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Machine Learning Internship Microsoft Jobs in Berkeley, CA

Atoms

Senior Machine Learning Engineer

San Francisco, CA · On-site

$144K - $190K/yr

Required : • 4+ years of non-internship professional MLE experience. • Deep expertise in ... • Strong background in machine learning engineering with a focus on model optimization ...

BigHat

Principal, Machine Learning Scientist

San Mateo, CA · On-site

$254 - $290/hr

Principal, Machine Learning Scientist Department: DS/ML (Data Science/Machine Learning) Employment ... and interns. * Help set strategy for future ML research, driven by a strong high-level ...

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Machine Learning Internship Microsoft information

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How much do machine learning internship microsoft jobs pay per year?

As of Aug 7, 2026, the average yearly pay for machine learning internship microsoft in Berkeley, CA is $52,141.00, according to ZipRecruiter salary data. Most workers in this role earn between $39,800.00 and $56,300.00 per year, depending on experience, location, and employer.

What is a machine learning internship at Microsoft?

A Machine Learning Internship at Microsoft is a temporary position for students or recent graduates to gain hands-on experience working on real-world machine learning projects. Interns collaborate with experienced engineers and researchers to develop, test, and deploy machine learning models and solutions that impact Microsoft products and services. The internship typically involves working with large datasets, implementing algorithms, and contributing to team goals while learning about cutting-edge AI technologies. Interns also benefit from mentorship, networking opportunities, and exposure to the latest industry practices.

What types of projects do interns typically work on during a machine learning internship at Microsoft?

As a Machine Learning intern at Microsoft, you can expect to work on impactful, real-world projects that contribute to ongoing products or research initiatives. Interns often collaborate with data scientists, software engineers, and product teams to develop, test, and refine machine learning models for applications such as natural language processing, computer vision, or recommendation systems. You'll likely participate in code reviews, present your findings, and receive mentorship from experienced professionals, all within a collaborative and innovative environment. These projects not only enhance technical skills but also provide valuable exposure to large-scale, industry-leading systems.

What is the difference between Machine Learning Internship Microsoft vs Data Science Internship Microsoft?

AspectMachine Learning Internship MicrosoftData Science Internship Microsoft
Required SkillsProgramming, ML algorithms, Python, TensorFlowStatistics, data analysis, Python, SQL
Work EnvironmentResearch and development teams focused on ML modelsData analysis and visualization teams
Industry UsageAI and ML product developmentBusiness insights and data-driven decision making

Both internships are highly competitive roles at Microsoft, often requiring programming skills and relevant coursework. Machine Learning Internships focus on developing and deploying ML models, while Data Science Internships emphasize analyzing data to generate insights. Candidates should review the specific role descriptions to align their skills accordingly.

What are the key skills and qualifications needed to thrive as a machine learning intern at Microsoft, and why are they important?

To thrive as a Machine Learning Intern at Microsoft, you need a solid foundation in mathematics, programming (especially Python), and machine learning concepts, typically supported by coursework or related projects. Familiarity with tools such as TensorFlow, PyTorch, scikit-learn, and experience using cloud platforms like Azure are often expected. Strong problem-solving skills, curiosity, and effective communication help you collaborate with team members and present findings. These skills are crucial for contributing to innovative projects and translating complex data-driven insights into impactful solutions within a dynamic tech environment.
What are popular job titles related to Machine Learning Internship Microsoft jobs in Berkeley, CA? For Machine Learning Internship Microsoft jobs in Berkeley, CA, the most frequently searched job titles are:
What job categories do people searching Machine Learning Internship Microsoft jobs in Berkeley, CA look for? The top searched job categories for Machine Learning Internship Microsoft jobs in Berkeley, CA are:
What cities near Berkeley, CA are hiring for Machine Learning Internship Microsoft jobs? Cities near Berkeley, CA with the most Machine Learning Internship Microsoft job openings:
Machine Learning Internship Microsoft jobs near you
Infographic showing various Machine Learning Internship Microsoft job openings in Berkeley, CA as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $52,141 per year, or $25.1 per hour.

