MLOps Jobs

Baseten is seeking a Software Engineer to join the Agent Infra team, focusing on building and enhancing Agent Drive, a distributed filesystem critical for agent sandboxes. This role involves developing a storage solution that supports thousands of concurrent sandbox mounts with strict data isolation and consistency. The work leverages advanced storage techniques like tiered caching, replication, and content-addressed data, with a focus on Linux filesystem internals. The team operates with a high degree of ownership, shipping features rapidly and contributing to the core infrastructure that powers leading AI companies.

$160k - $330k

Glean is seeking a Software Engineer to help build a scalable software platform, including enterprise search solutions. This role involves working across distributed systems, data pipelines, APIs, and user interfaces to deliver secure, high-quality products. You will contribute to a platform that powers intelligent search, an AI assistant, and AI agents, with a focus on enterprise-grade AI solutions. The work is deeply embedded in how people get things done, shipping agentic capabilities on an open, extensible stack.

$187k - $234k

Scale AI

Scale's ML platform (RLXF) team builds our internal distributed framework for large language model training and inference. The platform powers MLEs, researchers, data scientists, and operators for fast and automatic training and evaluation of LLMs, as well as data quality evaluation. You will work closely across Scale’s ML teams and researchers to build the foundation platform that supports all our ML research and development, enabling the next generation of LLM training, inference, and data curation.

$190k - $237k

Scale AI

Scale's LLM post-training platform team builds an internal distributed framework for large language model training, powering MLEs, researchers, data scientists, and operators for fast and automatic training and evaluation of LLMs. This platform also serves as the underlying training framework for the data quality evaluation pipeline. You will work closely with Scale’s ML teams and researchers to build the foundation platform which supports all our ML research and development works, enabling next generation LLM training, inference, and data curation.

$290k - $363k

Scale AI

The Human Frontier Collective (HFC) is a unique and exclusive expert network that brings together researchers, academics, and domain leaders from over 70 fields to shape the future of AI. With over 90% of members holding doctorates, the collective focuses on how frontier AI systems are built, evaluated, and governed. Members participate in high-impact AI/ML projects, collaborate on research publications, and gain access to a vibrant community network. This role offers opportunities to work on projects such as building AI safety guardrails, optimizing PyTorch models, and evaluating ML code, with the potential to co-author technical reports and research papers.

Join NVIDIA's Modular Diagnostics team and lead AI-powered innovation. Our team develops key diagnostic applications and infrastructure to test every NVIDIA GPU, ensuring flawless performance before launch. As a Senior Software Engineer, AI Infrastructure Solutions, you will build intelligent automation to speed up critical engineering workflows and improve GPU validation speed and quality.

$152k - $242k

Ema builds AI Employees for HR, IT, and Finance, automating busy work across the employee experience. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team comprises engineers from premier tech companies and graduates of top universities. We are backed by leading investors and are at the forefront of Agentic AI, shipping real systems that run business processes at scale. We are seeking innovative and passionate Machine Learning Engineers who excel at solving complex problems with large datasets, transforming theoretical concepts into practical, scalable solutions, and pushing the boundaries of Natural Language Processing and Information Retrieval.

$160k - $220k

Glean is seeking a Machine Learning Engineer to enhance the quality of its AI Assistant and autonomous agents. This role bridges production machine learning, LLM-powered systems, and product engineering, focusing on developing, evaluating, and refining assistant experiences for reliability and usefulness within enterprise workflows. You will tackle applied challenges in agent quality, evaluation, personalization, retrieval, and orchestration, with an emphasis on shipping production systems and improving the assistant's capabilities over time through enhanced signals, feedback loops, and end-to-end execution.

$180k - $205k

The Agentic Runtime team builds the low-latency, reliable, and secure foundation that powers Glean’s AI agents and assistant experiences at scale. You’ll design and operate core runtime services for multi-turn orchestration, tool calling, model routing, memory, streaming, and safety. You’ll work across distributed systems, production observability, and ML infra integrations to deliver an experience that feels instant, accurate, and trustworthy — while optimizing cost and reliability.

$180k - $210k

Accenture

You will design, build, and deploy production-grade agentic AI solutions across the full enterprise technology stack. This role involves working directly with client engineering teams, leading technical design sessions, and building reusable patterns and accelerators that scale beyond individual engagements. The position offers broad exposure across industries and enterprise technology stacks, with opportunities for vendor fellowship access and a direct pathway to a Forward Deployed Engineer program.

OpenAI

OpenAI's Hardware organization is developing next-generation AI-native silicon and integrated systems to power frontier models. This role focuses on defining and building the CI/CD systems essential for qualifying these advanced models and the software stack that runs on OpenAI's custom AI accelerators. The work ensures that correctness, performance, and stability are measurable for every code change, from initial commits to production releases. This position involves model workloads, accelerator software, systems infrastructure, and enhancing developer productivity by establishing scalable CI/CD and GitOps practices, designing robust regression and benchmarking pipelines, and collaborating with various engineering teams to optimize feedback loops.

