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Principal Applied Scientist

Swiftkey

Mountain View, CAJobPosted 1 day agoStill listed today

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At a glance

Compensation
No compensation found
Location
Mountain View, CA
Work Authorization
Not specified

Olive lists jobs from US employers, including remote roles you can work from the United States.

Job overview

The Principal Applied Scientist will lead research initiatives and translate research into production improvements across search, LLM alignment, and retrieval-augmented systems. The role advances post-training and alignment methods, develops retrieval and ranking capabilities, and architects RAG pipelines. It also involves rigorous experimentation, cross-disciplinary strategy, mentoring, and collaboration with engineering, product, design, and academic partners.

Skills & qualifications

RequiredNice to have

Skills

PythonC++C#CJavaMachine LearningLarge-Scale Machine Learning SystemsSearch SystemsAdvertising SystemsRecommendation SystemsLarge Language ModelsNatural Language ProcessingProblem Solving

Qualifications

Bachelor's in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering or Related Field + 8 Years; Master's in These Fields or Related Field + 6 Years; Or Doctorate in These Fields or Related Field + 5 YearsMaster's in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering or Related Field + 12 Years or Doctorate in These Fields or Related Field + 8 Years or Equivalent Experience6+ Years Coding Experience6+ Years Industry Machine Learning Experience8+ Years Related Experience6+ Years Related Experience5+ Years Related Experience12+ Years Related Experience

Full job description

You will lead one or more big initiatives leveraging your expertise across a broad research landscape, including advanced research methodologies and applied techniques. You'll gain deep knowledge of a service, platform, or domain, and drive product opportunities by sharing emerging industry trends and applied technologies. You will review business requirements and incorporate research insights to meet strategic goals. You'll provide directions on the types of data and machine learning model strategies needed to solve complex problems and apply deep subject‑matter expertise to drive measurable business impact. You will support the onboarding of new team members and help develop academic collaborators into effective contributors within multidisciplinary teams. You will advance LLM post‑training and alignment techniques by designing, implementing, and evaluating novel methods that improve reasoning quality, safety, controllability, and factual grounding across large‑scale models. You will drive and develop next‑generation search capabilities by building and optimizing retrieval, ranking, and relevance systems that integrate deeply with LLM‑powered experiences. You will architect and refine RAG pipelines that enhance retrieval fidelity, reduce hallucinations, and deliver more context‑aware, user‑aligned responses in production environments. You will translate research into production by running experiments, analyzing results, and collaborating with engineering partners to deploy scalable, reliable model improvements. You will drive scientific rigor through hypothesis‑driven experimentation, reproducible methodologies, and clear documentation of findings, insights, and model behaviors. You will drive collaborate across disciplines—including research, engineering, product, and design—to shape long‑term strategy for search, alignment, and retrieval‑augmented systems. You will contribute to a culture of innovation by sharing learnings, mentoring peers, and participating in internal research discussions, reviews, and technical deep dives. Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 8+ years related experience (e.g., statistics, predictive analytics, research) OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 5+ years related experience (e.g., statistics, predictive analytics, research) Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 12+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 8+ years related experience (e.g., statistics, predictive analytics, research) OR equivalent experience. 6+ years of experience coding in Python, C++, C#, C or Java. 6+ year of industry experience applying Machine Learning techniques. Experience building and improving large scale Machine Learning system for search, ads, and recommendation, adopting LLM. Research background on Machine Learning, LLM and NLP. Proficient problem solver: ability to identify and solve problems that the world has not solved before.

How this job compares

Set against the 983 open Applied Scientist jobs on Olive Jobs, counted November 7, 2026.

Pay
  • This postingNot listed
  • California median$172–260K/yr176 salary ranges
Openings
Olive Jobs lists 200 open Applied Scientist jobs in California and 983 across the US. 1% of them nationwide are listed as remote or flexible.
Hiring the most in California
Experience
This posting asks for at least 5 years of experience; Applied Scientist postings that state a minimum ask for 4 years at the median (790 postings).
Education
438 of the 983 open Applied Scientist jobs (45%) ask for a bachelor's degree or higher.

Counted across the open, public US postings on Olive Jobs on November 7, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.

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