Machine Learning Engineer (Active Secret Clearance)

3w3 weeks ago

Striveworks

Schofield Barracks, US · Full-time · $175,000 – $205,000

About this role

Striveworks helps organizations harness artificial intelligence to solve real-world national security and business challenges, serving as the command center between data, models, and outcomes. Founded by data scientists and engineers, we make deployment to ongoing optimization simple and effective. Organizations build reliable, adaptable systems ready to scale in unpredictable environments.

As a Machine Learning Engineer, be a core contributor to customer-driven projects and enduring products from day one. Represent Striveworks on solutions leveraging Chariot, our proprietary AIOps platform. Work alongside data scientists, software engineers, and DevOps to transform models into operational capabilities.

Day-to-day involves developing machine learning pipelines and custom analytics for image, video, text, geospatial, time series, and structured data. Orchestrate and automate complex data engineering pipelines. Envision, specify, design, and implement core product functionality while conducting mission-critical fieldwork.

Thrive in a high-trust environment valuing candor, passion, perseverance, ownership, and agency. Share excitement about contributions to things that matter. This hybrid/on-site role at customer sites includes up to 30% travel, including international.

Requirements

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)
Proficiency in Python and exposure to libraries like TensorFlow
Active Secret Clearance
Outcome driven with passion for applying software engineering and data science to real-world problems

Responsibilities

Develop machine learning pipelines and custom analytics applied to image, video, text, geospatial, time series, and structured data
Orchestrate and automate complex data engineering and analytic pipelines
Envision, specify, design, and implement core product functionality
Conduct mission-critical fieldwork in support of customers and stakeholders
Transform machine learning models into operational capabilities
Leverage Chariot proprietary AIOps platform on projects and solutions
Inform and contribute to future capabilities of the platform