Staff Machine Learning Engineer

Build, Deploy, and Maintain AI for an Unpredictable World

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. Striv...

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—fro...

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.
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. You will be expected to travel up to 20% of the time. 
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.

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 TensorFlow, 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, scoping, planning, and delivering complex technical solutions in production environments
Proficiency with modern software engineering tools and processes (Agile, version control, issue tracking, CI/CD, debugging, etc.)
Demonstrated ability to lead, manage, and mentor small cross-functional teams that work across office, remote, and customer sites
Ability to communicate complex topics with professionalism, competence, and clarity to internal and external stakeholders (both technical and non-technical) via documents, presentations, and conversations
Eligibility and willingness to obtain and maintain a Secret (or above) US security clearance
Due to the nature of this role, candidates must have US citizenship

We’re very interested in candidates who possess the above qualifications, and we appreciate and consider the addition of:
Experience with Kubernetes (k8s) and horizontally scaled architectures
Knowledge of messaging systems such as NATS, Kafka, RabbitMQ, or similar
Experience building AI agents and workflows
Experience with complex and varied data types, such as multi-spectral imagery, full motion video, acoustic or sonar signals, synthetic aperture radar, or hardware telemetry
Experience delivering technology solutions in secure government environments
Active Secret (or above) US security clearance

The anticipated