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Internship Full Stack Machine Learning Engineer Jobs in California

We are building an AI-driven simulation software stack for engineering and manufacturing across ... Enhanced parental leave - 3 months full pay paternity and 6 months full pay maternity leave, to ...

As a Machine Learning Engineer, you will play a central role in translating cutting-edge machine ... Familiarity with data processing stacks such as Spark and Airflow. * Experience with multi-node GPU ...

As a Machine Learning Engineer, you will play a central role in translating cutting-edge machine ... Familiarity with data processing stacks such as Spark and Airflow. * Experience with multi-node GPU ...

We are looking for developers who are excited about staying at the forefront of deep learning ... the machine learning stack, and who move fast and take ownership of their projects. Our ideal ...

As a Full-stack AI Developer, will bridge the gap between AI research and production-ready ... Implement machine learning models (using frameworks like PyTorch, TensorFlow, or scikit-learn) into ...

Advantest is seeking a motivated Junior Machine Learning Engineer to support the development of ... Hands-on experience with ML modeling via coursework, internships, or independent projects.

Currently, We are looking for entry-level software programmers, Java Full stack developers, Python/Java developers, Data analysts/ Data Scientists, Machine Learning engineers for full time positions ...

... stack. * Collaborate with cross-functional teams to define machine learning use cases and evaluate ... D. in Electrical Engineering, Computer Science, or a related field. * Minimum of 3 years of ...

Currently, We are looking for entry-level software programmers, Java Full stack developers, Python/Java developers, Data analysts/ Data Scientists, Machine Learning engineers for full time positions ...

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Internship Full Stack Machine Learning Engineer information

What are the key skills and qualifications needed to thrive as an Internship Full Stack Machine Learning Engineer, and why are they important?

To succeed as an Internship Full Stack Machine Learning Engineer, you need a solid understanding of programming (Python, JavaScript), basic machine learning concepts, and foundational knowledge in computer science or a related field. Familiarity with frameworks like TensorFlow or PyTorch, web development tools (React, Node.js), and version control systems like Git is typically expected. Strong problem-solving abilities, collaboration skills, and a willingness to learn set exceptional interns apart. These skills enable interns to contribute effectively to both model development and deployment, bridging the gap between data science and software engineering in real-world applications.

What is an Internship Full Stack Machine Learning Engineer?

An Internship Full Stack Machine Learning Engineer is a student or early-career professional who supports both the development of machine learning models and the integration of these models into full-stack applications. This role typically involves working on data preprocessing, building and training machine learning algorithms, and deploying these models within web or mobile applications. Interns in this field gain experience in both backend and frontend technologies, as well as in machine learning frameworks and tools. The position is ideal for those seeking hands-on experience in applying AI solutions within real-world products.

What types of projects and responsibilities can I expect as an Internship Full Stack Machine Learning Engineer?

As an Internship Full Stack Machine Learning Engineer, you can expect to work on end-to-end machine learning projects that involve both model development and integration into web or cloud applications. This may include tasks like cleaning and preparing datasets, building and testing machine learning models, developing APIs to serve predictions, and collaborating with front-end developers to deliver user-facing features. Interns often work closely with data scientists, software engineers, and product managers, gaining exposure to the full development lifecycle. These experiences help build both technical and teamwork skills, laying a strong foundation for a future career in the field.

What is the difference between Internship Full Stack Machine Learning Engineer vs Software Developer Intern?

AspectInternship Full Stack Machine Learning EngineerSoftware Developer Intern
Required SkillsKnowledge of machine learning, programming (Python, JavaScript), full stack development, data handlingProficiency in programming languages (Java, Python, JavaScript), software development, basic algorithms
Work EnvironmentCollaborates on ML models, data pipelines, backend and frontend developmentFocuses on application development, coding, debugging, and testing
Industry UsageUsed in AI-driven companies, tech startups, data science teamsCommon in software firms, app development companies, tech startups

The Internship Full Stack Machine Learning Engineer role emphasizes working with machine learning models and data-driven applications, combining full stack development skills with AI expertise. In contrast, a Software Developer Intern focuses more on traditional software development tasks like coding and debugging. Both roles are valuable entry points in tech, but they target different skill sets and project types.

What are the most commonly searched types of Full Stack Machine Learning Engineer jobs in California? The most popular types of Full Stack Machine Learning Engineer jobs in California are:
What job categories do people searching Internship Full Stack Machine Learning Engineer jobs in California look for? The top searched job categories for Internship Full Stack Machine Learning Engineer jobs in California are:
What cities in California are hiring for Internship Full Stack Machine Learning Engineer jobs? Cities in California with the most Internship Full Stack Machine Learning Engineer job openings:

