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Data Science Software Engineer Jobs in California

Software Engineer, Data

San Francisco, CA · On-site

$134K - $162K/yr

As a Software Engineer, Data, you will contribute to data engineering efforts by designing and ... Responsibilities : • Work across our engineering organization and stakeholders from data science ...

Senior Software Engineer

Sunnyvale, CA · On-site

$143K - $189K/yr

... Science, Software Engineering, Machine Learning, or related field. Passion for solving complex problems and uncovering hidden insights through data.

Data Engineer

San Diego, CA · On-site

$61K - $141K/yr

Master's degree in Computer Science, Computer Engineering, Mathematics, Data Science, Software Engineering, Electrical Engineering, Physics, or a related field * Cloud Development Certification ...

Master's degree in Computer Science, Computer Engineering, Mathematics, Data Science, Software Engineering, Electrical Engineering, Physics, or a related field * Cloud Development Certification ...

Data Engineer

San Diego, CA · On-site

$62K - $141K/yr

Master's degree in Computer Science, Computer Engineering, Mathematics, Data Science, Software Engineering, Electrical Engineering, or Physics * Cloud Development Certification, including AWS ...

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Showing results 1-20

Data Science Software Engineer information

See California salary details

$43.9K

$128K

$175.2K

How much do data science software engineer jobs pay per year?

As of Jul 13, 2026, the average yearly pay for data science software engineer in California is $128,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $113,000.00 and $135,700.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Data Science Software Engineer, and why are they important?

To thrive as a Data Science Software Engineer, you need strong proficiency in programming (especially Python or R), a solid understanding of statistics and algorithms, and typically a degree in computer science, data science, or a related field. Familiarity with machine learning frameworks (such as TensorFlow or scikit-learn), data processing tools (like Spark or Hadoop), and cloud platforms (AWS, GCP, or Azure) is essential, as are relevant certifications. Excellent problem-solving abilities, communication skills, and the ability to work collaboratively with cross-functional teams set top performers apart. These competencies are vital for efficiently developing scalable data-driven solutions that drive business insights and innovation.

How does a Data Science Software Engineer typically collaborate with data scientists and other stakeholders on projects?

Data Science Software Engineers play a vital role in bridging the gap between data science and software engineering teams. They work closely with data scientists to translate prototypes and models into scalable, production-ready code, and often collaborate with product managers, analysts, and infrastructure engineers to ensure seamless integration. Regular communication and code reviews are essential, as is an iterative development process to address feedback and ensure solutions meet both technical and business requirements. This cross-functional collaboration helps deliver robust data-driven applications that align with organizational goals.

Which is the hardest field in it?

For a Data Science Software Engineer, the most challenging fields often involve complex machine learning algorithms, large-scale data processing, and advanced statistical analysis. Staying current with rapidly evolving tools like Python, R, and cloud platforms also requires continuous learning and adaptation. These areas demand strong problem-solving skills and deep technical knowledge.

What is a Data Science Software Engineer?

A Data Science Software Engineer is a professional who combines software engineering skills with data science expertise to build scalable data-driven systems and applications. They design, develop, and optimize software that supports data pipelines, machine learning models, and analytics platforms. Their work bridges the gap between data scientists, who focus on statistical analysis and modeling, and traditional software engineers, who focus on building robust and efficient software systems. Data Science Software Engineers ensure that data solutions are production-ready, scalable, and maintainable.

Can a software engineer work as a data scientist?

A software engineer can transition to a data scientist role by developing skills in statistics, machine learning, and data analysis, often using tools like Python, R, and SQL. While the roles have different focuses, software engineers' programming expertise can be a strong foundation for data science work, especially with additional training or experience in data modeling and analytics.

Is 40 too late for data science?

Data science software engineers can enter the field at any age, as success depends on skills, experience, and continuous learning. Many professionals transition into data science later in their careers by acquiring relevant knowledge in programming, statistics, and tools like Python or R. Age is not a barrier if you develop the necessary technical expertise and stay current with industry trends.

