Senior Machine Learning Engineer (Active TS/SCI Clearance)

About the role

“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 it.

Striveworks was built to solve that problem.

What you’ll build

Since 2018, we have delivered the most trusted AI systems operating in real-world use cases—providing a layer of assurance underneath hundreds of deployed models that monitors performance, manages drift, and sustains systems long after they leave the lab.

As a Senior Machine Learning Engineer, 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 define requirements and orchestrate complex data engineering pipelines. You’ll also develop machine learning models and custom analytics applied to image, video, text, geospatial, time series, and structured data. Your work will inform the future of Chariot, our proprietary AI operations platform. The work extends to the field, with mission-critical deployments, direct customer contact, and insights that shape what we build next.

What it’s like here

We lead with trust, treat each other with respect, and use candor consistently, kindly, and constructively. We care deeply about our work, and we find genuine satisfaction in doing it well. Above all, we take ownership—because we feel the weight of collective results personally. We are looking for people who share these values and are eager to put them into practice.

What we’re looking for

- A BS degree in computer science, machine learning, or a related discipline and 6+ years of relevant experience

- Experience integrating LLMs and/or building AI agents, agentic workflows, or agentic systems

- Proficiency in programming languages and libraries common to machine learning; excellence in Python is essential, as is knowledge of TensorFlow, PyTorch, and/or scikit-learn

- Proficiency in software engineering fundamentals to include algorithms, data structures, design patterns, and at least one systems programming language

- Proficiency with modern software engineering tools and processes

- Active TS/SCI security clearance and US citizenship

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

- Experience implementing and deploying software into containerized or cloud environments