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.
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.
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.
Staff AI/ML Engineer architects production-grade AI systems including recommendation engines, multi-LLM architectures, and ML pipelines for Rippling's growth infrastructure. Requires 7+ years software engineering with 3+ years in production ML, expertise in LLMs, data engineering, and MLOps leadership.
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.
Leads team to build and optimize high-performance ML inference systems for generative models. Drives hands-on optimizations across the performance stack, collaborates with research teams, and mentors engineers to exceed industry benchmarks.
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.
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.
Designs and builds scalable agentic systems for generating and QA'ing reinforcement learning environments that teach AI models to code. Collaborates with AI researchers using TypeScript, React, NodeJS stack in a tight-knit founding team.
Develops and optimizes transformer-based vision-language foundation models for physical security, owning full-cycle training, fine-tuning, compression, and deployment for real-time inference on images, videos, and text. Requires PhD/Master's in CS/EE, hands-on ML expertise with PyTorch/TensorFlow, Transformers, and ViTs.
Builds, evaluates, and deploys LLM-driven features like document analysis and chat experiences using models from OpenAI, Anthropic, and Gemini. Requires 5+ years in software engineering and AI/ML, Python proficiency, and product thinking for scalable systems.
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.
Builds and deploys production ML models for real-time voice AI agents, fine-tuning LLMs and audio models, running benchmarks and human evaluations, and maintaining ML infrastructure for high-scale performance.
Builds and scales AI agents for autonomous patient recruitment, screening, data collection, and 24/7 support in clinical trials. Focuses on ML models, multi-channel LLM deployment, and integrating legacy healthcare systems.
Develops and optimizes OpenAI's inference infrastructure for AMD GPUs, handling low-level kernel performance, distributed execution, and integration with serving frameworks like vLLM and Triton. Requires expertise in GPU programming with HIP/CUDA and distributed systems scaling.
Leads development of proprietary AI reasoning model TRAM for interpreting global trade law, building data pipelines, fine-tuning LLMs, and evaluation frameworks for high-speed, accurate compliance determinations. Requires AI product experience, especially RAG systems and model fine-tuning.
Designs and implements novel causal inference algorithms and production systems for marketing attribution challenges at enterprise scale. Requires 5+ years shipping research code, strong math/stats background, Python proficiency, and customer collaboration.
Develops ML models and workflows for generating simulation scenarios in autonomous vehicle testing, integrating LLMs/VLMs, collecting data for fine-tuning, and collaborating with teams to enhance safety validation. Requires MS/PhD, 2+ years ML experience, and Python/PyTorch proficiency.
Designs, builds, and productionizes scalable ML systems using physiological data to deliver personalized health metrics. Requires 4+ years ML engineering experience, strong Python, cloud deployment, and backend skills.
Designs, builds, and iterates on AI/ML models for personalization, query understanding, and content discovery. Requires 5+ years in ML, deep learning expertise (PyTorch/TensorFlow/JAX), Python, and full ML lifecycle ownership.
Designs, builds, and deploys generative AI systems including LLM-based code reviews, agentic workflows, and RAG pipelines for developer productivity tools. Requires 3+ years in ML/LLM production systems, Python/TypeScript proficiency, and AI frameworks like LangChain.
Develops and deploys AI/ML models including fine-tuning LLMs and multi-modal systems from concept to production. Requires strong AI/ML skills from top CS/EECS/Math/Physics programs and proven production experience.
Partners with government agencies to develop and deploy GenAI applications using OpenAI API, from strategy to production. Requires 7+ years public sector technical consulting, TS/SCI clearance, and ML implementation experience.
Builds and deploys production-grade AI agents and workflows for business functions like marketing, recruiting, and product. Requires 3+ years experience shipping AI/ML apps, including LLM systems, with strong Python/TypeScript skills.
Develops full-stack AI features for legal contracting platform using TypeScript, React, Node.js, and LLMs. Builds scalable SaaS products like summarization and redlining, collaborating with product and design teams to deliver high-impact capabilities.
