Machine Learning Engineer, Public Sector

The shape of it

In the posting’s own words

The goal of a Machine Learning Engineer at Scale is to leverage techniques in the fields of generative AI, computer vision, reinforcement learning, and agentic AI to improve Scale's products and customer experience in production environments. Our machine learning engineers take advantage of robust internal infrastructure and unique access to massive datasets to deliver improvements to our customers.

What it asks for · 5

• Comfortable with light travel (approximately 10%) for customer interaction and team needs
• 2+ years of experience building and deploying applied ML systems in production environments
• Extensive experience with GenAI, Agentic AI, natural language processing, deep learning and deep reinforcement learning, or computer vision in a production environment
• Strong programming skills in Python, experience in Tensorflow or PyTorch
• Experience with geospatial data or maps - GIS tooling, spatial reference systems, or imagery.

Also a plus

• Experience deploying software into environments you can't reach from your laptop - on-prem, edge, air-gapped, or otherwise restricted networks. Regulated industries count; the constraint is the point, not the sector.
• Any prior exposure to government or defense work: military or civilian service, a cleared internship, or time at a federal contractor.
• Hands-on fine-tuning of open-weight models - LoRA/PEFT, instruction tuning, or training embedding models, at work or on your own.
• Having written evaluations for a system whose output isn't deterministic: benchmarks, LLM judges, or a regression suite that caught something real.
• Experience with geospatial data or maps - GIS tooling, spatial reference systems, or imagery.
• A shipped project with real users behind it, where you owned it after launch rather than handing it off at merge.

Tools and skills named

Words the posting leans on

• models11×
• learning10×
• product7×
• experience6×
• production6×
• machine learning5×
• systems5×
• agentic4×
• computer vision4×
• customer4×
• building3×
• deploying3×
• government3×
• llm3×
• reinforcement learning3×
• training3×

Counted from the posting after the mission statement and the legal notices are set aside. The ones near the top are the ones a screener is looking for.

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