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Applied Math Jobs in Sunnyvale, CA (NOW HIRING)

LinkedIn

Senior Applied Scientist

Mountain View, CA · On-site

$144K - $236K/yr

Doctorate in Statistics, Biostatistics, Applied Mathematics, Engineering, Operations Research, Economics, Informatics, Computer Science, Data Science or related field. * BS and 5+ years of relevant ...

LinkedIn

Senior Applied Scientist

Mountain View, CA · On-site +1

$144K - $236K/yr

Doctorate in Statistics, Biostatistics, Applied Mathematics, Engineering, Operations Research, Economics, Informatics, Computer Science, Data Science or related field. * BS and 5+ years of relevant ...

Capital One

Applied Researcher II

San Francisco, CA · On-site

S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 4 years of experience in Applied Research Preferred Qualifications: * PhD in Computer ...

Capital One

Applied Researcher II

San Jose, CA · On-site

S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 4 years of experience in Applied Research Preferred Qualifications: * PhD in Computer ...

Capital One

Applied Researcher II

San Francisco, CA · On-site

S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 4 years of experience in Applied Research Preferred Qualifications: * PhD in Computer ...

Capital One

Applied Researcher II

San Francisco, CA · On-site

S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 4 years of experience in Applied Research Preferred Qualifications: * PhD in Computer ...

Capital One

Applied Researcher II

San Jose, CA · On-site

S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 4 years of experience in Applied Research Preferred Qualifications: * PhD in Computer ...

Capital One

Applied Researcher II

San Jose, CA · On-site

S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 4 years of experience in Applied Research Preferred Qualifications * PhD in Computer ...

Capital One

Applied Researcher II

San Jose, CA · On-site

S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 4 years of experience in Applied Research Preferred Qualifications: * PhD in Computer ...

Capital One

Applied Researcher II

San Jose, CA · On-site

S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 4 years of experience in Applied Research Preferred Qualifications: * PhD in Computer ...

Capital One

Applied Researcher II

San Francisco, CA · On-site

S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 4 years of experience in Applied Research Preferred Qualifications * PhD in Computer ...

Capital One

Applied Researcher II

San Jose, CA · On-site

S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 4 years of experience in Applied Research Preferred Qualifications * PhD in Computer ...

Capital One

Applied Researcher II

San Jose, CA · On-site

S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 4 years of experience in Applied Research Preferred Qualifications * PhD in Computer ...

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Showing results 21-40

All JobsApplied Math JobsApplied Math Jobs in Sunnyvale, CA

Applied Math information

See Sunnyvale, CA salary details

$26.4K

$69.1K

$110.9K

How much do applied math jobs pay per year?

As of Sep 6, 2026, the average yearly pay for applied math in Sunnyvale, CA is $69,054.00, according to ZipRecruiter salary data. Most workers in this role earn between $52,800.00 and $82,200.00 per year, depending on experience, location, and employer.

What is an applied mathematician?

Applied mathematicians are professionals who use mathematical theories, techniques, and computational methods to solve practical problems in fields such as engineering, science, business, and industry. They often develop models to analyze real-world phenomena, optimize processes, and predict outcomes. Applied mathematicians may work in diverse areas like data analysis, operations research, finance, and computer science, collaborating with experts from other disciplines to address complex challenges.

What are the key skills and qualifications needed to thrive as an applied mathematician, and why are they important?

To thrive as an Applied Mathematician, you need strong mathematical modeling, analytical, and problem-solving skills, usually supported by a degree in mathematics, applied mathematics, or a related field. Familiarity with programming languages (such as Python, MATLAB, or R), statistical software, and computational tools is typically required. Excellent communication, teamwork, and critical thinking abilities help translate complex mathematical concepts for diverse audiences and collaborative projects. These skills are vital for developing solutions to real-world problems across industries, ensuring accuracy, innovation, and practical impact.

What are some typical projects or problems an applied mathematician may work on within a multidisciplinary team?

Applied mathematicians often collaborate with experts from fields such as engineering, computer science, and finance to tackle real-world challenges. For example, they might develop algorithms for optimizing logistics and supply chains, create mathematical models to predict disease spread in healthcare, or analyze large data sets to inform business strategies. This collaboration typically involves regular meetings, data sharing, and iterative problem solving, making strong communication skills and adaptability essential for success in the role.

What is the difference between Applied Math vs Data Analyst?

AspectApplied MathData Analyst
Required CredentialsBachelor's or higher in Mathematics, Applied Math, or related fieldsBachelor's or higher in Statistics, Data Science, or related fields
Work EnvironmentResearch labs, academia, finance, engineeringBusiness, finance, healthcare, marketing
Industry UsageModeling, simulations, algorithm developmentData interpretation, reporting, visualization
Common Search/ComparisonApplied Math vs Data Analyst

Applied Math and Data Analysts often share skills in statistical analysis and problem-solving. However, Applied Math focuses more on developing mathematical models and algorithms, while Data Analysts primarily interpret and visualize data to inform business decisions. Both roles are vital across industries, but their daily tasks and focus areas differ significantly.

Is applied math a useful degree?

Applied math is a useful degree for careers in data analysis, finance, engineering, and research, as it develops skills in problem-solving, modeling, and quantitative analysis. Graduates often find employment in industries that rely on mathematical and computational tools, and the degree can lead to roles requiring programming and statistical knowledge.

