Builds and scales data pipelines, models, and integrations to provide real-time insights for product, engineering, finance, and GTM teams. Requires 4+ years experience with SQL, Python/JavaScript, dbt/Airflow, and data architecture.
Lead enterprise data architecture strategy, designing scalable data warehouse and BI solutions across cloud platforms while establishing governance, quality, and AI/ML integration practices.
Analyzes user behavior, models campaign outcomes, runs experiments, and builds data/ML pipelines to optimize creator ad matching, pricing, and attribution in a high-growth adtech platform. Applies analytical methods to big data for product and business decisions.
Build and scale data ingestion pipelines and connectors for enterprise SaaS apps, transform unstructured data for AI search and agents, ensure reliability and security at petabyte scale. Requires 3+ years backend/data infrastructure experience with distributed systems.
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 maintains scalable data pipelines for processing massive lead datasets and real-time intent signals. Owns data ingestion, modeling, ML dataset preparation, quality monitoring, and optimization in a fast-paced AI startup.
Lead development of personalization and recommendation systems as an early data hire. Build ML pipelines, classification models, and data infrastructure from the ground up using SQL and Python.
Research and develop improvements to pre-trained models for deployment in ChatGPT and API using reinforcement learning and product-driven approaches. Requires strong ML engineering, research experience with novel models, and ability to debug large codebases.
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.
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.
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.
Leads design and implementation of scalable streaming data pipelines using Kafka, Flink, and Spark Streaming. Mentors engineers, ensures data quality and observability, with 10+ years experience including 4+ in real-time 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.
Data Scientist owns high-impact projects across Product, Finance, Marketing, and Platform teams, building models, designing experiments, and driving decisions through data insights. Requires 4+ years experience, SQL/Python fluency, and cross-functional collaboration.
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.
Build and scale data pipelines partnering with Data Science, Infrastructure, and business teams to deliver reliable data for metrics and self-serve reporting. Requires 4+ years experience, SQL/Python fluency, and familiarity with Snowflake, dbt, Dagster.
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.
Leads end-to-end insights process for Life Sciences programs, partnering with cross-functional teams to deliver data-driven analyses, executive narratives, and value demonstrations using healthcare data. Requires 2-5 years experience in analytics/consulting, strong communication, and bachelor's in quantitative field.
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.
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.
Lead architecture of exabyte-scale distributed data systems that self-optimize via compression, metadata, and intelligent layouts to power efficient AI infrastructure. Requires deep expertise in distributed systems, low-level data representation, and leadership of large-scale production systems.
Build foundational data systems for AI at scale, including global metadata, adaptive engines, and intelligent data layouts using distributed systems, columnar formats, and languages like Java/Rust/Go/C++.
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.
Develop techniques to predict and mitigate unsafe behaviors in early-stage base models, design safer pretraining architectures, and integrate safety signals throughout training. Collaborate across safety teams to build robust, scalable safety foundations grounded in real-world risks.
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.
Builds and scales data pipelines, models, and integrations to provide real-time insights for product, engineering, finance, and GTM teams. Requires 4+ years experience with SQL, Python/JavaScript, dbt/Airflow, and data architecture.
Lead enterprise data architecture strategy, designing scalable data warehouse and BI solutions across cloud platforms while establishing governance, quality, and AI/ML integration practices.
Analyzes user behavior, models campaign outcomes, runs experiments, and builds data/ML pipelines to optimize creator ad matching, pricing, and attribution in a high-growth adtech platform. Applies analytical methods to big data for product and business decisions.
Build and scale data ingestion pipelines and connectors for enterprise SaaS apps, transform unstructured data for AI search and agents, ensure reliability and security at petabyte scale. Requires 3+ years backend/data infrastructure experience with distributed systems.
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 maintains scalable data pipelines for processing massive lead datasets and real-time intent signals. Owns data ingestion, modeling, ML dataset preparation, quality monitoring, and optimization in a fast-paced AI startup.
Lead development of personalization and recommendation systems as an early data hire. Build ML pipelines, classification models, and data infrastructure from the ground up using SQL and Python.
Research and develop improvements to pre-trained models for deployment in ChatGPT and API using reinforcement learning and product-driven approaches. Requires strong ML engineering, research experience with novel models, and ability to debug large codebases.
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.
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.
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.
Leads design and implementation of scalable streaming data pipelines using Kafka, Flink, and Spark Streaming. Mentors engineers, ensures data quality and observability, with 10+ years experience including 4+ in real-time 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.
Data Scientist owns high-impact projects across Product, Finance, Marketing, and Platform teams, building models, designing experiments, and driving decisions through data insights. Requires 4+ years experience, SQL/Python fluency, and cross-functional collaboration.
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.
Build and scale data pipelines partnering with Data Science, Infrastructure, and business teams to deliver reliable data for metrics and self-serve reporting. Requires 4+ years experience, SQL/Python fluency, and familiarity with Snowflake, dbt, Dagster.
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.
Leads end-to-end insights process for Life Sciences programs, partnering with cross-functional teams to deliver data-driven analyses, executive narratives, and value demonstrations using healthcare data. Requires 2-5 years experience in analytics/consulting, strong communication, and bachelor's in quantitative field.
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.
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.
Lead architecture of exabyte-scale distributed data systems that self-optimize via compression, metadata, and intelligent layouts to power efficient AI infrastructure. Requires deep expertise in distributed systems, low-level data representation, and leadership of large-scale production systems.
Build foundational data systems for AI at scale, including global metadata, adaptive engines, and intelligent data layouts using distributed systems, columnar formats, and languages like Java/Rust/Go/C++.
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.
Develop techniques to predict and mitigate unsafe behaviors in early-stage base models, design safer pretraining architectures, and integrate safety signals throughout training. Collaborate across safety teams to build robust, scalable safety foundations grounded in real-world risks.
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.