Own model quality and performance for Cerebras inference by building AI agent-driven eval suites, automating benchmarking, and creating customer-specific tooling. Requires strong AI agent experience and tooling intuition.

Builds core agent harness for Codex AI agents, enabling safe tool use, code execution, and long-horizon tasks in production. Designs systems for sandboxing, evaluation, observability, and performance optimization across ML workflows and infrastructure.

Build and ship machine-learning systems for enterprise search and AI assistants, including ranking, personalization, language-model adaptation, and question answering. The role requires 6+ years of experience, strong coding and analytical skills, and production model development experience.

Leads the design, build, and operation of AI and data platform for autonomy systems, managing training, simulation, data pipelines, MLOps, and deployment across on-premise, cloud, and edge environments. Requires deep expertise in scalable ML infrastructure and compute strategy.

Research Engineer builds ML infrastructure and agentic systems to accelerate scientific discovery in biology, neuroscience, and more. Requires 2+ years experience with Python, PyTorch/JAX/TF, cloud resources, and deep learning for LLM/agent research at Ai2.

Leads architecture and hands-on development for Rippling’s AI platform, building scalable agent infrastructure and self-correcting distributed systems. The role requires 8+ years of software engineering experience, strong technical leadership, and expertise in large-scale platform engineering.

This internship focuses on designing, training, and deploying large-scale machine learning models, exploring learning strategies, and partnering with product teams. Candidates should be enrolled students with Python and ML framework proficiency, distributed training experience, and familiarity with Transformer-based models.

Designs, builds, and maintains LLM-based AI systems, data pipelines, and automation tools to transform business processes. Requires 6+ years software engineering with 2+ years AI/LLM production experience, strong Python, and data engineering skills.

Partners with researchers to productionize ML models for quantitative trading, builds data pipelines and infrastructure, and leads projects requiring strong Python, math, and ML systems expertise.

ML intern on the Machine Learning team developing and shipping production ML models and pipelines. Requires current enrollment in an M.Sc. or Ph.D. program and strong Python/PyTorch backend skills.

Builds and maintains ML training and inference infrastructure, scales distributed workloads across GPU clusters, and develops tooling for observability and fast iteration. Requires strong Python, systems engineering, Kubernetes, and distributed training experience.

Build and scale distributed pipelines that ingest, curate, filter, and prepare large-scale video and multimodal datasets for model training. The role requires Python, distributed processing, orchestration, containers, cloud infrastructure, and experience with VLM-based captioning or data-quality workflows.

Conducts foundational and post-training research for large-scale video generation models while building scalable multimodal data pipelines. The role requires hands-on experience with distributed ML systems, distillation, reward modeling, preference-based fine-tuning, and Python-based deep learning frameworks.

As a Senior AI Engineer, you will develop and scale AI agent and chat capabilities, build infrastructure for real-time AI interactions, and prototype new AI applications. This role involves significant impact on product development within a cross-functional team.

Builds, scales, and operates production-grade ML systems for real-time personalization on Attentive's platform. Requires 6+ years experience with Python, PyTorch/TensorFlow, and scalable ML pipelines in a fast-paced environment.

Build and own the software infrastructure supporting large-scale tabular model research, from experimentation through production. The role requires 5+ years of software engineering experience, expert Python and PyTorch skills, strong architecture expertise, and familiarity with modern ML tooling and cloud infrastructure.

Develops and deploys ML models for credit underwriting in regulated banking, owning full stack from data curation to production decisioning. Leads MLOps initiatives and improves policies using advanced techniques for underserved segments. Requires 8+ YOE in ML production and technical degree.

DeepLearning.AI is seeking an AI Engineer to join their Learning Experience Lab. This role involves developing new AI products and features for their education platform, leveraging expertise in software development and machine learning, and building full-stack applications using GenAI tools.

Leads team developing and deploying a unified camera-first perception model for self-driving systems across diverse vehicles, geographies, and conditions. Hands-on with ML architecture, training, evaluation, embedded optimization, and customer requirements. Requires 5+ years ML perception experience and 2+ years team leadership.

Develops forecasting interfaces, data pipelines, and scheduling systems to predict support contact volume and optimize agent schedules for thousands, incorporating ML models and constraints like labor laws. Requires Python/ML experience and performance focus.

Builds AI infrastructure, frameworks, and agentic systems powering company products. Partners with teams to deploy high-impact AI use cases; requires 2+ years AI/ML experience, LLMs proficiency, and full-stack skills.

Builds and optimizes ML research infrastructure, deploys models to production for market-making strategies, and mentors engineers. Requires 5+ years backend experience, Python proficiency, and ML frameworks like PyTorch/Jax.

Leads and scales machine learning organization at fintech company, defining ML roadmap, productionizing models at scale, and collaborating cross-functionally. Requires 12+ years engineering experience, 7+ years leadership, MS/PhD, deep ML expertise, Python/SQL proficiency.

Builds AI prototypes and solutions using Celonis Process Intelligence platform for strategic customers, focusing on generative AI, agentic systems, and proof-of-value projects to drive ROI and adoption. Requires 7+ years in technical pre-sales, Python/ML expertise, and business process knowledge.

Build and operate production machine learning systems that optimize Spotify messaging across channels and user journeys. The role emphasizes ranking, experimentation, reinforcement learning, long-term optimization, and collaboration across product and engineering teams.

