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Adaption

Research Scientist

Adaption is hiring a Research Scientist for a remote role open to applicants in United States. Level rates it ; you can apply on Adaption.

Level's read on this job

  • Builds AI ●●●● is how Level rates this research scientist role: the job is building AI systems.
  • The posting lists this role as remote.
  • Tools and skills the posting cites include PyTorch, TensorFlow and JAX.
  • Level classifies it as a mid-level role.
  • Level lists 10 other open roles at Adaption.

AI in this role

PyTorchTensorFlowJAX
fine-tuning

Our research principles

Sweat the details. Technical excellence requires obsessing over every detail. We co-design serving, algorithms, and interface as one system to maximize efficiency and enable real-time adaptation.

Move with conviction. Extraordinary results require extraordinary effort. We operate with urgency as a unified team, concentrating resources on a few high-conviction bets where research and impact intersect.

Metrics that matter. The most intelligent system will increasingly be defined by building an algorithm that can interact with the world. Research ideas are tested through working products. If it doesn't improve what users can do, we question whether it matters. We share what moves the field; we don't optimize for paper count.

The role

This is a research role which is focused on real world impact. We care about building our frontier innovation around efficiency, gradient free exploration, real time learning and interface design. A revolution is underway where the cost of generating synthetic data is now low enough that we can treat the data space as malleable and something which can be optimized. We can steer synthetic data towards desirable properties and make previously invisible worlds with limited data coverage more visible. The most intelligent system will increasingly be defined by building an algorithm that can interact with the world. This means for the first time researchers who care about intelligence need also be obsessed with how a model interacts. If any of these statements resonate with you, we would like to hear from you.

Responsibilities

  • Innovation: innovate on our product to co-design algorithms that react real-time to product signal and feedback. Design new ways of giving feedback that drive better algorithms.

  • Cross-Stack Optimization: collaborate across software, hardware, and algorithmic domains to achieve system-wide efficiency gains

  • Measure what matters: we believe strongly that the ultimate signal of value is whether we have real world impact. Our current algorithms are capable of interacting with the world which is why product matters so much.

Qualifications

  • A PhD or equivalent research experience in a computer science field

  • 4-5+ years of industry experience

  • Deep expertise in at least one area: model efficiency, real time alignment or algorithmic optimization

  • Systems thinking ability to understand and optimize across the full ML stack

  • Strong programming skills in Python. Experience with deep learning frameworks (PyTorch, JAX, TensorFlow)

  • Knowledge of model optimization techniques (RLHF, finetuning)

  • Experience in an industry lab with computing at scale

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.

How we rate this

Research Scientist at Adaption rates 95 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Fine-tuningPyTorchTensorFlowJAX

Also common in research scientist jobs at this level

Pay

Typical research scientist job
$190k

This posting doesn't list pay. Use the typical research scientist figure when pay comes up. See research scientist jobs

Questions you could be asked

  1. Walk me through fine-tuning a model: what data did you use, and how did you check the result?
  2. Walk me through how you've used PyTorch in your day-to-day work.
  3. What are the limits of TensorFlow that you've run into, and how did you work around them?
  4. What's a project where you used JAX hands-on?
  5. How would you decide a model or AI system is ready to ship?

Adapt your resume

  • List these exact terms on your resume: Fine-tuning, PyTorch, TensorFlow, and JAX. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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