Data Scientist (Active Secret Clearance)
Technologies
Chariot · TensorFlow · PyTorch · scikit-learn · Python · Git · Agile · Docker · Kubernetes
About Striveworks
Cloud-to-edge AIOps platform that helps defense and other high-stakes teams build, deploy, evaluate, and maintain AI models in contested, fast-changing environments.
Series B · 50–100 people
Job description
The full responsibilities and requirements are on the employer’s site.
Read the job description ↗Source and classification
Internal deployment & tooling · Evidence for this classification:
direction of the company. Working as part of a team of data scientists, machine learning engineers, software engineers, and DevOps engineers, you’ll develop and validate machine learning models and custom analytic algorithms applied to image, video, text, geospatial, time series, structured, and other data. You will design AI-based solutions, based on both agentic and traditional approaches, for cloud and edge environments. You will sense what customers need, identify evolving demands, and translate that feedback into actionable input for our product teams. The work extends to the field, with mission-critical deployments and direct customer contact. What it’s like here We lead with trust, treat each other with respect, and use candor consistently, kindly, and constructively. We care deeply about our work, and we find genuine satisfaction in doing it well. Above all, we take
More from the job description
“In 36 months, agentic AI systems will be an operating reality across major institutions. We intend to be central to it.” — Dr. Jim Rebesco, Cofounder and CEO, Striveworks The government’s demand for AI is growing far faster than the systems required to support it. Fewer than 15% of federal AI programs have reached sustained production, despite billions of dollars invested. The models perform in testing, but they degrade in the real world. And when performance drops, trust goes with it. Striveworks was built to solve that problem. What you’ll build Since 2018, we have delivered the most trusted AI systems operating in real-world use cases—providing a layer of assurance underneath hundreds of deployed models that monitors performance, manages drift, and sustains systems long after they leave the lab. As a Data Scientist, you will be a core contributor to the projects, products, and direction of the company. Working as part of a team of data scientists, machine learning engineers, software engineers, and DevOps engineers, you’ll develop and validate machine learning models and custom analytic algorithms applied to image, video, text, geospatial, time series, structured, and other data. You will design AI-based solutions, based on both agentic and traditional approaches, for cloud and edge environments. You will sense what customers need, identify evolving demands, and transl [... source excerpt omitted ...] ove to see it: An advanced degree in computer science, machine learning, mathematics, or a related discipline Experience deploying machine learning and data science solutions to production environments Exposure to DevOps and to cloud infrastructure Experience processing a variety of unstructured data types (e.g., image/video, text, telemetry, graphs, or other) Experience implementing ETL pipelines, data pipelines, and/or workflow automation Experience developing software in a systems programming language (e.g., Go, Rust, C++, Java, Scala, etc.) You will be hybrid or on site at our Austin, Texas, office. This role requires travel up to 30% of the time. Compensation The anti
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