Is applied math in demand?

Applied math professionals are in high demand across industries such as finance, data analysis, engineering, and technology due to their skills in modeling, problem-solving, and quantitative analysis. Employers seek candidates with strong analytical abilities and proficiency in tools like MATLAB, Python, or R, making applied math a valuable and often well-compensated field.

What careers use applied math?

Applied math is used in careers such as data analyst, financial analyst, operations researcher, actuary, engineer, and computer scientist. These roles involve using mathematical models, statistical techniques, and computational tools to solve real-world problems across industries like finance, technology, healthcare, and engineering.

What to do with a degree in applied math?

A degree in applied math prepares individuals for roles such as data analyst, operations researcher, financial analyst, or software developer. It involves skills in problem-solving, statistical analysis, and programming, often utilizing tools like MATLAB, Python, or R. Graduates can work in industries including finance, technology, engineering, and consulting.

What are popular job titles related to Applied Math jobs in Sunnyvale, CA?

For Applied Math jobs in Sunnyvale, CA, the most frequently searched job titles are:

What job categories do people searching Applied Math jobs in Sunnyvale, CA look for?

The top searched job categories for Applied Math jobs in Sunnyvale, CA are:

What cities near Sunnyvale, CA are hiring for Applied Math jobs?

Cities near Sunnyvale, CA with the most Applied Math job openings:

Applied Math jobs near you
Infographic showing various Applied Math job openings in Sunnyvale, CA as of August 2026, with employment types broken down into 74% Full Time, 23% Part Time, 2% Contract, and 1% Nights. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $69,054 per year, or $33.2 per hour.

Senior Applied Scientist, Efficient LLM Inference & Model Optimization

Nebius

Palo Alto, CA • On-site, Remote

Full-time

Medical, Dental, Vision, Retirement

Re-posted 15 days ago

Job description

The role 

Nebius Token Factory needs scientists who can turn frontier inference bottlenecks into research problems, publish credible work, and then help ship the results into production. This is not a papers-only research role. The Applied Scientist is expected to design rigorous experiments, write strong code, collaborate with engineers, and convert research into deployed inference capabilities.

A Senior Applied Scientist owns well-scoped research and production optimization projects. They can publish or prepare high-quality technical work while also producing code, experiments, and prototypes that engineers can use.

Your responsibilities: 

  • Own focused research projects from hypothesis through experiment, ablation, prototype, and production handoff.

  • Prepare internal reports, technical blogs, or papers when the work is externally credible.

  • Partner directly with MLEs to ensure research prototypes become usable production components.

  • Define and execute research programs in efficient LLM and VLM inference with measurable production impact.

  • Invent, evaluate, and productionize methods for quantization, QAT, distillation, speculative decoding, KV-cache reuse, KV-cache compression, long-context inference, MoE routing, and model/runtime co-optimization.

  • Build high-quality prototypes in PyTorch, Triton, CUDA-adjacent tooling, or inference-serving frameworks, then work with MLEs and platform engineers to productionize them.

  • Design rigorous evaluation methodology covering quality, latency, throughput, numerical stability, memory footprint, tail latency, and cost per token.

  • Publish papers, technical reports, blog posts, and open-source artifacts that build external credibility for Nebius Token Factory.

  • Collaborate with MLE, GPU kernel, backend infrastructure, product, and customer teams to choose high-leverage research bets.

  • Mentor engineers and scientists on experimental design, scientific rigor, and model/system tradeoffs.

Must-haves: 

  • PhD in computer science, machine learning, ML systems, computer systems, computer architecture, electrical engineering, applied math, or a closely related field.

  • Strong publication record or equivalent research artifacts in ML, ML systems, efficient inference, model compression, quantization, distillation, serving systems, or related areas.

  • Strong hands-on coding ability in Python and PyTorch; ability to move from idea to experiment to prototype quickly.

  • Deep understanding of LLMs, VLMs, transformer inference, decoding algorithms, model compression, quantization, and production-serving tradeoffs.

  • Strong experimental design skills, including ablations, baselines, metrics, statistical reasoning, and failure analysis.

  • Excellent written and verbal communication.

Nice-to-haves: 

  • First-author publications in NeurIPS, ICML, ICLR, MLSys, ACL, EMNLP, ASPLOS, OSDI, SOSP, ISCA, HPCA, or comparable venues.

  • Experience deploying ML models or inference optimizations in production.

  • Experience with vLLM, SGLang, TensorRT-LLM, NVIDIA Dynamo, FlashAttention, FlashInfer, Triton, CUDA, or PyTorch internals.

  • Experience with post-training, SFT, DPO, RLHF, RLAIF, preference optimization, or synthetic data generation when connected to inference quality or efficiency.

  • Open-source research artifacts, widely used benchmarks, high-quality technical blogs, or invited talks in efficient AI systems.

Key employee benefits in the US:

  • Health insurance: 100% company-paid medical, dental, and vision coverage for employees and families.

  • 401(k) plan: Up to 4% company match with immediate vesting.

  • Parental leave: 20 weeks paid for primary caregivers, 12 weeks for secondary caregivers.

  • Remote work reimbursement: Up to $85/month for mobile and internet.

  • Disability & life insurance: Company-paid short-term, long-term and life insurance coverage.

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