Senior Machine Learning Engineer, Agentic Systems

The government’s demand for AI is growing far faster than the systems required to support it. Fewer than 15% of federal AI programs have reached sustained production, despite billions of dollars invested. The models perform in testing, but they degrade in the real world. And when performance drops, trust goes with it.

What you’ll build

As a Senior Machine Learning Engineer, Agentic Systems, you will be a core contributor to both customer-driven projects and the enduring products of the company. Working directly with customers, data scientists, software engineers, and DevOps engineers, you’ll develop machine learning solutions, orchestrate complex data and agentic workflows, and help shape the capabilities of Chariot, our proprietary AI operations platform. You’ll work across models, agents, tools, and workflows to build reliable and effective AI systems while analyzing and improving their performance and usability.

Your work will inform platform improvements, expand our capabilities, and extend to the field through mission-critical deployments, direct customer contact, and insights that shape what we build next.

What we’re looking for

• A BS degree in computer science, machine learning, or a related discipline and 6+ years relevant experience
• Demonstrated experience delivering data-centric systems (e.g., data engineering, data cleaning, ETL pipelines, machine learning, and other production analytics)
• Experience designing, building, evaluating, and optimizing LLM-powered agents and agentic workflows
• Experience integrating AI systems with external tools, APIs, MCP servers, and enterprise data sources
• Experience developing evaluation approaches and frameworks to measure agent performance, reliability, and safety
• Familiarity with retrieval-augmented generation (RAG), tool use, planning, and multi-agent architectures
• Proficiency in programming languages and libraries common to machine learning; excellence in Python is essential, as is knowledge of libraries like TensorFlow, PyTorch, and/or scikit-learn
• Strong software engineering fundamentals, including algorithms, data structures, design patterns, proficiency in at least one systems programming language (e.g., Go, Rust, C++, Java, Scala, etc.)
• Proficiency with modern software engineering tools and processes (Agile, version control, issue tracking, CI/CD, debugging, etc.)
• US citizenship with eligibility and willingness to obtain and maintain a Secret US security clearance

The following isn’t required, but we’d love to see it:

• An advanced degree in data science, machine learning, computer science, or a related discipline
• Knowledge of relevant architectures and design patterns for client-server systems (e.g., asynchronous programming, REST, GraphQL, React, Vue, Angular)
• Experience implementing and deploying software into containerized or cloud environments (e.g., Docker, Kubernetes [K8s], infrastructure as code, major cloud architectures)
• Experience with a variety of unstructured data types (e.g., imagery, full-motion video, text, acoustic, sonar, RF, telemetry signals)
• Experience defining, scoping, planning, and delivering complex technical solutions
• Experience leading a small team
• Experience delivering technology solutions in secure government environments
• Active Secret (or above) US security clearance

This position offers a fully remote work environment, or you can work hybrid/on site at our office in northwest Austin, TX. You will be expected to travel up to 20% of the time.

Compensation

The anticipated base pay range for this position is $160,000–$200,000/year. Striveworks’ total compensation package includes a competitive base salary, equity grants, and cash bonuses.

Benefits include:

In compliance with federal law, all persons hired will be required to verify their identity and eligibility to work in the United States and to complete an employment eligibility verification form upon hire.