Build and scale AI agents automating healthcare workflows. Lead complex feature development using JavaScript/TypeScript/Node.js, LLMs, and DevOps tools. Requires 4+ years experience and CS degree.
Leads development of agentic AI platform to autonomously resolve healthcare insurance claim denials using multi-agent workflows, RAG systems, and LLMs. Requires 5+ years in production ML engineering with Python and frameworks like PyTorch.
Leads design, development, and deployment of AI agents using language models and ML frameworks. Drives scalable, safe AI systems while mentoring teams and collaborating cross-functionally. Requires strong Python skills and AI leadership experience.
Build and improve ML systems and data pipelines infrastructure to support modeling engineers. Requires 2+ years experience, bachelor's in CS/math/sciences, strong coding in Python/Go/Java/C++, and production ML infra expertise.
Leads design and execution of AI strategy for legal discovery platform, guiding engineering teams on LLMs, NLP, and frontier models at massive scale. Requires 6+ years ML/AI experience and 10+ years software engineering.
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 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.
Builds ML platform infrastructure including evaluation/release gates, debug tooling, chart context retrieval, data pipelines, and model serving to accelerate AI improvements for clinical workflows. Requires 7+ years software engineering with 3+ in ML infra/platform, strong Python/TypeScript backend skills.
Develops AI-powered solutions using LLMs to improve code security vulnerability detection, prioritization, and remediation. Collaborates with customers, implements end-to-end features, and evaluates models through experimentation on real-world data.
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.
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.
Builds and productionizes ML models for host personalization products using NLP and computer vision. Requires 8+ years experience, MS/PhD, strong programming, and expertise in ML infrastructure and large-scale data pipelines.
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, develops, and optimizes GenAI inference engine for LLMs, focusing on performance, scalability, and efficiency across the full stack. Requires 3+ years in performance-critical systems, CUDA/GPU expertise, and ML inference knowledge.
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.
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.
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, 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.
Build customer-facing generative AI platform covering ML lifecycle from data generation to agent-building. Requires 4+ years experience in distributed systems and ML platforms, with strong product ownership.
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.
Leads technical enablement and adoption of OpenAI products like ChatGPT Enterprise, API, and Agents for enterprise customers through workshops and trainings. Requires 4+ years customer-facing experience, strong AI technical knowledge including RAG and fine-tuning, and exceptional communication skills.
Designs and optimizes prompts for social AI characters to ensure realistic personality, emotion, and behavior across text, voice, image, and video. Collaborates with product, design, and engineering on scalable systems; requires 3+ years LLM experience and Python familiarity.
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.
Develops and deploys AI models for robotic perception, control, inspection, and simulation-to-real transfer in manufacturing environments. Requires Master's/PhD, 5+ years experience, PyTorch proficiency, and hands-on robotics work.
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.
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.
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.
Build advanced search quality systems using machine learning, including personalization signals, ranking models, and domain-adapted LLMs for enterprise search. Requires 2+ years experience in ML, search/NLP, strong coding in Python/Go/Java/C++, and bachelor's in CS/math.
Build and scale ML compute infrastructure and distributed training pipelines for foundation models. Optimize GPU/CPU efficiency and data throughput for large-scale model training and inference.
Develops AI-driven code conversion, data migration pipelines, and validation tools for migrating applications to Snowflake. Requires strong Python expertise, agentic AI experience, and distributed systems knowledge.
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.
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.
Build AI-assisted tools using LLMs to generate tests, fix bugs, and boost developer productivity at Datadog. Requires 5+ years backend experience in Go/Java/Python and shipping LLM software to production.
Leads development of LLM- and agent-based features for Datadog's APM to detect, resolve, and prevent performance issues using traces, metrics, and logs. Requires 4+ years in backend/ML systems, production AI experience, and distributed systems expertise.
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.
Owns end-to-end lifecycle of memory features in AI systems, fine-tuning LLMs for extraction/updates/forgetting, implementing research papers, building large-scale evaluations, and shipping production models with engineering. Requires RAG/IR experience, PyTorch proficiency, and production ML expertise.
