Senior Machine Learning Engineer (Active Secret Clearance)
$185,000–$230,000 year
HybridAustin, Texas, United States
Job Summary
Define requirements and orchestrate complex data engineering pipelines while developing machine learning models and custom analytics for image, video, text, geospatial, time series, and structured data. Collaborate directly with customers, data scientists, software engineers, and DevOps teams to inform the future of Chariot, our proprietary AI operations platform, and support mission-critical deployments with direct customer contact. This Senior Machine Learning Engineer role requires an active Secret (or above) US security clearance and US citizenship. Based in Austin, Texas with hybrid work and up to 25% travel, the position offers a base salary of $185,000–$230,000/year.
Required Qualifications
- BS degree in computer science, machine learning, or a related discipline
- 6+ years relevant experience
- Demonstrated experience delivering data-centric systems
- Proficiency in programming languages and libraries common to machine learning
- excellence in Python
- knowledge of TensorFlow, PyTorch, and/or scikit-learn
- Proficiency in software engineering fundamentals to include algorithms, data structures, design patterns
- at least one systems programming language
- Proficiency with modern software engineering tools and processes
- Active Secret (or above) US security clearance
- US citizenship
- You will be hybrid out of our Austin, Texas, office
- This role requires travel up to 25% of the time
- 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
Desired Qualifications
- Advanced degree in data science, machine learning, computer science, or a related discipline
- Knowledge of relevant architectures and design patterns for client-server systems
- Experience implementing and deploying software into containerized or cloud environments
- Experience with a variety of unstructured data types
- Experience delivering technology solutions in secure government environments
- Experience building AI agents, agentic workflows, or agentic systems
- Experience defining, scoping, planning, and delivering complex, production-level technical solutions
- Experience leading, managing, or mentoring small, cross-functional engineering teams
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