Builds and optimizes production inference pipelines for large tabular models using Triton Inference Server. Requires 5+ years in ML infrastructure, expert Python skills, and deep knowledge of inference frameworks and optimization techniques.

Leads end-to-end ML initiatives for Reddit's consumer features like recommendations, search, and AI discovery. Requires 7+ years experience with deep learning frameworks, production ML systems, and expertise in Transformers, LLMs, or recommender systems.

Leads technical integration of AI agent solutions for clients, designs custom multi-agent workflows using Python, troubleshoots implementations, and optimizes production deployments. Requires Python expertise, AI/ML familiarity, and customer-facing technical experience.

Leads algorithmic development for Instacart's ads optimization systems, including real-time bidding, budget pacing, and auction mechanics using constrained optimization and control theory. Requires MS/PhD, 8+ years experience deploying production systems at scale, and proficiency in Go/Java/C++/Python.

Build and maintain ML infrastructure pipelines to deploy research models to production at scale, including CI/CD, A/B testing, monitoring, and optimization for low-latency voice AI serving. Requires 4+ years MLOps experience with Python, Docker, Kubernetes.

Staff Data Scientist advances ML models for healthcare claims auditing, curating data, developing precise models, and optimizing business impact for health plans. Requires expertise in SQL, Python/R, and building ML models from scratch.

Develop and advance ML models to select healthcare claims for auditing, improving precision and recovering millions in overpayments for large health plans. Requires experience with SQL, Python/R, and building modern ML models from scratch.

Leads development and deployment of ML and GenAI systems to detect billing errors, audits, and fraud in healthcare payments. Requires 5+ years data science experience, team management, and a degree in CS or related field.

Builds ML infrastructure, models, and platforms to enable AI-powered features for developers handling massive datasets. Requires 5+ years backend experience, production ML deployment, and expertise in LLMs, RAG, distributed systems, and cloud platforms.

Builds production-ready agentic AI systems including runtimes, orchestration, reliability, observability, and integrations with LLMs/APIs. Requires strong backend experience, shipped agent/LLM systems, and production reliability expertise.

Embeds with marketing teams to identify high-leverage workflows, build custom AI tools/agents/automations, coach marketers on AI integration, and scale transformations for self-sufficiency. Requires 5+ years experience building transformative AI solutions and strong coaching skills.

Builds and scales Generative AI platform infrastructure using advanced ML techniques. Requires deep expertise in large-scale model training, deployment, and optimization on cloud platforms.

Senior Data Scientist develops ML models and features using device, network, and behavioral data for fraud prevention and identity verification. Requires 6+ years experience, Master's in quantitative field, Python/SQL proficiency, and production ML deployment expertise.

Designs threat models and experiments for agentic AI security risks, builds prototypes with fine-tuned models and analysis tools, and turns research into scalable product defenses. Requires MS/PhD in CS/ML, production coding skills, and security mindset.

Leads applied AI investments, owning technical direction for high-impact AI products from design to production deployment. Requires 8+ years AI/ML experience, Python expertise, foundation models, LLM patterns, and evaluation systems.

Leads architecture of AI agents that convert natural language to production full-stack apps, driving multi-provider LLM strategies, tool integration, evaluation standards, and cross-team AI initiatives. Requires deep LLM expertise, prompt engineering, and scalable systems design.

Designs and implements AI agents that transform natural language into production-ready full-stack applications using state-of-the-art LLMs. Integrates multiple LLM providers, orchestrates workflows, and continuously improves agent performance through data analysis and experimentation. Requires TypeScript proficiency and hands-on LLM experience.

Conducts foundational research in spatial AI for residential construction, developing novel models using reinforcement learning, computer vision, LLMs, and 3D geometry. Requires 5+ years software engineering with 2+ years LLM experience, Master's degree, and expertise in PyTorch and RAG systems.

Staff Data Scientist owns end-to-end development of ML and Generative AI solutions for the RiskOS fraud prevention platform, from data exploration and modeling to production deployment and monitoring. Requires 6+ years experience in data science with fraud/risk focus, Python/SQL proficiency, and GenAI expertise.

Senior AI Engineer builds, trains, deploys, and operates character AI agents at scale, managing LLM/SLM pipelines, social platform integrations, and feedback loops. Requires 5+ years in backend/ML engineering with production AI deployment experience.

Leads development of large-scale ML platforms, focusing on MLOps, graph ML infrastructure, performance optimization, and distributed training pipelines. Requires 8+ years in ML infrastructure with expertise in Python, PyTorch, Kubernetes, Ray, and cloud tools.

