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Software Engineer Applied Math Jobs in Berkeley, CA

Amazon

Software Engineer

San Francisco, CA · On-site

You'll be part of a larger team of Software Engineers and partner with Product Managers, Applied Scientists, and other engineering teams across the company. This role is based in San Francisco, CA.

Amazon

Software Engineer

San Francisco, CA

You'll be part of a larger team of Software Engineers and partner with Product Managers, Applied Scientists, and other engineering teams across the company. This role is based in San Francisco, CA.

Docusign

Applied AI Software Engineer

San Francisco, CA · On-site

$146.40K - $235.38K/yr

What you'll do Docusign is looking for a highly motivated Applied AI Software Engineer to join our "Agentic Team", as part of our product-led growth organization. As a founding member of the Agentic ...

DocuSign

Applied AI Software Engineer

San Francisco, CA · On-site +1

$146.40K - $235.38K/yr

What you'll do Docusign is looking for a highly motivated Applied AI Software Engineer to join our "Agentic Team", as part of our product-led growth organization. As a founding member of the Agentic ...

The Walt Disney Company

Sr Staff R&D Engineer

Nicasio, CA

$206.40K - $276.70K/yr

MSc or PhD in Computer Science, Electrical Engineering, Applied Math, or a related field with a ... Software Engineer Employment Type: Full time Primary City, State, Region, Postal Code: Nicasio, CA ...

Vertex Sigma Software

Software Engineer

Foster City, CA · On-site

Bachelors degree in an engineering, mathematics, or related field6+ years of industry experience working on large code basesStrong proficiency in TypeScript/JavaScript and one or more of the frontend ...

Applied Materials

Senior Software Developer

Benicia, CA · On-site

$112K - $154K/yr

Who We Are Applied Materials is a global leader in materials engineering solutions used to produce ... Senior Software Engineer - Sigray Connect Location: Benicia, CA (Onsite) Department: Software ...

Apex Informatics

Data Engineer

Pleasanton, CA · On-site

$127.20K - $152.70K/yr

Bachelor's degree or equivalent experience in computer science, applied math, physics, engineering, statistics, economics or related field. 3+ years of industry experience in Data Engineering 3+ ...

Socotec

Software Engineer

San Francisco, CA

We're hiring a Software Engineer to join our US engineering team and contribute meaningfully across ... This is a full-stack role with significant exposure to applied AI, data infrastructure, and ...

Epic

Software Engineer

Fremont, CA · On-site

Required : • Relocation to the Madison, WI area (Reimbursed) • BS/BA or greater in Computer Science, Mathematics, Software Engineering, Computer Engineering, or a related field • A history of ...

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Software Engineer Applied Math information

See Berkeley, CA salary details

$77.8K

$180.6K

$251.6K

How much do software engineer applied math jobs pay per year?

As of May 31, 2026, the average yearly pay for software engineer applied math in Berkeley, CA is $180,634.00, according to ZipRecruiter salary data. Most workers in this role earn between $146,900.00 and $211,800.00 per year, depending on experience, location, and employer.

What is a Software Engineer Applied Math job?

A Software Engineer in Applied Math develops and implements mathematical models, algorithms, and simulations to solve complex problems in various domains such as finance, engineering, and data science. They use programming languages like Python, C++, or MATLAB to create efficient solutions based on numerical analysis, optimization, and machine learning. This role often involves collaborating with scientists, analysts, and engineers to enhance computational methods and improve decision-making processes.

What are the key skills and qualifications needed to thrive in the Software Engineer Applied Math position, and why are they important?

To thrive as a Software Engineer Applied Math, you need a solid background in computer science, mathematical modeling, and software engineering, often supported by a relevant degree such as computer science, applied mathematics, or engineering. Expertise in programming languages (such as Python, C++, or MATLAB), experience with numerical libraries and data analysis tools, and familiarity with version control systems are typically required. Strong analytical thinking, effective problem-solving, and the ability to communicate complex technical concepts are important soft skills for this role. These skills enable you to build efficient software solutions for complex mathematical problems, drive innovation, and collaborate effectively within technical teams.

What types of projects do Software Engineers in Applied Math typically work on?

Software Engineers specializing in Applied Math are often involved in developing algorithms, simulations, and analytical software that solve complex, real-world problems in fields like finance, engineering, machine learning, or data science. Daily responsibilities may include implementing mathematical models, optimizing existing code for performance, and collaborating with cross-disciplinary teams to refine solutions. Depending on the employer, you might work on projects such as risk modeling, signal processing, optimization engines, or predictive analytics tools. This role frequently requires balancing theoretical problem solving with practical software implementation to deliver robust, scalable applications. Working closely with researchers, data scientists, and other engineers, you will contribute to innovation and technical excellence in your organization's projects.
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Software Engineer Applied Math jobs near you
Infographic showing various Software Engineer Applied Math job openings in Berkeley, CA as of May 2026, with employment types broken down into 100% Full Time. Highlights an 50% In-person, and 50% Remote job distribution, with an average salary of $180,634 per year, or $86.8 per hour.
Applied AI Software Engineer

Applied AI Software Engineer

Canvas Medical

San Francisco, CA • On-site

Full-time

Posted yesterday

Job description

Canvas Medical is the electronic medical records (EMR) and payments development platform for healthcare. We build modern, elegant front- and back-end tooling to enable new ways for developers and clinicians to collaborate to solve healthcare’s toughest challenges. Canvas is institutionally backed by some of the greatest technology investors in the world (funded notable health tech companies such as GoodRx, Oscar Health, and Hims & Hers Health).

