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Machine Learning Engineer (Active Secret Clearance)
- Tacoma, Washington, United States
- Tacoma, Washington, United States
Über
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 DevOps 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 critical to success.
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 fully remote work environment, or you can work hybrid/on site at customer locations at Joint Base Lewis–McChord in Tacoma, WA. If remote, you will be expected to travel up to 30% of the time. If local, you will be expected to travel up to 25% of the time.
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
Experience contributing to 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 TensorFlow, 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 candidates who possess the above qualifications, and we appreciate and consider the addition of:
An advanced degree (e.g., MS, MEng, PhD) in computer science, machine learning, data science, or a related discipline
Excellence in Python and deep knowledge of libraries like TensorFlow, PyTorch, and/or scikit‑learn
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], cloud architectures)
Experience with machine learning applied to imagery and/or video data
Experience building agentic systems, agentic workflows, or AI agents
Experience defining, scoping, planning, and delivering complex technical solutions
Experience delivering technology solutions in secure government environments
The anticipated base pay range for this position is $160,000–$190,000/year. Striveworks’ total compensation package includes a competitive base salary, equity grants, and cash bonuses.
The Benefits
Medical/dental/vision insurance
Voluntary life, long‑term disability, accident, and hospital indemnity insurance
HSA and FSA (including dependent care FSA) plans
401(k) plan
Unlimited PTO
Paid parental leave
Check us out on Built In!
Striveworks is an Equal Opportunity Employer and does not discriminate in employment on the basis of race, color, religion, belief, sex (including pregnancy and gender identity or expression), national origin, social or ethnic origin, political affiliation, sexual orientation, marital status, disability, genetic information, age, membership in an employee organization, retaliation, parental status, military service, or other non‑merit factors. Striveworks will not tolerate discrimination or harassment of any kind.
If you require assistance or a reasonable accommodation in the application process, please contact Operations at hr@striveworks.us.
In compliance with federal law, all persons hired will be required to verify 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.
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Sprachkenntnisse
- English
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