ML infrastructure engineer productionizing generative AI models from research to scale, optimizing multi-GPU inference, and building reliable serving systems. Requires 4+ years ML inference experience, PyTorch, Kubernetes expertise.
Designs prompt and context engineering strategies for AI products, builds evaluation pipelines, and ensures model quality and behavioral consistency. Requires 3+ years with LLMs, Python experience, and expertise in AI evaluations.
Build and maintain core GenAI infrastructure including model gateways, vector databases, observability tools, and integration with agent workflows. Requires extensive AI platform experience, Kubernetes, OpenTelemetry/MLFlow, and preferred LLM serving frameworks.
Lead the design, build, and operation of multi-agent AI systems from prototypes to production, owning architecture, reliability, and performance for consumer AI products. Requires strong production experience with LLM-powered systems, agentic workflows, and backend engineering.
Develop and enhance TypeScript-based AI SDK for building AI-native products and agents. Collaborate with distributed engineering team; requires 5+ years experience in JavaScript/TypeScript and open source contributions.
Research-Hardware Codesign Engineer bridges ML research and silicon architecture, debugging performance gaps, writing quantization kernels, prototyping numerics in RTL, and analyzing system tradeoffs for AI-optimized hardware.
Build and operate high-performance inference infrastructure for large language models, deploying optimized NLP models to production with low latency and high throughput using Kubernetes and cloud platforms. Requires 5+ years experience in scalable distributed systems and GPU workloads.
Build and ship full-stack AI projects including AI agents, RAG, structured extraction, and LLM infrastructure. Requires proficiency in full-stack development, backend systems, cloud infrastructure, and production LLM experience.
Builds scalable ML systems and end-to-end pipelines for fraud detection, anomaly detection, and real-time decisioning in payments. Requires 5+ years ML production experience, including 2+ in fraud/risk, Python proficiency, and ML frameworks like PyTorch/TensorFlow.
Leads AI/ML organization by setting technical vision, building and mentoring data scientists/ML engineers, architecting scalable ML infrastructure, and hands-on prototyping models for healthcare applications. Requires PhD, 8+ years shipping ML products, and 3+ years leading ML teams.
Build and scale AI agents automating healthcare workflows. Lead complex feature development using JavaScript/TypeScript/Node.js, LLMs, and DevOps tools. Requires 4+ years experience and CS degree.
Leads development of agentic AI platform to autonomously resolve healthcare insurance claim denials using multi-agent workflows, RAG systems, and LLMs. Requires 5+ years in production ML engineering with Python and frameworks like PyTorch.
Leads design, development, and deployment of AI agents using language models and ML frameworks. Drives scalable, safe AI systems while mentoring teams and collaborating cross-functionally. Requires strong Python skills and AI leadership experience.
Build and improve ML systems and data pipelines infrastructure to support modeling engineers. Requires 2+ years experience, bachelor's in CS/math/sciences, strong coding in Python/Go/Java/C++, and production ML infra expertise.
Leads design and execution of AI strategy for legal discovery platform, guiding engineering teams on LLMs, NLP, and frontier models at massive scale. Requires 6+ years ML/AI experience and 10+ years software engineering.
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 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.
Builds ML platform infrastructure including evaluation/release gates, debug tooling, chart context retrieval, data pipelines, and model serving to accelerate AI improvements for clinical workflows. Requires 7+ years software engineering with 3+ in ML infra/platform, strong Python/TypeScript backend skills.
Develops AI-powered solutions using LLMs to improve code security vulnerability detection, prioritization, and remediation. Collaborates with customers, implements end-to-end features, and evaluates models through experimentation on real-world data.
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.
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.
Builds and productionizes ML models for host personalization products using NLP and computer vision. Requires 8+ years experience, MS/PhD, strong programming, and expertise in ML infrastructure and large-scale data pipelines.
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, develops, and optimizes GenAI inference engine for LLMs, focusing on performance, scalability, and efficiency across the full stack. Requires 3+ years in performance-critical systems, CUDA/GPU expertise, and ML inference knowledge.
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.
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.
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, 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.
Build customer-facing generative AI platform covering ML lifecycle from data generation to agent-building. Requires 4+ years experience in distributed systems and ML platforms, with strong product ownership.
