Design and deploy deep learning models on biosensor and time-series data to deliver personalized health metrics. Requires strong ML/DL fundamentals, publications, and 4+ years of research experience.
Designs and builds scalable backend systems and applies machine learning to address safety, integrity, and Generative AI risks. Requires 8+ years backend experience, ML expertise, and distributed systems knowledge.
Designs, builds, and deploys custom AI agents for enterprise customers, providing hands-on technical support, troubleshooting, and acting as technical account manager. Requires 3+ years customer-facing experience and expertise in Python, AWS, SQL, and AI agent frameworks like LangChain and CrewAI.
Owns voice AI infrastructure for insurance operations, building scalable outbound/inbound agents, customer service, and underwriting systems with sub-second latency. Requires 3-6 years experience in production voice AI and real-time systems.
Designs and builds AI agents, workflows, and evaluation systems for enterprise audit platforms. Requires experience shipping production software with TypeScript, React, Python, Postgres, LLMs, RAG, and agent orchestration.
Builds performance benchmarking, diagnostic, and optimization tools for LLM inference on GPU clusters. Early-career role requiring Python proficiency, systems curiosity, and interest in AI hardware—no prior experience needed.
Design and deliver custom LLM solutions for enterprise customers, train frontier models using Cohere's stack, and influence foundation model capabilities. Requires strong ML fundamentals, Python fluency, and customer-facing technical leadership.
Design and deliver custom LLM solutions for enterprise customers, train frontier models using Cohere's stack, and contribute to foundation model improvements. Requires strong ML fundamentals, Python fluency, and experience with LLMs and large-scale data.
Designs, builds, and deploys production-grade AI agents using LLMs for enterprise workflows. Collaborates with customers to solve business problems, ensures reliability, and mentors teams on agentic architectures.
Builds and deploys end-to-end AI/ML systems, including LLM workflows and rapid prototypes for internal tools and product features in healthcare. Requires 4+ years experience, strong full-stack skills, evaluation/monitoring expertise, and Python proficiency.
Build and maintain scalable ML platform for model experimentation, training, evaluation, inference, and feature store to power underwriting products. Requires 5+ years experience with Python, ML stacks like Databricks/AWS, and MLOps systems.
Designs, builds, and scales agentic AI systems using LLMs for compliance automation, including multi-step reasoning, RAG, and production deployment. Requires 7+ years software engineering with 2+ years ML/AI, Python proficiency, and cross-functional collaboration.
Builds sophisticated AI agent products for investigating financial crimes, leads technical designs and teams. Requires 4-10 years experience in software development, Python, cloud infrastructure, and hybrid SF Bay Area work.
Builds and deploys production-scale AI/ML systems using LLMs, from fine-tuning and evaluation to low-latency infrastructure. Requires 5+ years experience with PyTorch/TensorFlow, MLOps, AWS, and taking models to production at high-growth startups.
Develop ML models for generating realistic autonomous vehicle simulation scenarios, integrating LLMs/VLMs and agentic AI for safety validation. Requires 5+ years ML experience, MS/PhD, and proficiency in PyTorch, transformers, diffusion models.
Leads design and development of scalable, real-time API and data infrastructure for AI model evaluations, processing large-scale event streams with low latency. Requires 5+ years in infrastructure or ML systems, expertise in distributed systems, stream processing, and backend architecture.
Builds and optimizes ML backend systems for recommendation, ranking, and search in a fast-growing AI consumer app. Requires 5+ years experience, CS bachelor's, ML frameworks like PyTorch/TensorFlow, cloud infra, and modern typed languages.
Develops LLM/NLU systems and data pipelines to process medical records, classify patients, and recommend care levels for a healthcare AI platform. Requires 5+ years backend/data engineering experience with production LLMs and integration into user-facing features.
Develops ML models using imitation and reinforcement learning for agent behavior prediction and autonomous vehicle planning. Requires PhD +1 year or MSc +5 years experience, expertise in RL, transformers, and production ML pipelines.
Builds personalization and recommendation systems from scratch for AI creative tools, modeling user taste and curating feeds. Designs algorithms for generative models to adapt to individual aesthetics, using ML frameworks like PyTorch/JAX.
Builds and deploys AI primitives and agents to automate workflows and enhance user experiences in investment management platform. Requires AI agent experience, distributed systems knowledge, and product-minded engineering across tech stacks.
Designs and implements novel model serving architectures on in-house inference engine to maximize throughput and minimize latency for generative media models. Develops performance tools and collaborates with ML teams on Nvidia-based systems optimizations.
Designs, trains, and deploys deep learning models for drone autonomy, focusing on computer vision tasks like optical flow, depth estimation, detection, and path planning using real-world and synthetic data. Requires MS/PhD, hands-on DL experience, and PyTorch/Python/C++ proficiency.
Builds and scales deep learning infrastructure for autonomous drone computer vision workloads, optimizing inference for high throughput/low latency across hardware, and implements MLOps pipelines for model deployment and monitoring. Requires hands-on MLOps, DL/CV expertise, and ML pipeline experience.