Builds retrieval stack and search subagents for Databricks AI agents, handling query understanding, hybrid retrieval across structured/unstructured enterprise data, and evaluation. Requires 10+ years in production IR/RAG systems and agentic workflows.

Builds and scales ML/DL infrastructure including data pipelines, annotation workflows, training, deployment, and monitoring for autonomous drone systems. Requires hands-on experience in data engineering, cloud ML platforms, containerization, and MLOps.

Build and improve core agentic capabilities (memory, context, multi-step tool use) and evaluation frameworks (LLM-as-judge) for Spotify's Talk to Spotify conversational AI. Requires 5+ years production ML experience, rigorous evaluation skills, and comfort with rapid iteration on real user data.

Designs new information architectures for LLMs to interact with external data sources, implements finetuning/RL training, builds evaluation sets, and develops agentic search capabilities. Requires strong Python/ML skills and LLM experience.

Leads architecture of scalable ML platforms for generative AI across text, image, audio, and video. Drives company-level strategy, mentors engineers, and builds large-scale systems requiring 12+ years experience in ML infrastructure.

Designs, builds, and deploys production AI/ML systems for financial operations like invoice matching and payment reconciliation. Requires 5+ years software engineering with 2+ years applied AI/ML, expertise in LLMs, RAG, and Python/PyTorch.

Conducts research on visual perception, multimodal learning, and large-scale AI model training. Designs architectures, builds datasets and evaluations, and collaborates on frontier models. Requires ML expertise, Python proficiency, and experimental rigor.

Designs and implements methods for sourcing, curating, and analyzing large-scale pre-training datasets for AI models, blending research with production-grade data engineering. Requires Python proficiency, deep learning frameworks, and strong ML fundamentals.

Develops and tunes post-training recipes for AI models, iterates on evaluations, debugs configurations, scales methodologies, and publishes research to advance collaborative intelligence. Requires Python proficiency, deep learning frameworks, and strong ML fundamentals.

Builds and ships AI agents that automate complex audit workflows using LLMs, retrieval pipelines, and orchestration logic. Owns end-to-end development, evaluation, reliability, and mentoring while partnering with product and design teams. Requires 3+ years experience with production LLM features.

Designs, builds, and deploys production ML systems for content safety, moderation, and policy enforcement at Spotify scale. Leads technical initiatives, develops multimodal/LLM models, and collaborates with Trust & Safety, Legal teams on safety-critical systems.

Builds and deploys custom integrations, APIs, and scalable solutions for enterprise clients using Mercor's AI platform. Requires strong engineering skills in modern languages and cloud environments, with customer-facing experience.

Develops and maintains behavioral models for road users (vehicles, pedestrians, cyclists) in autonomous driving perception stack. Requires MS/PhD, 7+ years experience, deep learning expertise, Python fluency, and production ML pipelines.

Builds AI agent systems for legal workflows, optimizing performance via prompt engineering, model selection, tools, and evaluations. Partners with customers/PMs to ship low-latency agents using Python and LLM APIs; requires 8+ years experience.

Develops performance optimizations for ML models across graph, kernel, and system levels using PyTorch and Thunder compiler. Builds tools, collaborates with partners, and contributes to open-source while requiring strong PyTorch expertise and optimization experience.

Develops ML perception algorithms and 4D world representations for autonomous vehicle stacks. Tests on real vehicles and collaborates with research teams. Requires 3+ years experience, C++/Python proficiency, and ML deployment expertise.

Develops and operates large-scale search engine infrastructure, including retrieval algorithms, indexing, and ML ranking models integrated with Grok AI. Requires experience with search systems, vector databases, and production ML in Python, Go, or Rust.

Leads a team of senior data scientists developing and deploying LLM-based ML products, defining technical roadmaps, overseeing model training/inference pipelines, and translating outputs into actionable insights for civic applications. Requires 6+ years ML experience and 1+ years leading teams.

Leads development of user-facing AI features using LLMs and AI models, integrating them into production for scalable, personalized experiences. Requires 5+ years engineering experience with Python/JS, databases, and AI orchestration expertise.

Builds scalable AI platform services for deploying and managing LLMs, integrates with providers like OpenAI and Anthropic, and applies AI to enhance product features. Requires deep backend expertise, distributed systems, and MLOps experience.

Build and maintain a platform for creating and deploying multi-agent AI systems, integrating multiple LLMs and orchestration frameworks like LangGraph. Requires deep expertise in AI backend engineering, evaluation frameworks, privacy, and search integration.

Senior AI Engineer builds and deploys user-facing AI features using LLMs and AI models, integrating them into production for scalable, personalized experiences. Requires 5+ years engineering experience with Python/JS, databases, and AI expertise.

Builds scalable AI platform backend for deploying and managing LLMs, integrates with providers like OpenAI/Anthropic/Google, and applies AI to enhance product features. Requires deep backend expertise, MLOps, cloud-native tech, and production AI experience.

Builds backend platform for multi-agent AI systems, integrating multiple LLMs and orchestration frameworks like LangGraph. Requires deep expertise in AI/ML, agent workflows, evaluation, privacy, and search integration.

Principal engineer architecting and building Redpanda's Agentic Data Plane, enabling AI agents to safely interact with enterprise data via streaming, query, and governance layers. Requires 10+ years building large-scale distributed systems and experience with agentic AI infrastructure.