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Applied Scientist
Adaption · San Francisco · Hybrid · Active · Ashby
Job facts
| Field | Value |
|---|---|
| Company | Adaption |
| Title | Applied Scientist |
| Normalized title | - |
| Department / team | Applied ML / Applied ML |
| Location | San Francisco, CA, United States |
| Work model | Hybrid / Hybrid |
| Employment type | Full Time |
| Salary | - |
| Status | active |
| ATS provider | Ashby |
| Posted / first seen | — / 2026-05-29 |
| Changed / last seen | 2026-05-29 / 2026-06-06 |
Related slices
| Page | What it contains | Open |
|---|---|---|
| Company jobs | Active postings from Adaption. | Open |
| Company breakdowns | Role, location, ATS, and work model facets for this company. | Open |
| ATS provider jobs | Active postings observed through Ashby. | Open |
| Provider filtered search | The same provider as a filtered job collection. | Open |
| City jobs | Active postings in San Francisco. | Open |
| Department jobs | Active postings in Applied ML. | Open |
| Work model jobs | Active Hybrid postings. | Open |
| Lifecycle events | Open, update, close, and reopen events for this posting. | Open |
| Original posting | Canonical source or apply URL captured from the ATS. | Open |
Linked records
| Company | Adaption |
| Source | 5f007786-fb83-4b96-aa3d-5e7a3599f28d |
| ATS provider | Ashby |
Description
The Role We're looking for an Applied Scientist who thrives at the intersection of applied research and real-world products. You'll push the frontier on efficiency, gradient-free exploration, real-time learning, and interface design — translating advances in these areas into adaptive ML systems that ship. You'll contribute meaningfully to both the research roadmap and product strategy, and lead the design and implementation of the systems that come out of it.
Responsibilities Advance the Research Frontier: Drive original work on efficient, adaptive ML. including online learning, gradient-free methods, and novel architectures, and turn those advances into systems that run in production.
Deliver Real-World Impact: Lead the design, implementation, and deployment of ML systems end-to-end, from research prototype to production.
Shape the Roadmap: Contribute to research direction and product strategy, identifying which problems are worth solving and which methods are worth investing in.
Hands-on Execution: Own implementation of data products at Adaption, addressing novel challenges in data, interaction, and evaluation with both creativity and engineering rigor.
Qualifications 3–4 years of industry experience in machine learning or applied research, with a track record of deploying ML systems that solved real business problems.
Strong software engineering skills and fluency with ML frameworks (e.g., PyTorch, JAX, TensorFlow).
Hands-on experience with online learning, reinforcement learning, or efficient ML architectures.
Solid understanding of data modeling for training and how curation decisions shape model performance.
Excellent communication skills and the ability to align technical work with high-level goals.
A mindset of ownership, curiosity, and a bias toward action.
Bonus: experience training or fine-tuning models using human feedback, reward signals, or other adaptive learning techniques.
Above all, we're looking for great teammates who make work feel lighter and aren't afraid to go out on a limb with bold ideas. You don't need to be perfect, but you do need to be adaptable. We encourage you to apply, even if you don't check every box.
About Us Most AI is frozen in place - it doesn't adapt to the world. We think that's backwards. Our mandate is to build efficient intelligence that evolves in real-time. Our vision is AI systems that are flexible, personalized, and accessible to everyone. We believe efficiency is what makes this possible - it's how we expand access and ensure innovation benefits the many, not the few. We believe in talent density: bringing together the best and most driven individuals to push the boundaries of continual adaptation. We're looking for builders and creative thinkers ready to shape the next era of intelligence.
Benefits Flexible work : In-person collaboration in the Bay Area, a distributed global-first team, and team offsites.
Adaption Passport : Annual travel stipend to explore a country you've never visited. We're building intelligence that evolves alongside you, so we encourage you to keep expanding your horizons.
Lunch Stipend: Weekly meal allowance for take-out or grocery delivery.
Well-Being : Comprehensive medical benefits and generous paid time off.
Full job record
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| Org ID | 1765bb84-ef1a-4913-b99d-908b8a356e16 |
| Source ID | 5f007786-fb83-4b96-aa3d-5e7a3599f28d |
| Board ID | 5f007786-fb83-4b96-aa3d-5e7a3599f28d |
| Provider | ashby |
| Provider Job Key | 3ad5b8c3-aea4-427e-9902-fa5425290721 |
| Title | Applied Scientist |
| Normalized Title | — |
| Status | active |
| Active | yes |
| Location Text | San Francisco |
| Department | Applied ML |
| Team | Applied ML |
| Employment Type | full_time |
| Workplace Type | hybrid |
| Remote Policy | hybrid |
| Country | United States |
| Region | CA |
| City | San Francisco |
| Salary Raw | — |
| Salary Min | — |
| Salary Max | — |
| Salary Currency | — |
| Salary Period | — |
| Source URL | https://jobs.ashbyhq.com/adaption/3ad5b8c3-aea4-427e-9902-fa5425290721 |
| Apply URL | https://jobs.ashbyhq.com/adaption/3ad5b8c3-aea4-427e-9902-fa5425290721/application |
| First Seen At | 2026-05-29 05:45:41Z |
| Last Seen At | 2026-06-06 20:30:07Z |
| Last Checked At | 2026-06-06 20:30:07Z |
| Last Changed At | 2026-05-29 05:45:41Z |
| Inactive At | — |
| Source Posted At | — |
| Source Updated At | — |
| Raw Payload Uri | s3://job-postings-prod-raw-590183727216/raw/provider=ashby/board=adaption/date=2026-06-06/2026-06-06T20-30-06-492Z-57d2bbcb4eebe301156faa98c3a8e28c5e98c01f9dc95103a00d6179aaa7e3be.json |
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