Develops real-time deep learning models for drone autonomy, focusing on detection, tracking, segmentation, and optical flow using visual data. Requires hands-on experience with deep neural networks, computer vision, Python/C++, and model optimization for embedded hardware.
Develops and optimizes deep learning inference infrastructure for real-time computer vision workloads on drones, focusing on high-throughput, low-latency performance across hardware platforms. Builds MLOps workflows, GPU kernels, and SDKs; requires strong DL, CV, and ML pipeline expertise.
Builds and improves AI agents for complex accounting tasks, working across product engineering, agent platforms, infrastructure, and data systems at the frontier of applied ML. Requires strong systems thinking, ownership, and excitement for coding agents in a fast-changing environment.
Develops quantitative models for portfolio optimization, fixed income relative value, risk estimation, and AI agents for credit research and portfolio management at a fintech platform. Requires Python coding, quant background, and bachelor's/PhD in math-related field.
Design, train, and integrate ML models for semantic map element detection in autonomous vehicles. Requires 5+ years experience, MS/PhD in CS, expertise in computer vision, deep learning, and PyTorch.
Builds and operates production AI systems for WHOOP's AI platform, including evaluation pipelines, fine-tuning workflows, and LLM observability. Requires 3+ years in applied ML/AI engineering with hands-on experience in modern language models.
Builds and optimizes AI/ML analytics engine using scientific Python stack for public opinion measurement platform. Requires 5+ years experience in quantitative software, ML, and distributed systems.
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.
AI Inference Engineer ports, optimizes, and benchmarks AI/LLM models on Quadric's GPNPU platform for edge devices. Requires 5+ years in model inference frameworks, quantization expertise, and proficiency in C++/Python.
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.
Leads development of generative AI tools for fashion design, including image generation, editing, and workflows. Mentors ML engineers, conducts applied research on diffusion models, and drives production systems integrating cloud GPUs and multimodal LLMs. Requires 7+ years ML experience and Master's/PhD.
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.
Senior engineer owning end-to-end AI infrastructure including LLM orchestration, agent architectures, evaluation systems, and scalable platforms for insurance quoting. Requires 3-6 years experience with production AI systems and strong architectural skills.
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.
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.
Builds end-to-end product experiences to drive AI adoption among scientists, focusing on onboarding, experimentation, and growth loops. Requires 5+ years full-stack experience with React/Python, strong product intuition, and analytics skills.
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.
Leads ML initiatives to enhance validation processes using large-scale fleet and synthetic data for autonomous vehicle safety. Requires PhD or 5+ years ML experience, Python/PyTorch expertise, and AV domain knowledge.
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.
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.
Design and deploy deep learning models on biosensor and time-series data to deliver personalized health metrics. Requires strong ML/DL fundamentals, publications, and 4+ years of research experience.
Designs and builds scalable backend systems and applies machine learning to address safety, integrity, and Generative AI risks. Requires 8+ years backend experience, ML expertise, and distributed systems knowledge.
Designs, builds, and deploys custom AI agents for enterprise customers, providing hands-on technical support, troubleshooting, and acting as technical account manager. Requires 3+ years customer-facing experience and expertise in Python, AWS, SQL, and AI agent frameworks like LangChain and CrewAI.
Owns voice AI infrastructure for insurance operations, building scalable outbound/inbound agents, customer service, and underwriting systems with sub-second latency. Requires 3-6 years experience in production voice AI and real-time systems.
Designs and builds AI agents, workflows, and evaluation systems for enterprise audit platforms. Requires experience shipping production software with TypeScript, React, Python, Postgres, LLMs, RAG, and agent orchestration.
Builds performance benchmarking, diagnostic, and optimization tools for LLM inference on GPU clusters. Early-career role requiring Python proficiency, systems curiosity, and interest in AI hardware—no prior experience needed.
Design and deliver custom LLM solutions for enterprise customers, train frontier models using Cohere's stack, and influence foundation model capabilities. Requires strong ML fundamentals, Python fluency, and customer-facing technical leadership.
Design and deliver custom LLM solutions for enterprise customers, train frontier models using Cohere's stack, and contribute to foundation model improvements. Requires strong ML fundamentals, Python fluency, and experience with LLMs and large-scale data.
Designs, builds, and deploys production-grade AI agents using LLMs for enterprise workflows. Collaborates with customers to solve business problems, ensures reliability, and mentors teams on agentic architectures.
Builds and deploys end-to-end AI/ML systems, including LLM workflows and rapid prototypes for internal tools and product features in healthcare. Requires 4+ years experience, strong full-stack skills, evaluation/monitoring expertise, and Python proficiency.
Build and maintain scalable ML platform for model experimentation, training, evaluation, inference, and feature store to power underwriting products. Requires 5+ years experience with Python, ML stacks like Databricks/AWS, and MLOps systems.
Designs, builds, and scales agentic AI systems using LLMs for compliance automation, including multi-step reasoning, RAG, and production deployment. Requires 7+ years software engineering with 2+ years ML/AI, Python proficiency, and cross-functional collaboration.
Builds sophisticated AI agent products for investigating financial crimes, leads technical designs and teams. Requires 4-10 years experience in software development, Python, cloud infrastructure, and hybrid SF Bay Area work.