What engineers make $500,000?

Senior data science software engineers with extensive experience, advanced skills in machine learning, and proficiency in tools like Python, R, and cloud platforms can reach salaries of $500,000 or more, especially in high-cost-of-living areas or within large tech companies. Compensation often includes base salary, bonuses, and stock options, reflecting their expertise and impact on business outcomes.

What is the difference between Data Science Software Engineer vs Data Analyst?

AspectData Science Software EngineerData Analyst
Required SkillsProgramming, software development, machine learningData visualization, statistical analysis, reporting
Work EnvironmentSoftware development teams, engineering projectsBusiness units, reporting teams
Common ToolsPython, Java, SQL, ML frameworksExcel, Tableau, SQL, R
Industry UsageTech, finance, healthcare, startupsMarketing, finance, retail, research

While both roles analyze data, Data Science Software Engineers focus on developing software solutions and machine learning models, requiring strong programming skills. Data Analysts primarily interpret data through visualization and statistical methods to support business decisions. The roles often overlap but serve different functions within organizations.

What are popular job titles related to Data Science Software Engineer jobs in California? For Data Science Software Engineer jobs in California, the most frequently searched job titles are:
What job categories do people searching Data Science Software Engineer jobs in California look for? The top searched job categories for Data Science Software Engineer jobs in California are:
Infographic showing various Data Science Software Engineer job openings in California as of July 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, 1% Temporary, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $128,018 per year, or $61.5 per hour.
Software Engineer - Data Platform

Software Engineer - Data Platform

Hadrian Automation, Inc

Los Angeles, CA • On-site

$123K - $148K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 10 days ago


Job description

Hadrian - Manufacturing the Future
Hadrian is building autonomous factories that help aerospace and defense companies manufacture rockets, satellites, jets, and ships up to 10x faster and up to 2x cheaper. By combining advanced software, robotics, and full-stack manufacturing, we are reinventing how America produces its most critical parts.
We're accelerating our mission with the launch of Factory 3 in Mesa, Arizona, a 290,000-square-foot facility creating 350 new jobs. We are expanding rapidly to support thousands of future hires, launching Hadrian Maritime to expand into naval production, and introducing a Factory-as-a-Service model that delivers complete systems instead of individual parts.
Hadrian is backed by leading investors including T. Rowe Price, Lux Capital, Founders Fund, and Andreessen Horowitz, our fast-growing team is united around reindustrializing American manufacturing for the 21st century and beyond.
The Role
As a foundational software engineer on our data platform engineering team, you will lead the charge on building the AI and data infrastructure that powers Hadrian's autonomous factories. This means writing software to aggregate, store, and make sense of data - and building the intelligent systems that sit on top of it.
Examples of possible work include building RAG pipelines and vector search systems that give our AI models access to the right manufacturing knowledge at the right time, developing MLOps infrastructure to deploy and monitor production models, building software agents to get data off of machines, and creating certified datasets that enable operations research, machine intelligence, and business analytics at scale.
You will be challenged to think creatively and solve complex data and AI integration problems. You will work cross functionally with production experts, operations research scientists, software engineers, and machining specialists to develop novel solutions working toward fully automated factories.
What You'll Do
  • Scope, architect, implement, and deploy critical AI and data infrastructure applications that will drive revenue and make a positive impact in the world.
  • Build and own RAG pipelines and vector search systems that enable intelligent retrieval of manufacturing knowledge across Hadrian's data estate.
  • Design and manage MLOps infrastructure - training pipelines, model deployment, monitoring, and orchestration - so that ML and operations research models run reliably in production.
  • Build and manage a robust data warehouse and write software to coordinate and deploy data pipelines.
  • Conceptualize and own the data architecture for multiple large-scale projects.
  • Create and contribute to data frameworks that span on-premises and cloud infrastructure, improving the efficacy of logging machine data, while working with data infrastructure to triage issues and resolve.
  • Solve our most challenging machine data and AI integration problems, utilizing optimal ETL patterns, frameworks, query techniques, and retrieval architectures sourcing from structured and unstructured data sources.
  • Collaborate with machine engineers, operations research scientists, product managers, and data scientists to understand data and AI needs, translating complex systems into tools people actually use.
  • Get to build alongside an incredible team of software engineers, mechanical engineers, operators, and the best machinists/CAM programmers in the world.

