Machine Learning Engineer (Active Secret Clearance)

About Striveworks

Striveworks helps organizations harness the power of artificial intelligence to solve real‑world national security and business challenges by serving as the command center between data, models, and business outcomes. Founded by data scientists and engineers, Striveworks set out to make the journey from deployment to ongoing optimization simple and effective.

With Striveworks, organizations aren’t just deploying AI—they’re building systems that remain reliable, adaptable, and ready to scale in an unpredictable world. Mission‑critical operations require models that perform where they’re deployed, scale as workloads grow, and adapt rapidly as AI capabilities advance. Striveworks meets these demands, increasing reliability and performance while lowering costs—and enabling confident, data‑driven decision‑making in dynamic environments.

The Role

As a Machine Learning Engineer at Striveworks, you’ll be challenged—and trusted—on day one to be a core contributor to both the customer‑driven projects and the enduring products of the company. You will represent Striveworks as a technology builder on projects and solutions that leverage Chariot, our proprietary AI operations (AIOps) platform, and you will inform and contribute to future capabilities of that platform.

You will inform, envision, and help extend Striveworks’ core software products. You will work alongside data scientists, software engineers, and Dev Ops engineers to transform machine learning models into operational capabilities.

You’re right for this opportunity if you value and possess technical expertise and enjoy pushing the boundaries of your own capabilities. You’re outcome driven and are passionate about applying both software engineering and data science to solve real‑world problems. You know that building customer‑centric solutions, communicating clearly, and capturing repeatable value into productized capabilities are all important.

Your day‑to‑day will include:

• Developing machine learning pipelines and custom analytics that are applied to image, video, text, geospatial, time series, and structured data
• Orchestrating and automating complex data engineering and analytic pipelines
• Envisioning, specifying, and, at times, designing and implementing core product functionality
• Conducting mission‑critical fieldwork in support of customers and other stakeholders

This position offers a hybrid/on‑site work environment at customer sites at Schofield Barracks in Oahu, Hawaii. You will be expected to travel up to 30% of the time, including some international travel.

The Right Fit

In addition to the specific skills and expertise detailed below, we are looking for individuals who share our values. Sharing a set of values allows us to move at the speed of trust.

Collectively, we value a high‑trust work environment where people respect each other and use candor kindly and constructively. We value work that intersects passion and perseverance, we geek out about the potential of our contributions, and we find joy in working hard on things that matter. Finally, we value taking ownership, having agency, and feeling individual responsibility for collective results.

Here’s what we’re looking for:

• BS degree in computer science, machine learning, or a related discipline and 2+ years of relevant experience
• Demonstrated experience delivering data‑centric systems (e.g., data engineering, data cleaning, ETL pipelines, machine learning, and other production analytics)
• Proficiency in software engineering fundamentals to include algorithms, data structures, design patterns, and at least one systems programming language (e.g., Go, Rust, C++, Java, Scala, etc.)
• Proficiency in Python and exposure to libraries like Tensor Flow, PyTorch, and/or scikit‑learn
• Exposure to modern software engineering tools and processes (Agile, version control, issue tracking, CI/CD, debugging, etc.)
• Active Secret (or above) US security clearance
• Due to the nature of this role, candidates must have US citizenship

The Wish List

We’re very interested in…