Builds and deploys production-scale AI/ML systems using LLMs, from fine-tuning and evaluation to low-latency infrastructure. Requires 5+ years experience with PyTorch/TensorFlow, MLOps, AWS, and taking models to production at high-growth startups.
Develop ML models for generating realistic autonomous vehicle simulation scenarios, integrating LLMs/VLMs and agentic AI for safety validation. Requires 5+ years ML experience, MS/PhD, and proficiency in PyTorch, transformers, diffusion models.
Leads design and development of scalable, real-time API and data infrastructure for AI model evaluations, processing large-scale event streams with low latency. Requires 5+ years in infrastructure or ML systems, expertise in distributed systems, stream processing, and backend architecture.
Builds and optimizes ML backend systems for recommendation, ranking, and search in a fast-growing AI consumer app. Requires 5+ years experience, CS bachelor's, ML frameworks like PyTorch/TensorFlow, cloud infra, and modern typed languages.
Develops LLM/NLU systems and data pipelines to process medical records, classify patients, and recommend care levels for a healthcare AI platform. Requires 5+ years backend/data engineering experience with production LLMs and integration into user-facing features.
Develops ML models using imitation and reinforcement learning for agent behavior prediction and autonomous vehicle planning. Requires PhD +1 year or MSc +5 years experience, expertise in RL, transformers, and production ML pipelines.
Builds personalization and recommendation systems from scratch for AI creative tools, modeling user taste and curating feeds. Designs algorithms for generative models to adapt to individual aesthetics, using ML frameworks like PyTorch/JAX.
Builds and deploys AI primitives and agents to automate workflows and enhance user experiences in investment management platform. Requires AI agent experience, distributed systems knowledge, and product-minded engineering across tech stacks.
Designs and implements novel model serving architectures on in-house inference engine to maximize throughput and minimize latency for generative media models. Develops performance tools and collaborates with ML teams on Nvidia-based systems optimizations.
Designs, trains, and deploys deep learning models for drone autonomy, focusing on computer vision tasks like optical flow, depth estimation, detection, and path planning using real-world and synthetic data. Requires MS/PhD, hands-on DL experience, and PyTorch/Python/C++ proficiency.
Builds and scales deep learning infrastructure for autonomous drone computer vision workloads, optimizing inference for high throughput/low latency across hardware, and implements MLOps pipelines for model deployment and monitoring. Requires hands-on MLOps, DL/CV expertise, and ML pipeline experience.
Develops real-time deep learning models for drone autonomy, focusing on detection, tracking, segmentation, and optical flow using visual data. Requires hands-on experience with deep neural networks, computer vision, Python/C++, and model optimization for embedded hardware.
Develops and optimizes deep learning inference infrastructure for real-time computer vision workloads on drones, focusing on high-throughput, low-latency performance across hardware platforms. Builds MLOps workflows, GPU kernels, and SDKs; requires strong DL, CV, and ML pipeline expertise.
Builds and improves AI agents for complex accounting tasks, working across product engineering, agent platforms, infrastructure, and data systems at the frontier of applied ML. Requires strong systems thinking, ownership, and excitement for coding agents in a fast-changing environment.
Develops quantitative models for portfolio optimization, fixed income relative value, risk estimation, and AI agents for credit research and portfolio management at a fintech platform. Requires Python coding, quant background, and bachelor's/PhD in math-related field.
Design, train, and integrate ML models for semantic map element detection in autonomous vehicles. Requires 5+ years experience, MS/PhD in CS, expertise in computer vision, deep learning, and PyTorch.
Builds and operates production AI systems for WHOOP's AI platform, including evaluation pipelines, fine-tuning workflows, and LLM observability. Requires 3+ years in applied ML/AI engineering with hands-on experience in modern language models.
Builds and optimizes AI/ML analytics engine using scientific Python stack for public opinion measurement platform. Requires 5+ years experience in quantitative software, ML, and distributed systems.
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.
AI Inference Engineer ports, optimizes, and benchmarks AI/LLM models on Quadric's GPNPU platform for edge devices. Requires 5+ years in model inference frameworks, quantization expertise, and proficiency in C++/Python.
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.
Leads development of generative AI tools for fashion design, including image generation, editing, and workflows. Mentors ML engineers, conducts applied research on diffusion models, and drives production systems integrating cloud GPUs and multimodal LLMs. Requires 7+ years ML experience and Master's/PhD.
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.
Senior engineer owning end-to-end AI infrastructure including LLM orchestration, agent architectures, evaluation systems, and scalable platforms for insurance quoting. Requires 3-6 years experience with production AI systems and strong architectural skills.
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.
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.
Builds end-to-end product experiences to drive AI adoption among scientists, focusing on onboarding, experimentation, and growth loops. Requires 5+ years full-stack experience with React/Python, strong product intuition, and analytics skills.
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.
Leads ML initiatives to enhance validation processes using large-scale fleet and synthetic data for autonomous vehicle safety. Requires PhD or 5+ years ML experience, Python/PyTorch expertise, and AV domain knowledge.
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.
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.