Machine Learning Engineer

PhysicsX

San Francisco, CA โ€ข On-site

Full-time

Medical, Retirement, PTO

Posted 15 days ago


Job description

About us
PhysicsX is a deep-tech company with roots in numerical physics and Formula One, dedicated to accelerating hardware innovation at the speed of software.
We are building an AI-driven simulation software stack for engineering and manufacturing across advanced industries. By enabling high-fidelity, multi-physics simulation through AI inference across the entire engineering lifecycle, PhysicsX unlocks new levels of optimization and automation in design, manufacturing, and operations - empowering engineers to push the boundaries of possibility. Our customers include leading innovators in Aerospace & Defense, Materials, Energy, Semiconductors, and Automotive.
Note: We are currently recruiting for multiple positions, however please only apply for the role that best aligns with your skillset and career goals.
Who We're Looking For
As a Machine Learning Engineer in Delivery, you are a problem solver who stays anchored to impact. You are someone who can grasp advanced engineering concepts across multiple industries, and excel at working directly with customers (and often side-by-side with them on-site) to embed cutting-edge AI models into tools that are useful and used.
You've shipped ML systems end-to-end and at scale: you design, build and test reliable, scalable ML data pipelines; you know how to explore and manipulate 3D point-cloud and mesh data to enable geometry-aware modelling; you select the right libraries, frameworks and tools. Working at the intersection of data science and software engineering, you translate R&D and project outputs into reusable libraries, tooling and products.
With at least 2 years industry experience (post Masters or PhD) in a commercial, non-research environment. You're truly excited about taking ownership of complex work streams and guiding teams to success, while continuously improving the systems and solutions you work on to ensure they are practical, impactful and meet the evolving needs of our customers.
We have hybrid offices in London, New York, and Singapore; this role is remote based in the San Francisco area.
This Role
As a Machine Learning Engineer, you'll work closely with our Data Scientists, Simulation Engineers, and customers to understand and define the engineering and physics challenges we are solving. You will iterate with customers and use your influence to drive decisions around reliable deployment with measurable outcomes.
What you will do
  • Work closely with our simulation engineers, data scientists and customers to develop an understanding of the physics and engineering challenges we are solving
  • Design, build and test data pipelines for machine learning that are reliable, scalable and easily deployable
  • Explore and manipulate 3D point cloud & mesh data
  • Own the delivery of technical workstreams
  • Create analytics environments and resources in the cloud or on premise, spanning data engineering and science
  • Identify the best libraries, frameworks and tools for a given task, make product design decisions to set us up for success
  • Work at the intersection of data science and software engineering to translate the results of our R&D and projects into re-usable libraries, tooling and products
  • Continuously apply and improve engineering best practices and standards and coach your colleagues in their adoption

You'll also have the opportunity to travel to customer sites in North America, Europe, Asia, Oceania, for an average of 3-4 weeks per quarter, where you'll collaborate closely with customers to build solutions on-site.
What you bring to the table
  • Experience applying Machine learning methods (including 3D graph/point cloud deep learning methods) to real-world engineering applications, with a focus on driving measurable impact in industry settings.
  • Experience in ML/Computational statistics/Modelling use-cases in industrial settings (for example supply chain optimisation or manufacturing processes) is encouraged.
  • A track record of scoping and delivering projects in a customer facing role
  • 2+ years' experience in a data-driven role, with exposure to software engineering concepts and best practices (e.g., versioning, testing, CI/CD, API design, MLOps)
  • Building machine learning models and pipelines in Python, using common libraries and frameworks (e.g., TensorFlow, MLFlow)
  • Distributed computing frameworks (e.g., Spark, Dask)
  • Cloud platforms (e.g., AWS, Azure, GCP) and HP computing
  • Containerization and orchestration (Docker, Kubernetes)
  • Strong problem-solving skills and the ability to analyse issues, identify causes, and recommend solutions quickly
  • Excellent collaboration and communication skills - with teams and customers alike
  • A background in Physics, Engineering, or equivalent
Our delivery teams drive innovation to turn AI models into practical solutions - read our blog to learn more about how you'll contribute to this exciting journey!
What we offer
Build what actually matters
Help shape an AI-native engineering company at a formative stage, tackling problems that genuinely matter for industry and society. This is work with real-world impact - and something you can be proud to stand behind.
Learn alongside exceptional people
Work with a high-caliber, collaborative team of engineers, scientists, and operators who care deeply about doing great work, and about helping each other get better. We come from diverse backgrounds, but we share a commitment to operating at the highest level and addressing some of the most complex challenges out there. If you're ambitious, thoughtful, and driven by impact, you'll feel at home.
Influence over hierarchy
We operate with a flat structure: good ideas win - wherever they come from. Questioning assumptions and challenging the status quo isn't just welcomed, it's expected.
And it doesn't stop there ...
Equity options - share meaningfully in the company you're helping to build.
5% contribution to 401(k) - build long-term security with a strong retirement plan.
Private health insurance - comprehensive cover for you, offering total peace of mind.
Enhanced parental leave - 3 months full pay paternity and 6 months full pay maternity leave, to provide extra flexibility during the moments that matter most.
20 days of Annual Leave (+ Public Holidays) - because taking time to rest matters.
Personal development - dedicated support for learning, development, and leveling up over time.
Gympass / Wellhub (subsidized) - for you and up to 3 family members, supporting both physical and mental wellbeing.
Flexible Spending Account (FSA) - set aside pre-tax dollars for eligible healthcare expenses.
Watch this space, we're continuing to build this as we grow...
Salary range:
$150,000 - $190,000 depending on experience
Seniority will be assessed throughout our interview process
We value diversity and are committed to equal employment opportunity regardless of sex, race, religion, ethnicity, nationality, disability, age, sexual orientation or gender identity. We strongly encourage individuals from groups traditionally underrepresented in tech to apply. To help make a change, we sponsor bright women from disadvantaged backgrounds through their university degrees in science and mathematics.
We collect diversity and inclusion data solely for the purpose of monitoring the effectiveness of our equal opportunities policies and ensuring compliance with UK employment and equality legislation. This information is confidential, used only in aggregate form, and will not influence the outcome of your application.