Designs and builds ML systems for real-time fraud detection, including data pipelines, model deployment, and backend services in Go/Python. Requires 5+ years software engineering with applied ML experience on large datasets.
Builds complex AI agent pipelines using LLMs, develops ML models with fine-tuning pipelines, and deploys AI infrastructure on cloud platforms. Requires 5+ years experience, expertise in AI/ML systems, and bachelor's degree or higher.
As a Perception Autonomy Engineer, you will develop, integrate, and maintain real-time sensor software solutions for autonomous vehicles. This involves designing and deploying AI/ML sensor algorithms, creating interfacing software for sensor control, and collaborating with cross-functional teams for seamless deployment and testing.
Builds and deploys language model-powered systems for cyber national security applications, including fine-tuning LLMs, RAG systems, and production inference. Requires 4+ years ML experience, Python/PyTorch proficiency, and LLM post-training expertise.
Architects and leads development of scalable ML training infrastructure, including scheduling, storage, networking, and reinforcement learning systems. Requires proficiency in Go, Kubernetes expertise, distributed systems knowledge, and experience with cloud providers and ML workloads.
Designs and implements AI solutions including ML models and LLMs to automate financial workflows and provide real-time insights in an accounting platform. Requires strong ML/DL/NLP expertise, Python, PyTorch/TensorFlow, and production deployment experience in a fast-paced startup.
Senior ML Engineer on Spotify's Supply Personalization squad, designing and implementing ML systems to optimize ad loads, user behavior analysis, and ad experiences using causal inference and large-scale experimentation. Requires strong applied ML, software engineering, data analysis expertise, and proficiency in Python/Java/Scala, TensorFlow/PyTorch, and data pipelines.
Builds and optimizes scalable ML inference infrastructure using Kubernetes and GPU resources to deploy production AI models with low latency. Collaborates with ML research and product teams on model serving, orchestration, and compute efficiency.
Develops AI applications and demos using Quadric's SDK, integrates products into AI/LLM frameworks, optimizes models for edge devices, and provides technical leadership and support to customers and developer community. Requires 5+ years with AI frameworks like PyTorch or TensorFlow, plus Python/C++ proficiency.
Builds and optimizes multimodal LLM-based AI agents for enterprise conversations, integrating with systems via APIs and automating high-stakes workflows. Requires 3+ years in AI engineering, Python/PyTorch proficiency, and experience with LLMs or vision models.
Builds, deploys, and optimizes enterprise-grade AI agents for high-stakes conversations, integrating with enterprise systems and fine-tuning LLMs. Requires 3+ years in AI engineering or NLP with Python, PyTorch/TensorFlow proficiency.
12-week fellowship for PhD/MSc STEM graduates to gain hands-on experience in AI engineering, product development, and research. Fellows develop/deploy AI agents using LLMs/RAG, optimize models, and work on enterprise projects with mentorship from AI leaders.
Builds foundational ML platform infrastructure including model serving pipelines, GPU scheduling systems, and CI/CD for large-scale multimodal AI models. Requires 5+ years in distributed systems with expertise in Python, Kubernetes, and AWS.
Develops and optimizes diffusion models and generative AI for fashion design software. Conducts research, implements techniques for design quality and controllability, and deploys to production. Requires Master's/PhD, 3+ years experience, PyTorch proficiency.
Build, scale, and maintain complex AI/NLP models for the Verneek AI platform, focusing on production deployment of large-scale systems. Requires 3+ years Python/PyTorch experience and BSc in CS; NLP expertise preferred.
Develops methods for AI agents to self-improve post-training through prompt optimization, continual learning from long-horizon tasks, hypothesis testing, and scalable experiments. Requires expertise in LLMs, agent frameworks, and impactful research track record.
Forward Deployed Engineer designs and deploys AI integrations and agentic workflows into customer enterprise systems, owning end-to-end production rollout. Requires 5+ years software engineering, Python proficiency, and LLM production experience.
Builds and improves AI agents and workflows for automating enterprise operations like IT, HR, and finance. Requires 4+ years software engineering with applied AI focus, full-stack skills in TypeScript/Node.js/React, and strong product sense.
