Applied Scientist

An Applied Scientist develops novel machine learning methods to solve concrete product problems. They read and extend research, prototype models, run rigorous experiments, and work with engineers to bring the best approaches into production. The role sits between pure research and engineering, prizing scientific rigor while staying anchored to real business impact.

Responsibilities

Research and prototype new modeling approaches
Design experiments with sound methodology and baselines
Adapt state-of-the-art methods to product constraints
Collaborate with engineers to productionize models
Analyze results and publish or document findings
Advise teams on modeling strategy and trade-offs

Must-have skills

Deep machine learning and statistics expertise
Strong research and experimental methodology
Proficiency in Python and a deep learning framework
Ability to read and implement research papers
Clear scientific communication

Nice-to-have skills

Advanced degree or publication record
Domain specialization (NLP, vision, RL)
Distributed and large-scale training
Production deployment experience

Average Salary

Typical US base salary for an HR Generalist by experience level.

Junior

0–2 yrs experience

$130,000 – $165,000
US annual salary (USD)

Intermediate

0–2 yrs experience

$165,000 – $205,000

US annual salary (USD)

Senior

0–2 yrs experience

$205,000 – $280,000

US annual salary (USD)

Figures are annual US market estimates for orientation, not offers. Actual pay varies by location, company stage, and equity.

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Frequently asked questions

Applied Scientist vs Research Scientist: what is the difference?
Applied Scientists focus on solving product problems with rigorous methods and shipping results. Research Scientists pursue longer-horizon, more fundamental questions, often with publication as a goal.
Do Applied Scientists need a PhD?
Many roles prefer or require an advanced degree because of the research depth involved, though strong applied research experience can qualify candidates.
How is this role different from a Machine Learning Engineer?
Applied Scientists invent and adapt methods; ML Engineers focus more on building and scaling the systems that run them. The line varies by company.
What does an Applied Scientist do day to day?
Reading papers, prototyping models, running experiments, analyzing results, and collaborating with engineering to move promising work into production.

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