Machine Learning Engineer

Build, Deploy, and Maintain AI for an Unpredictable World

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.

As a Staff Machine Learning Engineer at Striveworks, you will be challenged—and trusted—on day one to be both a core contributor and a customer‑facing technical leader on the projects and direction of the company. In this mission‑critical work, you will design AI‑powered solutions, you will bring them into being—from data shaping and ingestion, through analytics, to end‑user delivery—and you will inform future platform capabilities.

You’re right for this opportunity if you value and possess technical expertise and enjoy pushing the boundaries of your own capabilities. You are passionate about applying both software engineering and data science to solve real‑world problems. You are comfortable simultaneously leading a team, executing directly on critical elements of the plan, and presenting vision and outcomes to your customer.

Your day‑to‑day will include:

• Working with customers, engineers, and other stakeholders to define clear requirements that solve the customers’ problems and leverage the capabilities of our AI operations platform.
• Translating requirements into a technical approach, design, scoping estimate, and execution plan.
• Leading execution teams to achieve on‑time completion of project deliverables mapped to customer business value while making key individual contributions throughout the process.
• Designing, orchestrating, and automating complex data pipelines and algorithms within modern architectures (cloud, event‑driven, microservices, etc.).
• Guiding the development of machine learning models and custom analytics applied to image, video, text, geospatial, time series, and structured data.
• Raising insights, opportunities, challenges, and feedback in order to improve group‑level practice, capture reusable functionality, expand company opportunities, and accelerate time to value.
• Conducting mission‑critical fieldwork and interfacing with customers and other stakeholders at their work sites.

This position offers a fully remote work environment, or you can work hybrid/on‑site at our office in northwest Austin, TX, with up to 20% travel.

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:

• Advanced degree in data science, machine learning, computer science, or a related discipline and 10+ years of relevant experience
• Broad proficiency in programming languages common to machine learning (excellence in Python is essential, as is knowledge of libraries like Tensor Flow, PyTorch, and scikit‑learn) and systems programming (e.g., Go, Rust, C++, Java, Scala, etc.)
• Proficiency in the design and delivery of algorithms, data structures, and production analytics and in the use of design patterns in cloud environments
• Demonstrated experience defining,…