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.
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.
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.
Staff AI/ML Engineer architects production-grade AI systems including recommendation engines, multi-LLM architectures, and ML pipelines for Rippling's growth infrastructure. Requires 7+ years software engineering with 3+ years in production ML, expertise in LLMs, data engineering, and MLOps leadership.
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.
Leads team to build and optimize high-performance ML inference systems for generative models. Drives hands-on optimizations across the performance stack, collaborates with research teams, and mentors engineers to exceed industry benchmarks.
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.
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.
Designs and builds scalable agentic systems for generating and QA'ing reinforcement learning environments that teach AI models to code. Collaborates with AI researchers using TypeScript, React, NodeJS stack in a tight-knit founding team.
Develops and optimizes transformer-based vision-language foundation models for physical security, owning full-cycle training, fine-tuning, compression, and deployment for real-time inference on images, videos, and text. Requires PhD/Master's in CS/EE, hands-on ML expertise with PyTorch/TensorFlow, Transformers, and ViTs.
Builds, evaluates, and deploys LLM-driven features like document analysis and chat experiences using models from OpenAI, Anthropic, and Gemini. Requires 5+ years in software engineering and AI/ML, Python proficiency, and product thinking for scalable systems.
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.
Builds and deploys production ML models for real-time voice AI agents, fine-tuning LLMs and audio models, running benchmarks and human evaluations, and maintaining ML infrastructure for high-scale performance.
Builds and scales AI agents for autonomous patient recruitment, screening, data collection, and 24/7 support in clinical trials. Focuses on ML models, multi-channel LLM deployment, and integrating legacy healthcare systems.
Develops and optimizes OpenAI's inference infrastructure for AMD GPUs, handling low-level kernel performance, distributed execution, and integration with serving frameworks like vLLM and Triton. Requires expertise in GPU programming with HIP/CUDA and distributed systems scaling.
Leads development of proprietary AI reasoning model TRAM for interpreting global trade law, building data pipelines, fine-tuning LLMs, and evaluation frameworks for high-speed, accurate compliance determinations. Requires AI product experience, especially RAG systems and model fine-tuning.
Designs and implements novel causal inference algorithms and production systems for marketing attribution challenges at enterprise scale. Requires 5+ years shipping research code, strong math/stats background, Python proficiency, and customer collaboration.
Develops ML models and workflows for generating simulation scenarios in autonomous vehicle testing, integrating LLMs/VLMs, collecting data for fine-tuning, and collaborating with teams to enhance safety validation. Requires MS/PhD, 2+ years ML experience, and Python/PyTorch proficiency.
Designs, builds, and productionizes scalable ML systems using physiological data to deliver personalized health metrics. Requires 4+ years ML engineering experience, strong Python, cloud deployment, and backend skills.
Designs, builds, and iterates on AI/ML models for personalization, query understanding, and content discovery. Requires 5+ years in ML, deep learning expertise (PyTorch/TensorFlow/JAX), Python, and full ML lifecycle ownership.
Designs, builds, and deploys generative AI systems including LLM-based code reviews, agentic workflows, and RAG pipelines for developer productivity tools. Requires 3+ years in ML/LLM production systems, Python/TypeScript proficiency, and AI frameworks like LangChain.
Develops and deploys AI/ML models including fine-tuning LLMs and multi-modal systems from concept to production. Requires strong AI/ML skills from top CS/EECS/Math/Physics programs and proven production experience.
Partners with government agencies to develop and deploy GenAI applications using OpenAI API, from strategy to production. Requires 7+ years public sector technical consulting, TS/SCI clearance, and ML implementation experience.
Builds and deploys production-grade AI agents and workflows for business functions like marketing, recruiting, and product. Requires 3+ years experience shipping AI/ML apps, including LLM systems, with strong Python/TypeScript skills.
Develops full-stack AI features for legal contracting platform using TypeScript, React, Node.js, and LLMs. Builds scalable SaaS products like summarization and redlining, collaborating with product and design teams to deliver high-impact capabilities.
