Senior Machine Learning Engineer, Agentic Systems

Striveworks builds trusted AI systems for real-world and government use cases, helping organizations monitor model performance, manage drift, and sustain production deployments. The Senior Machine Learning Engineer, Agentic Systems will develop machine learning solutions, orchestrate data and agentic workflows, evaluate and improve AI systems, collaborate with customers and technical teams, and help shape the company’s Chariot AI operations platform.

Responsibilities:

• 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

Requirements:

• 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
• 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