The Role

We’re hiring an Applied AI Software Engineer to lead evaluations for agents in development and the post-deployment fleet of agents operating in Canvas to automate work for our customers. You will help develop agents in Canvas using state of the art foundation model inference and fine-tuning APIs along with our server-side SDK. The server-side SDK provides extensive tools and virtually all the context necessary for excellent agent performance. You’ll be responsible for designing and running rigorous evaluation experiments that measure performance, safety, and reliability across a wide variety of clinical, operational, and financial use cases.

This role is ideal for someone with deep experience evaluating LLM-based agents at scale. You’ll create high-fidelity unit evals and end-to-end evaluations, define expert-determined ground truth outcomes, and manage iterations across model variants, prompts, tool use, and context window configurations. Your work will directly inform model selection, fine-tuning, and go/no-go decisions for AI features used in production settings.
You’ll collaborate with product, ML engineering, and clinical informatics teams to ensure that Canvas's AI agents are not only capable, but trustworthy and robust under real-world healthcare constraints. You will also work with technical product marketers and developer advocates to help our broader developer community and the broader market understand the uniquely differentiated value of agents in Canvas.
Who You Are
  • You have extensive hands-on experience evaluating LLM-based systems, including multi-agent architectures and prompt-based pipelines.
  • You are deeply familiar with foundation model APIs (OpenAI, Claude, Gemini, etc.) and how to systematically benchmark agent performance using those models in applied settings.
  • You care about correctness and reproducibility and have built or contributed to frameworks for automated evals, annotation pipelines, and experiment tracking.
  • You bring structure to ambiguity and know how to define “correctness” in complex, nuanced domains.
  • You are comfortable collaborating across engineering, product, and clinical subject matter experts.
  • You are not afraid of complexity and are energized by the rigor required in healthcare deployments.
What You’ll Do
  • Design and execute large-scale evaluation plans for LLM-based agents performing clinical documentation, scheduling, billing, communications, and general workflow automation tasks.
  • Build end-to-end test harnesses that validate model behavior under different configurations (prompt templates, context sources, tool availability, etc.).
  • Partner with clinicians to define accurate expected outcomes (gold standard) for performance comparisons in domains of clinical consequence, and partner with other subject matter experts in other non-clinical domains.
  • Run and replicate experiments across multiple models, parameters, and interaction types to determine optimal configurations.
  • Deploy and maintain ongoing sampling for post-deployment governance of agent fleets.
  • Analyze results and summarize tradeoffs in clarity for product and engineering stakeholders, as well as for technical stakeholders among our customers and the broader market.
  • Take ownership over internal eval tooling and infrastructure, ensuring speed, rigor, and reproducibility.
  • Identify and recommend candidates for reinforcement fine-tuning or retrieval augmentation based on gaps identified in evals.
What Success Looks Like at 90 Days
  • An expanded set of robust evaluation suites exists for all major AI features currently in development and in production.
  • We have well-defined correctness criteria for each workflow and a reliable source of expert-determined outcome objects.
  • Product and engineering teams have integrated your evaluation tools into their daily workflows.
  • Evaluation results are clearly documented and reproducible, enabling trust in the performance trajectory.
  • Your have effectively engaged your marketing counterparts to translate your work into key messages to the market and to Canvas customers.
Qualifications
  • 5+ years of experience in applied machine learning or AI engineering, with a focus on evaluation and benchmarking.
  • Proficiency with foundation model APIs and experience orchestrating complex agent behaviors via prompts or tools.
  • Experience designing and running high-throughput evaluation pipelines, ideally including human-in-the-loop or expert-labeled benchmarks.
  • Superlative Python engineering skills and familiarity with experiment management tools and data engineering toolsets in general including, yes, SQL and database management.
  • Familiarity with clinical or healthcare data is a strong plus.
  • Experience with reinforcement fine-tuning, model monitoring, or RLHF is a plus.
  • Research shows that women and other minority groups might avoid applying if they don’t meet 100% of the qualifications. We encourage you to apply even if you don’t meet everything listed in the job posting.
We are a mostly remote, distributed team. We encourage people to do their work when and where they perform at their best. Because of this structure, strong written communication skills, time management skills, and personal accountability are very important to us.

Employee Benefits:
Competitive Salary & Equity Package
Health Insurance
Home Office Stipend
401k
Paid Maternity/Paternity Leave (12 weeks)
Flexible/unlimited PTO
Canvas Medical provides equal employment opportunities to all employees and applicants for employment without regard to race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.