schedulers. Requires strong systems engineering in Python, Rust, Golang, with Kubernetes and distributed systems experience.

Staff Data Scientist owns product measurement strategies, leads cross-team initiatives, sets experimentation standards, and builds scalable analytics for product areas. Requires 10+ years experience, SQL/Python expertise, and strong causal inference skills.

Build and operate production AI systems including LLM-powered agents, model orchestration, RAG, and backend APIs for tax automation workflows. Requires 7+ years experience with 2+ in LLMs, backend fluency, and startup intensity.

Builds distributed training, inference, and data systems for frontier coding models, working with researchers to enable fast iteration. Requires strong infrastructure background and intuitions about language models.

Designs and trains embedding and retrieval models for AI agents to access web data at hyperscale, balancing research innovation with production efficiency for sub-second latency and fresh indexes.

Builds analytical metrics, dashboards, automations, and reporting systems for risk and broader business decisions. The role requires strong SQL and Python skills, sound data modeling, business judgment, and the ability to solve ambiguous problems independently.

Build full-stack systems, tools, and infrastructure for human feedback collection, AI model alignment, and evaluation. Collaborate with researchers to scale production systems and enhance model safety in a fast-paced environment.

Develops and optimizes AI and LLM inference kernels for Quadric’s neural processing platform, profiling performance across hardware configurations and improving compiler and runtime components. Requires 5+ years of kernel optimization experience, strong C/C++ and Python skills, and familiarity with CUDA, DSP, NEON, or Triton.

Pioneers quantitative research for music generation AI using proprietary datasets, designs evaluation frameworks for models, drives data roadmaps, and builds production infrastructure at the intersection of research, engineering, and product. Requires PhD or 5+ years quant experience with strong coding skills.

Develops and optimizes inference engines for multimodal AI models, integrating new architectures, building scheduling systems, and managing large-scale GPU deployments. Requires strong Python, model serving frameworks like PyTorch/vLLM, and Kubernetes expertise.

Conducts cutting-edge research in Generative AI, building foundation models and autonomous agents for cloud observability, SRE, and code repair. Requires PhD in ML or related field, publications at top conferences, and expertise in PyTorch/TensorFlow distributed training.

Lead GenAI/ML initiatives for Datadog's APM team, designing and deploying models for agentic workflows, automated investigations, and performance optimization. Requires 10+ years experience with 4+ years leading cross-team projects.

Lead development of LLM observability features at Datadog, building tools for monitoring, tracing, and evaluating AI systems in production. Requires expertise in distributed systems, GenAI applications, and model internals.

Builds and deploys ML models for sleep personalization, readiness forecasting, and behavior prediction using foundation models and multimodal data. Requires 2+ years production ML experience with PyTorch/TensorFlow, personalization systems, and strong Python engineering.

Leads the technical vision and implementation of Docker’s containerized AI agent platform, including runtime infrastructure, distributed systems, evaluation, and operational excellence. The role requires 10+ years of software engineering experience, principal-level technical leadership, and practical experience with Go, Docker, and LLM-based agent development.

Build analytics foundation for Deepgram's voice AI platform, owning self-serve growth strategy, experiments, and dashboards using SQL, Superset, and Heap. Partner with product team to drive API adoption and inform strategic investments.

Build marketing data science function, define metrics and dashboards, model channel/campaign performance using stats/ML. Partner with Marketing/GTM/Finance; requires 6+ years experience, SQL/Python/R expertise, modern data stack proficiency.

Conduct cutting-edge research on Large Language Models, focusing on transformer optimization, distributed training, data curation, and RL. Collaborate on experiments, deploy models to production, and drive voice AI innovations.

Pioneers Latent Space Models to solve core challenges in voice AI, developing neural audio codecs, generative speech models, and scalable multimodal systems. Requires strong expertise in statistical learning, foundation models, and bridging theory to efficient deployment.

Leads the architecture and performance of high-throughput real-time streaming and Lakehouse data platforms. The role requires 8+ years of software engineering experience, deep Scala or Java and JVM expertise, extensive Kafka experience, and strong AWS capabilities.

Develops and customizes large language and deep learning models for customer-specific applications, owning training, fine-tuning, evaluation, and agentic-system development. Requires advanced graduate education, hands-on experience with 1B+ parameter models, Python, PyTorch, and distributed training.

Build and maintain scalable data models, pipelines, and Core Data tables to transform raw data into actionable insights. Collaborate with data scientists and business teams using SQL, DBT, Snowflake, Airflow, and Python.

Develops novel C++ computer vision algorithms and real-time perception pipelines for autonomous platforms. The role requires strong computer vision, image processing, machine learning, and high-performance systems expertise, with deep learning and robotics experience advantageous.