Designs and builds ML systems for real-time fraud detection, including data pipelines, model deployment, and backend services in Go/Python. Requires 5+ years software engineering with applied ML experience on large datasets.
Builds complex AI agent pipelines using LLMs, develops ML models with fine-tuning pipelines, and deploys AI infrastructure on cloud platforms. Requires 5+ years experience, expertise in AI/ML systems, and bachelor's degree or higher.
As a Perception Autonomy Engineer, you will develop, integrate, and maintain real-time sensor software solutions for autonomous vehicles. This involves designing and deploying AI/ML sensor algorithms, creating interfacing software for sensor control, and collaborating with cross-functional teams for seamless deployment and testing.
Builds and deploys language model-powered systems for cyber national security applications, including fine-tuning LLMs, RAG systems, and production inference. Requires 4+ years ML experience, Python/PyTorch proficiency, and LLM post-training expertise.
Architects and leads development of scalable ML training infrastructure, including scheduling, storage, networking, and reinforcement learning systems. Requires proficiency in Go, Kubernetes expertise, distributed systems knowledge, and experience with cloud providers and ML workloads.
Designs and implements AI solutions including ML models and LLMs to automate financial workflows and provide real-time insights in an accounting platform. Requires strong ML/DL/NLP expertise, Python, PyTorch/TensorFlow, and production deployment experience in a fast-paced startup.
Senior ML Engineer on Spotify's Supply Personalization squad, designing and implementing ML systems to optimize ad loads, user behavior analysis, and ad experiences using causal inference and large-scale experimentation. Requires strong applied ML, software engineering, data analysis expertise, and proficiency in Python/Java/Scala, TensorFlow/PyTorch, and data pipelines.
Builds and optimizes scalable ML inference infrastructure using Kubernetes and GPU resources to deploy production AI models with low latency. Collaborates with ML research and product teams on model serving, orchestration, and compute efficiency.
Develops AI applications and demos using Quadric's SDK, integrates products into AI/LLM frameworks, optimizes models for edge devices, and provides technical leadership and support to customers and developer community. Requires 5+ years with AI frameworks like PyTorch or TensorFlow, plus Python/C++ proficiency.
Builds and optimizes multimodal LLM-based AI agents for enterprise conversations, integrating with systems via APIs and automating high-stakes workflows. Requires 3+ years in AI engineering, Python/PyTorch proficiency, and experience with LLMs or vision models.
Builds, deploys, and optimizes enterprise-grade AI agents for high-stakes conversations, integrating with enterprise systems and fine-tuning LLMs. Requires 3+ years in AI engineering or NLP with Python, PyTorch/TensorFlow proficiency.
12-week fellowship for PhD/MSc STEM graduates to gain hands-on experience in AI engineering, product development, and research. Fellows develop/deploy AI agents using LLMs/RAG, optimize models, and work on enterprise projects with mentorship from AI leaders.
Builds foundational ML platform infrastructure including model serving pipelines, GPU scheduling systems, and CI/CD for large-scale multimodal AI models. Requires 5+ years in distributed systems with expertise in Python, Kubernetes, and AWS.
Develops and optimizes diffusion models and generative AI for fashion design software. Conducts research, implements techniques for design quality and controllability, and deploys to production. Requires Master's/PhD, 3+ years experience, PyTorch proficiency.
Build, scale, and maintain complex AI/NLP models for the Verneek AI platform, focusing on production deployment of large-scale systems. Requires 3+ years Python/PyTorch experience and BSc in CS; NLP expertise preferred.
Develops methods for AI agents to self-improve post-training through prompt optimization, continual learning from long-horizon tasks, hypothesis testing, and scalable experiments. Requires expertise in LLMs, agent frameworks, and impactful research track record.
Forward Deployed Engineer designs and deploys AI integrations and agentic workflows into customer enterprise systems, owning end-to-end production rollout. Requires 5+ years software engineering, Python proficiency, and LLM production experience.
Builds and improves AI agents and workflows for automating enterprise operations like IT, HR, and finance. Requires 4+ years software engineering with applied AI focus, full-stack skills in TypeScript/Node.js/React, and strong product sense.