Leads development of large-scale ML platforms, focusing on MLOps, graph ML infrastructure, performance tuning, and distributed training optimization. Requires 5+ years in ML infrastructure with expertise in PyTorch, Kubernetes, Ray, and cloud tools.

Builds scalable ML training systems and infrastructure for speech AI models (STT/TTS), prototypes novel ideas with researchers, and creates internal tools for cross-functional teams. Requires strong ML research pipeline experience, especially in speech domains, plus orchestration tools expertise.

Build and maintain fraud detection models and financial risk products through full ML lifecycle, including production code. Requires 6+ years experience (or 8+ with Masters), PhD preferred, strong end-to-end DS/ML skills, and domain interest in fraud/identity.

Build and maintain fraud detection models and financial risk products through full data science lifecycle, including production code. Requires 6+ years experience (or 8+ with Masters), advanced ML/stats skills, and PhD preferred.

Build and maintain fraud detection ML models and financial risk products with end-to-end ownership. Requires 4+ years experience (or 6+ with Masters), advanced degree, strong ML/stats skills, production coding, and domain interest in fraud/identity.

Build and deploy scalable machine learning infrastructure, models, and AI platforms for voice, speech, and natural-language products. The role requires 5+ years in ML or AI, production experience with large-scale data and multi-tenant applications, and expertise in distributed cloud systems.

Leads ML team building scalable systems for personalization, ranking, search, and ads. Owns end-to-end architecture from training to serving at consumer scale, requiring 8+ years ML experience and strong systems design skills.

Designs, fine-tunes, and deploys image generation models for photorealistic AI bots, optimizing for consistency, latency, and quality. Requires 5+ years software engineering, 2+ years production ML, and expertise in diffusion models like Stable Diffusion and PyTorch.

Builds scalable machine learning systems for real-time fraud detection using unsupervised/supervised ML, big data tools like Spark and Kafka, and streaming technologies. Requires 1-5 years experience in Java, Python, Shell, and big data technologies.

Builds machine learning systems using unsupervised/supervised algorithms and deep learning to detect fraud in real-time. Designs distributed streaming systems with big data technologies like Spark, Kafka, and Flink. Requires 5+ years in Java, Python, Shell.

Leads engineering initiatives to build scalable ML platform infrastructure, including unified embeddings, feature pipelines, and continuous learning systems. Requires 7+ years in applied ML, Python/ML frameworks expertise, and Master's/PhD in quantitative field.

Build and operate scalable ML infrastructure for deploying models to IoT sleep devices. Own end-to-end pipelines, optimize performance, and collaborate cross-functionally. Requires 5+ years in ML ops, Python, AWS, and production ML deployment.

Develop scalable ML services for data enrichment, managing the full lifecycle from model training with PyTorch/TensorFlow to deploying optimized inference using ONNX/vLLM. Requires 5+ years experience in production ML systems, strong deployment skills, and software engineering proficiency.

Build and improve machine learning models for Pinterest's recommendation systems across Homefeed, Ads, Search, and more. Requires 2+ years experience in ML methods like personalization and recommender systems, plus hands-on work with large-scale data pipelines.

Develop advanced ML models using deep learning to personalize Pinterest experiences across Homefeed, Ads, Search, and more. Requires 4+ years in ML, experience with large-scale systems like Spark/Hadoop, and a degree in CS/ML.

Senior ML engineer leads development of GenAI models and pipelines for Airbnb's customer support, productionizing at scale. Requires PhD, 10+ years ML experience including 2+ in GenAI, and expertise in NLP, deep learning, and agile AI practices.

Builds production AI agents and LLM pipelines for marketing workflows, integrating with data warehouses. Requires strong backend architecture skills, product thinking, and creativity with LLMs; senior role emphasizing impact over years of experience.

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 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.

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.

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.

Build and evolve the distributed training framework and tooling powering frontier-scale language models. The role focuses on large-scale ML systems, HPC infrastructure, performance optimization, reliability, and developer tooling across multi-node GPU clusters.

Build and optimize synthetic data and inference pipelines for large language models, combining research and software engineering to improve data quality, throughput, and model performance. The role requires strong Python and data-pipeline experience, familiarity with LLM inference frameworks, and experience with large-scale datasets.

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.

Build and scale agentic AI systems for mission-critical public-interest applications while researching and shipping state-of-the-art models. The role requires strong software engineering, Python and ML framework expertise, LLM experience, distributed GPU training knowledge, and Canadian citizenship with security-clearance eligibility.

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.