Senior Machine Learning Engineer, Agentic Systems

“In 36 months, agentic AI systems will be an operating reality across major institutions. We intend to be central to it.” — Dr. Jim Rebesco, Cofounder and CEO, Striveworks

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 i...

Striveworks was built to solve that problem.

Striveworks is an Equal Opportunity Employer and does not discriminate in employment on the basis of race, color, religion, belief, sex (including pregnancy and gender identity or expression), national origin, social or ethnic origin, political affiliation, sexual orientation, marital status, disability, genetic information, age, membership in an employee organization, retaliation, parental status, military service, or other non-merit factors. Striveworks will not tolerate discrimination or harassment of any kind.
If you require assistance or a reasonable accommodation in the application process, please contact People Operations at [email protected].
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.
Striveworks is a participating employer in the E-Verify program.

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.