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Applied Research - Software Engineering

đź•’ 26 days ago
PythonGolangTypeScriptVue

📜 Description

  • Turn state-of-the-art research implementations into product features that deliver useful machine learning capabilities to operators at the edge.
  • Build in-product integrations into the Frontline Perception System and other TurbineOne artifacts, working across Python model services, Golang application services, and the Vue 3 client as needed.
  • Collaborate with Research, Product, Design, Mission, Field Engineering, and external technical partners to understand operational problems and match them to possible solutions.
  • Develop reliable software around imperfect and rapidly evolving models, including tests, observability, failure handling, and clear technical documentation.
  • Design for disconnected, resource-constrained environments by considering latency, compute, memory, bandwidth, hardware architecture, and model packaging.

🛠️ Requirements

  • 8+ years working in software engineering, product engineering, or production machine learning positions.
  • Demonstrable experience taking machine learning, robotics, computer vision, or other research-grade software from prototype to production.
  • Strong Python experience and the ability to work effectively in unfamiliar parts of a full-stack system. Experience with Golang, TypeScript, or a reactive framework such as Vue or React is valuable.
  • Experience with machine learning runtimes and frameworks such as PyTorch, ONNX Runtime, or TensorRT, including containerized deployment on GPU-enabled systems.
  • Experience designing and evolving APIs using technologies such as gRPC, Protocol Buffers, GraphQL, or REST.
  • A track record of working through ambiguous technical and product domains, breaking broad problems into incremental deliverables, and defining what to implement before diving into implementation.
  • Excellent engineering judgment, with an emphasis on simple designs, readable code, thoughtful testing, and understanding behavior beyond the happy path.
  • Curiosity and self-direction: you can go deep to understand an unfamiliar system or research implementation, then return with a practical recommendation and working software.
  • Scope and own initial product integrations from end to end: evaluate a research implementation, define an incremental path to delivery, adapt and productionize the core capability, build the required APIs and data
Full job description

Senior/Principal, Applied Research Software Engineer

Remote

ABOUT THE JOB

Company Intro: TurbineOne is the frontline perception company. We deliver decision advantage, better situational awareness, and stronger force protection. Our customers love how we automate the right portions of the military intelligence cycle while keeping them in the loop. The company is a small, fast-moving, and high-performance startup that is backed by the best DefenseTech venture capitalists.

Job Title: Senior/Principal, Applied Research Software Engineer

Reporting directly to: The Director of Applied Research

Location: Geographically flexible for home-office

The Applied Research team identifies promising research and turns it into effective, edge-focused capabilities that people can use without a background in machine learning. This is not a pure research organization: success means shipping timely, reliable product features around rapidly evolving models and algorithms.

Primary Responsibilities

  • Turn state-of-the-art research implementations into product features that deliver useful machine learning capabilities to operators at the edge.
  • Scope and own initial product integrations from end to end: evaluate a research implementation, define an incremental path to delivery, adapt and productionize the core capability, build the required APIs and data flows, and update the product UI so users can access it.
  • Build in-product integrations into the Frontline Perception System and other TurbineOne artifacts, working across Python model services, Golang application services, and the Vue 3 client as the feature requires.
  • Collaborate with Research, Product, Design, Mission, Field Engineering, and external technical partners to understand the operational problem and match it to a set of possible solutions based on state-of-the-art algorithms and machine learning processes.
  • Develop reliable software around imperfect and rapidly evolving models, including tests, observability, failure handling, and clear technical documentation. Validate solutions work against real customer data.
  • Design for disconnected, resource-constrained environments by considering latency, compute, memory, bandwidth, hardware architecture, and model packaging from the beginning.
  • Contribute actively to technical design and code reviews, help teammates navigate unfamiliar parts of the stack, and improve the shared frameworks that make future integrations faster.

Desired Experience

  • 8+ years working in software engineering, product engineering, or production machine learning positions.
  • Demonstrable experience taking machine learning, robotics, computer vision, or other research-grade software from prototype to production.
  • Strong Python experience and the ability to work effectively in unfamiliar parts of a full-stack system. Experience with Golang, TypeScript, or a reactive framework such as Vue or React is valuable.
  • Experience with machine learning runtimes and frameworks such as PyTorch, ONNX Runtime, or TensorRT, including containerized deployment on GPU-enabled systems.
  • Experience designing and evolving APIs using technologies such as gRPC, Protocol Buffers, GraphQL, or REST.
  • A track record of working through ambiguous technical and product domains, breaking broad problems into incremental deliverables, and defining what to implement before diving into implementation.
  • Excellent engineering judgment, with an emphasis on simple designs, readable code, thoughtful testing, and understanding behavior beyond the happy path.
  • Curiosity and self-direction: you can go deep to understand an unfamiliar system or research implementation, then return with a practical recommendation and working software.
  • Strong cross-functional communication skills and experience incorporating feedback from engineers, product partners, domain experts, and end users.

Startup Culture Expectations

We're a small, fully remote team and everything is our responsibility. Our team thrives on autonomy, trust, and solid communication. Everyone on the team needs to be very comfortable with constant change, moving fast, sharing failures, embracing grit, and building things themselves. Most startups fail and no one will come to save us.

Eligibility

Must be eligible to obtain and maintain a clearance with the U.S. government.



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