$318k - $485k

Ironclad is seeking a Technical Lead Manager to lead a team of engineers focused on building production generative AI systems. This role combines hands-on technical leadership with people management, involving setting the technical direction for the team and fostering engineer growth. The team will own the technical roadmap and quality bar for their systems, partnering with product management to translate business needs into technical deliverables. The Tech Lead Manager will also contribute directly through design documents, architectural decisions, and writing production code for critical problems. A key aspect of the role is staying deeply involved in the team's architecture and technical details to effectively review designs, unblock engineers, and make prioritization calls, while also setting and upholding high engineering standards for code quality, testing, and production monitoring.

$188k - $235k

Prime Intellect is developing an open superintelligence stack, providing infrastructure for AI labs. Their platform, Lab, integrates compute, environments, evaluations, secure sandboxes, and high-performance training for post-training at scale, including SFT, RL, tool use, agent workflows, and continuous model improvement. They are building open-source frontier AI models for long-horizon tasks and the platform their research team uses. The role focuses on building post-training and agent systems for national institutions, public-sector organizations, and regulated industries, addressing needs for models and agents that operate within strict boundaries for data, deployment, access, auditability, and human authority, while enabling self-improvement without external model dependency.

$150k - $300k

Prime Intellect is developing an open superintelligence stack, providing infrastructure that AI labs typically build internally to ambitious AI teams. Their platform, Lab, integrates compute, environments, evaluations, secure sandboxes, high-performance training, and deployment for post-training at scale, covering SFT, RL, tool use, agent workflows, and continuous model improvement. They are focused on building open-source frontier AI models trained for long-horizon tasks and the platform their research team uses. The company has secured significant funding from prominent investors and AI leaders, and is seeking individuals passionate about building at the intersection of frontier research, infrastructure, and go-to-market strategy for a nascent category.

$150k - $300k

Deepgram is a leading platform for Voice AI, providing real-time APIs for speech-to-text and text-to-speech, enabling developers to build production-grade voice agents at scale. We are seeking researchers who are passionate about solving customer challenges by improving our AI models. This role involves identifying model limitations, designing evaluations, curating data, fine-tuning models, and shipping solutions to production within weeks. The ideal candidate will have an AI-first mindset, be comfortable experimenting with new AI tools and models, and thrive in a fast-paced, evolving environment.

$216k - $338k

Salesforce AI Labs is seeking exceptional emerging AI and computer science talent for a highly selective, 24-month rotational fellowship designed to develop the next generation of AI builders. Fellows will tackle real technical and customer challenges, build with frontier AI technologies, and ship solutions into production at enterprise scale. This program offers hands-on experience across four distinct dimensions of the AI lifecycle: Product Engineering, Product Management, Customer Solution Deployment, and Enterprise Workflow Transformation. The rotational model provides exposure to different AI teams, technologies, and problems, building the technical depth, adaptability, and product mindset needed to become an AI leader. Upon successful completion, Fellows will transition into high-impact AI teams across Salesforce.

$114k - $136k

Confido is seeking a Senior ML Ops Engineer to be the first dedicated owner of its ML platform. This role will be responsible for the pipelines, serving, and cloud foundation that enable AI/ML models and agents to operate reliably and cost-efficiently in production. The engineer will ensure the platform can handle large-scale workloads, including document understanding, forecasting, and agentic systems, with a focus on making AI/ML development and deployment seamless for the AI/ML team.

$210k - $300k

NVIDIA is seeking a Staff Engineer to develop the company's Enterprise Data Governance platform. This platform is crucial for protecting sensitive information, managing data access across all collaboration and content systems, and building a knowledge infrastructure that ensures the trustworthiness and accuracy of enterprise AI. The role presents a unique challenge in balancing the need for broad data access for AI agents with strict security, legal, and export control requirements. This position is ideal for technically strong engineers at the senior to principal level who are passionate about solving complex infrastructure problems and contributing to NVIDIA's core operations at scale.

$168k - $322k

Salesforce is seeking a highly skilled and experienced Lead Member of Technical Staff (LMTS) to provide technical leadership and full-stack expertise for the Page Builder platform. This role involves leading the architectural design, engineering roadmap, and development of enterprise-scale web capabilities that power salesforce.com. The LMTS will set engineering standards, foster technical excellence, drive AI-first workflow innovations, and mentor engineers. The team focuses on building and owning a content authoring and rendering platform for marketing pages, with a strong emphasis on frontend development, modular component libraries, and robust rendering for global audiences. This role is an opportunity to shape the future of AI integration within engineering workflows and contribute to a high-traffic digital ecosystem.

$173k - $260k

Applied Intuition Defense is seeking a Perception Engineer to join their expert team, focusing on advancing perception model performance across various domains including maritime, land, and air-to-surface. This role involves developing custom detector and classifier architectures, leveraging proprietary MLOps tooling for rapid iteration on large datasets, and utilizing frontier AI and extensive token budgets. The position requires building and optimizing perception models for high accuracy and real-time performance on edge devices, as well as contributing to the entire perception stack from labeling tools to simulation. Collaboration with a world-class AI talent pool and scaling datasets through advanced generation techniques are key aspects of this hands-on, full-stack position.

$125k - $175k