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.
Leads technical enablement and adoption of OpenAI products like ChatGPT Enterprise, API, and Agents for enterprise customers through workshops and trainings. Requires 4+ years customer-facing experience, strong AI technical knowledge including RAG and fine-tuning, and exceptional communication skills.
Designs and optimizes prompts for social AI characters to ensure realistic personality, emotion, and behavior across text, voice, image, and video. Collaborates with product, design, and engineering on scalable systems; requires 3+ years LLM experience and Python familiarity.
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.
Develops and deploys AI models for robotic perception, control, inspection, and simulation-to-real transfer in manufacturing environments. Requires Master's/PhD, 5+ years experience, PyTorch proficiency, and hands-on robotics work.
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.
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.
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.
Build advanced search quality systems using machine learning, including personalization signals, ranking models, and domain-adapted LLMs for enterprise search. Requires 2+ years experience in ML, search/NLP, strong coding in Python/Go/Java/C++, and bachelor's in CS/math.
Build and scale ML compute infrastructure and distributed training pipelines for foundation models. Optimize GPU/CPU efficiency and data throughput for large-scale model training and inference.
Develops AI-driven code conversion, data migration pipelines, and validation tools for migrating applications to Snowflake. Requires strong Python expertise, agentic AI experience, and distributed systems knowledge.
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.
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.
Build AI-assisted tools using LLMs to generate tests, fix bugs, and boost developer productivity at Datadog. Requires 5+ years backend experience in Go/Java/Python and shipping LLM software to production.
Leads development of LLM- and agent-based features for Datadog's APM to detect, resolve, and prevent performance issues using traces, metrics, and logs. Requires 4+ years in backend/ML systems, production AI experience, and distributed systems expertise.
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.
Owns end-to-end lifecycle of memory features in AI systems, fine-tuning LLMs for extraction/updates/forgetting, implementing research papers, building large-scale evaluations, and shipping production models with engineering. Requires RAG/IR experience, PyTorch proficiency, and production ML expertise.
ML infrastructure engineer productionizing generative AI models from research to scale, optimizing multi-GPU inference, and building reliable serving systems. Requires 4+ years ML inference experience, PyTorch, Kubernetes expertise.
Designs prompt and context engineering strategies for AI products, builds evaluation pipelines, and ensures model quality and behavioral consistency. Requires 3+ years with LLMs, Python experience, and expertise in AI evaluations.
Build and maintain core GenAI infrastructure including model gateways, vector databases, observability tools, and integration with agent workflows. Requires extensive AI platform experience, Kubernetes, OpenTelemetry/MLFlow, and preferred LLM serving frameworks.
Lead the design, build, and operation of multi-agent AI systems from prototypes to production, owning architecture, reliability, and performance for consumer AI products. Requires strong production experience with LLM-powered systems, agentic workflows, and backend engineering.
Develop and enhance TypeScript-based AI SDK for building AI-native products and agents. Collaborate with distributed engineering team; requires 5+ years experience in JavaScript/TypeScript and open source contributions.
Research-Hardware Codesign Engineer bridges ML research and silicon architecture, debugging performance gaps, writing quantization kernels, prototyping numerics in RTL, and analyzing system tradeoffs for AI-optimized hardware.
Build and operate high-performance inference infrastructure for large language models, deploying optimized NLP models to production with low latency and high throughput using Kubernetes and cloud platforms. Requires 5+ years experience in scalable distributed systems and GPU workloads.
Build and ship full-stack AI projects including AI agents, RAG, structured extraction, and LLM infrastructure. Requires proficiency in full-stack development, backend systems, cloud infrastructure, and production LLM experience.
Builds scalable ML systems and end-to-end pipelines for fraud detection, anomaly detection, and real-time decisioning in payments. Requires 5+ years ML production experience, including 2+ in fraud/risk, Python proficiency, and ML frameworks like PyTorch/TensorFlow.
Leads AI/ML organization by setting technical vision, building and mentoring data scientists/ML engineers, architecting scalable ML infrastructure, and hands-on prototyping models for healthcare applications. Requires PhD, 8+ years shipping ML products, and 3+ years leading ML teams.