What We're Looking For
  • Have extensive experience shipping modern, data-centric applications (our data systems use Argo-Workflows, Dagster, Superset, Aurora, RDS, S3, and back-ends are Go and Python, with gRPC/Avro and Kafka as our messaging platform).
  • Experience building AI infrastructure in production: RAG pipelines, vector databases (such as Pinecone, Weaviate, Chroma, or equivalent), embedding systems, or semantic search.
  • Hands-on MLOps experience: owning the full lifecycle of ML models from training through deployment and monitoring (SageMaker, Ray, MLflow, or equivalent).
  • Have experience with IaC and GitOps tooling (We use Terraform extensively and have centralized on Kubernetes/Argo/Helm).
  • Extremely well versed with data querying techniques across NoSQL and SQL platforms.
  • Have a Bachelor's degree in Computer Science and/or equivalent experience.
  • Solid understanding in building data architecture and pipelines.
  • Are self-motivated and eager to get hands-on and tackle challenges independently while working collaboratively toward identified objectives.
  • Work with a platform mentality -- driven to find the right architecture and plan up front and solve problems with the long term in mind.
  • Take responsibility and ownership finding solutions no matter what.
  • Deploy your broad experience and big picture view to fix undreamed of problems with innovative solutions.
  • Feel passionate about making things move in the real world with software.
  • Are excited to work in a fast-paced environment with high-stakes and quick iteration cycles.
  • Are a highly effective communicator when speaking or writing, especially when presenting technical information.

Compensation
For this role, the target salary range is $120,000 - $200,000 (actual range may vary based on experience).
This is the lowest to highest salary we reasonably and in good faith believe we would pay for this role at the time of this posting. We may ultimately pay more or less than the posted range, and the range may be modified in the future. An employee's pay position within the salary range will be based on several factors, including, but not limited to, relevant education, qualifications, certifications, experience, skills, geographic location, performance, and business or organizational needs.
Benefits for Full-time Employees
  • Medical, dental, vision, and life insurance plans for employees
  • 401k
  • Relocation support may be provided for certain situations, based on business need.
  • Flexible vacation policy
  • Equity

ITAR Requirements
To conform to U.S. Government space technology export regulations, including the International Traffic in Arms Regulations (ITAR) you must be a U.S. citizen, lawful permanent resident of the U.S., protected individual as defined by 8 U.S.C. 1324b(a)(3), or eligible to obtain the required authorizations from the U.S. Department of State. Learn more about the ITAR here.
Hadrian Is An Equal Opportunity Employer
It is the Company's policy to provide equal employment opportunity for all applicants and employees. The Company does not unlawfully discriminate on the basis of race inclusive of traits historically associated with race (including, but not limited to, hair texture and protective hairstyles, such as braids, locks and twists), color, religion, sex (including pregnancy, childbirth, or related medical conditions), gender identity, gender expression, transgender status, national origin (including, in California, possession of a drivers license), ancestry, citizenship, age, physical or mental disability, height or weight, medical condition, family care status, military or veteran status, marital status, domestic partner status, sexual orientation, genetic information, exercise of reproductive rights, any other basis protected by local, state, or federal laws, or any combination of the above characteristics. When necessary, the Company also makes reasonable accommodations for disabled candidates and employees, including for candidates or employees who are disabled by pregnancy, childbirth, or related medical conditions.