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Bayesian Optimization Jobs in Santa Clara, CA (NOW HIRING)

Intuit

Staff AI Scientist

Mountain View, CA · On-site

$209K - $283K/yr

Proficient in multiple optimization paradigms such as combinatorial optimization, gradient methods, or Bayesian optimization. * Proficient in NLP techniques, Explainable AI, and ML frameworks.

Intuit

Staff AI Scientist

Mountain View, CA

$209K - $283K/yr

Proficient in multiple optimization paradigms such as combinatorial optimization, gradient methods, or Bayesian optimization. * Proficient in NLP techniques, Explainable AI, and ML frameworks.

Intuit

Staff AI Scientist

Mountain View, CA · On-site

$209K - $283K/yr

Proficient in multiple optimization paradigms such as combinatorial optimization, gradient methods, or Bayesian optimization. * Proficient in NLP techniques, Explainable AI, and ML frameworks.

Intuit

Staff AI Scientist

Mountain View, CA

$209K - $283K/yr

Proficient in multiple optimization paradigms such as combinatorial optimization, gradient methods, or Bayesian optimization. * Proficient in NLP techniques, Explainable AI, and ML frameworks.

Intuit

Staff AI Scientist

Mountain View, CA · On-site

$209K - $283K/yr

Proficient in multiple optimization paradigms such as combinatorial optimization, gradient methods, or Bayesian optimization. * Proficient in NLP techniques, Explainable AI, and ML frameworks.

Intuit

Staff AI Scientist

Mountain View, CA · On-site

$209K - $283K/yr

Proficient in multiple optimization paradigms such as combinatorial optimization, gradient methods, or Bayesian optimization. * Proficient in NLP techniques, Explainable AI, and ML frameworks.

Intuit Inc.

Staff AI Scientist

Mountain View, CA · On-site

$150 - $190/hr

Proficient in multiple optimization paradigms such as combinatorial optimization, gradient methods, or Bayesian optimization. * Proficient in NLP techniques, Explainable AI, and ML frameworks.

Merck Group

Head of Materials AI

San Jose, CA · On-site

$227K - $340K/yr

Multi-year transformation portfolio spanning AI co-scientists, Bayesian optimization, ML-based simulation, lab digitization, and ELN infrastructure across all global R&D sites * Annual program budget ...

Advantest

Applied AI Engineer

San Jose, CA

Experience with OR-Tools, CP-SAT, ILP/MIP solvers, simulated annealing, genetic algorithms, Bayesian optimization or other metaheuristics. * Experience with graph/netlist data, geometric layouts ...

Advantest

Applied AI Engineer

San Jose, CA · On-site

Experience with OR-Tools, CP-SAT, ILP/MIP solvers, simulated annealing, genetic algorithms, Bayesian optimization or other metaheuristics. * Experience with graph/netlist data, geometric layouts ...

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All JobsBayesian Optimization JobsBayesian Optimization Jobs in Santa Clara, CA

Bayesian Optimization information

What is the difference between Bayesian Optimization vs Data Scientist?

AspectBayesian OptimizationData Scientist
Primary FocusOptimizing complex functions and hyperparametersAnalyzing data, building models, deriving insights
Required SkillsStatistics, probability, machine learning, programmingStatistics, programming, data analysis, visualization
Work EnvironmentResearch labs, AI/ML teams, R&D departmentsBusiness, tech companies, consulting firms
Common ToolsPython, R, Bayesian libraries (e.g., GPy, scikit-optimize)Python, R, SQL, visualization tools

Bayesian Optimization is a specialized technique used within machine learning and AI to efficiently tune hyperparameters or optimize functions. Data Scientists often utilize Bayesian Optimization as part of their toolkit but have broader responsibilities, including data analysis, modeling, and reporting. While Bayesian Optimization focuses on optimization tasks, Data Scientists work on understanding and interpreting data to inform business decisions.

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Bayesian Optimization jobs near you
Infographic showing various Bayesian Optimization job openings in Santa Clara, CA as of August 2026, with employment types broken down into 86% Full Time, 11% Part Time, 1% Temporary, and 2% Contract. Highlights an 77% Physical, 5% Hybrid, and 18% Remote job distribution.

Principal AI Scientist - AI Foundation

Intuit Inc.

Mountain View, CA • On-site

$273.50 - $369.50/hr

Other

Re-posted 11 days ago

Intuit rating

8.2

Company rating: 8.2 out of 10

Based on 92 frontline employees who took The Breakroom Quiz

107th of 246 rated software companies

Job description

Come join the AI Foundation as a Principal AI Scientist. The PDX AI Foundation team focuses on building capabilities that enable and accelerate AI development across Intuit. You will get the chance to lead the work to leverage cutting‑edge AI technologies at scale, focusing on developing AI standards, evaluation methodologies, and tools, as well as collaborating across organizations and functions with our partners in the engineering, product management, analytics and design departments to ensure that we are accelerating the work of developers across Intuit.

Responsibilities
  • Practice leadership and communication skills to influence teams and evangelize data science across the organization.
  • Collaborate with stakeholders to define success criteria and align model metrics with business goals. Work side‑by‑side with product managers, software engineers, and designers in designing experiments and minimum viable products.
  • Lead technical work of a Scrum team: initiating and designing model solutions, driving end‑to‑end architecture designs, and holding the team accountable for high quality code, git, design, costs, and implementation standards.
  • Perform hands‑on data analysis and modeling with large data sets, including discovering data sources, getting data access, cleaning data, and making them model‑ready. Be willing and able to do own ETL and design/build featurization.
  • Apply data mining, NLP, and machine learning (such as supervised/unsupervised, causal‑ML, online learning, Bayesian learning, reinforcement learning, or deep learning) to real‑world problems and datasets.
  • Communicate with partners to ensure successful delivery and integration of DS solutions.
  • Proactively research, explore, and enable new ML technologies. Keep up with new developments in academia and industry and consider possible extensions to solve Intuit customer problems.
Qualifications
  • 10+ years industry experience with data science.
  • BS, MS or PhD in Statistics, Mathematics, Computer Science, Economics, Operations Research, or equivalent.
  • 8+ years hands‑on expertise in ML paradigms such as causal‑ML, supervised/unsupervised, online, Bayesian, reinforcement, or deep learning.
  • Proficiency in multiple optimization paradigms such as combinatorial optimization, gradient methods, or Bayesian optimization.
  • Proficiency in NLP techniques, explainable AI, and ML frameworks.
  • Expertise in modern analytical tools and programming languages such as Python, Scala, Java, and/or R.
  • Experience building end‑to‑end reusable pipelines from data acquisition to model output delivery.
  • Quick learner, adaptable, and able to work independently in a fast‑paced environment.
  • Strong oral and written communication skills. Ability to conduct meetings, make professional presentations, and explain complex concepts and technical material to non‑technical users.

Intuit provides a competitive compensation package with a strong pay‑for‑performance rewards approach. This position will be eligible for a cash bonus, equity rewards, and benefits, in accordance with our applicable plans and programs. Pay offered is based on factors such as job‑related knowledge, skills, experience, and work location. To drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender. The expected base pay range for this position is: Bay Area, California $273,500 – $369,500. For more about our compensation and benefits, see Intuit Careers | Benefits.

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