Applied Research - Software Engineering
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 13h ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 33d ago
The date the source published, not the day we noticed it (2026-08-12). Last seen at its source 2h ago.
Is it remote?
Remote
That is the location the employer filed this posting under. Quoted as written — we do not re-word the source's own location.
Who may apply?
Not stated
The description states no restriction of its own. This is the source's own tag.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
-
greenhouse employer's own board first seen 33d ago · last seen 2h ago
The listing
Senior/Principal, Applied Research Software Engineer
Remote
ABOUT THE JOBCompany 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.