Top AI & Machine Learning Jobs

Develop and deploy reliable machine learning, LLM-powered agent, and agentic workflow systems for government and enterprise customers. Integrate models with tools, APIs, MCP servers, and data sources; build evaluation frameworks for performance, reliability, and safety; improve Chariot, the company’s AI operations platform; and support mission-critical deployments. Collaborate with data scientists, software engineers, DevOps teams, and customers in secure government environments.

Develop and deploy reliable machine learning, LLM, agentic, and data-centric systems for government and enterprise customers. Build and evaluate AI agents, workflows, tool integrations, and retrieval-augmented systems; measure performance, reliability, and safety; and improve the Chariot AI operations platform. Collaborate with customers, data scientists, software engineers, and DevOps teams on mission-critical deployments. The role is fully remote or hybrid in Austin, with travel up to 20%.

Develop machine learning capabilities, custom analytics, and mission-critical AI solutions across image, video, text, geospatial, time-series, and structured data. Build and orchestrate data engineering pipelines for agentic and traditional architectures, collaborate with data scientists, software and DevOps engineers, contribute to the Chariot AI operations platform, and support customer-facing deployments.

As a Staff Machine Learning Engineer, lead teams in designing AI solutions, managing projects, and interfacing with clients while ensuring technical excellence and operational effectiveness.

The Staff Machine Learning Engineer will lead the development of AI solutions, ensure project delivery, and manage technical teams while interfacing with customers. Responsibilities include designing data pipelines, overseeing machine learning model development, and facilitating customer engagement.

Design and deploy production-grade machine learning models and data pipelines across image, video, text, geospatial, time-series, and structured data. Collaborate with customers, data scientists, software and DevOps engineers to define requirements, maintain mission-critical deployments, and contribute to the Chariot AI operations platform.

Design, validate, and deploy machine learning models and custom analytic algorithms across image, video, text, geospatial, time-series, and structured data. Work with engineers to implement AI solutions for cloud and edge, monitor model performance, manage drift, and sustain production systems in secure government environments.

Lead product vision and roadmap for AI infrastructure and agentic systems. Work with engineering, data science, and sales to define requirements, prioritize features, enable execution, validate deliverables, maintain technical documentation, support go-to-market launches, and track customer feedback and market trends to drive platform strategy and measurable outcomes.

As a Machine Learning Engineer, you will develop machine learning models, automate data engineering pipelines, and support customer-centric projects while collaborating with data scientists and engineers.

As a Data Scientist, you'll develop and validate machine learning models, implement AI solutions, and conduct fieldwork in support of customers.