Senior Machine Learning Engineer

ATOMS Careers page

San Francisco, CA • On-site

$144K - $190K/yr

Full-time

Medical, Dental, Vision, Life, Retirement

Re-posted 12 days ago

Job description

Who we are
Atoms is building the machines that power the next era of progress.
Over the last decade, software has transformed the digital world. But the physical world, where food is made, minerals are mined, goods are moved, and industries are run, remains far less intelligent, far less efficient, and far more constrained. We're changing that.
Atoms builds Physical AI- real-world robots for the industries that move civilization forward, starting with food, mining, and transport. Our systems are designed to understand, predict, and control the real world with precision, turning complex physical operations into something more reliable, more scalable, and more productive.
This work requires more than robotics. It requires deep integration across hardware, software, AI, operations, manufacturing, and real estate. We don't just build machines in a lab. We deploy them into real environments, operate them, learn from them, and improve them until they work at scale.
We are roboticists, engineers, operators, and builders. We believe the next great technology companies will not only transform information, but the physical systems that shape everyday life.
If you want to work on hard problems with real-world impact, join us.
What we're seeking
A visionary Machine Learning Engineer to join our founding team who will help bridge the gap between high-level AI research and real-world physical actuation for our next-generation autonomous transport platforms. We are actively hiring across three core specialized subcategories: AI Research, Post-Training Optimization, and Data Engineering.
AI Researcher (World Models & VLA)
What you'll do
  • Research and develop cutting edge RL and distillation techniques for trajectory planning
  • Integrate emerging research from the broader AI community, identifying and prototyping the most promising solutions
  • Design and deploy end-to-end multimodal models that translate real-time visual perception and high-level behavioral goals into physical vehicle actuation
  • Develop interactive world models from raw multi-sensor logs, allowing the team to re-simulate events and query what a vehicle would see if it altered its trajectory
  • Ensure core autonomous driving models can seamlessly adapt to novel urban environments and edge cases
  • Partner with validation and QA teams to run model releases through rigorous simulated scenarios, detecting regressions and identifying systemic performance bottlenecks.
What we're looking for
  • 4+ years of non-internship professional MLE experience.
  • Deep expertise in applying AI Transformers to robotics, physical actuation, or spatial-temporal data.
  • Proven track record designing or training multimodal systems, large-scale VLA models, or generative Diffusion models.
  • Strong background in Sensor Fusion, combining inputs from Cameras, LiDAR, and Radar.
  • Fluency in PyTorch or JAX for training large-scale models.
  • Experience with multi-task learning, Birds-Eye-View (BEV) frameworks, representation learning, or data tokenization is highly preferred.
  • Proficiency in Python and familiarity with C++.
Post-Training & Optimization
What you'll do
  • Own the post-training lifecycle by distilling, quantizing, and optimizing massive models to run with low latency on vehicle edge hardware.
  • Profile real-time inference pipelines to identify and eliminate CPU, GPU, and memory bandwidth bottlenecks on the vehicle.
  • Work with low-level hardware, electrical, and firmware teams to iterate on custom carrier boards, sensor interfaces, and GPUs on edge devices.
  • Benchmark and deploy models utilizing hardware-accelerated runtimes (e.g., TensorRT, CUDA) to minimize inference times under strict constraints.
What we're looking for
  • 4+ years of non-internship professional MLE experience.
  • Strong background in machine learning engineering with a focus on model optimization, distillation, and deployment.
  • Hands-on experience optimizing models for edge deployment or custom embedded GPU targets.
  • Deep understanding of profiling tools and debugging resource constraints across CPU/GPU boundaries.
  • Experience with modern deep learning frameworks (PyTorch or JAX) and runtime compilation.
  • Robust programming skills in Python and C++.
  • Familiarity with low-level camera/sensor interfaces and robotics hardware is a significant plus.
Data & Long-Tail Scenarios
What you'll do
  • Architect automated pipelines to ingest, filter, and identify rare, high-value, and long-tail scenarios out of multi-petabyte multi-sensor datasets.
  • Target and extract complex structural corner cases from real-world driving logs to continuously feed, challenge, and improve our end-to-end behavior models.
  • Iterate closely with QA, testing, and simulation teams to transform ambiguous real-world anomalies into concrete data blocks for simulation testing.
  • Implement programmatic data curation, active learning strategies, and statistical quality metrics to optimize the signal-to-noise ratio of our training pipelines.
What we're looking for
  • 4+ years of non-internship professional MLE experience.
  • Professional experience building data curation pipelines, active learning workflows, or data mining architectures for massive physical datasets.
  • Strong familiarity with robotics data structures and spatial frameworks, including Birds-Eye-View (BEV) or spatial tokenization.
  • Experience processing and structuring raw data from Cameras, LiDAR, and Radar.
  • Expert-level proficiency in Python, data engineering frameworks, and PyTorch/JAX.
  • Exceptional ability to navigate, structure, and derive signal from highly ambiguous, messy, or undefined real-world data distributions.

Why join us
At Atoms, you'll work on one of the defining challenges of our time - bringing automation into the physical world to drive real, lasting impact. We exist to uncover valuable unknown truths and turn them into progress, which means constantly pushing beyond what's known and building what doesn't yet exist. The work is ambitious and often challenging, but it's grounded in a shared sense of purpose and a team committed to seeing it through together. Our work only matters if it serves others, and we know that meaningful progress depends on the trust of the people we serve and the strength of our team-so we invest in both, creating an environment where you can do your best work and grow.
What else you need to know
This role is based in our San Francisco office. Atoms is a company driven by invention and continuous change - we are constantly reimagining our industries, building new products, and refining how we operate. We do our best work together. That's why all of our office-based teams work onsite, five days a week.
The base salary range for this role is $208,000 - $263,500
Actual compensation will be determined on an individual basis and may vary depending on experience, skills, and qualifications.
Base salary is just one part of your total rewards package. You may also be eligible for equity awards and an annual performance-based bonus.
Benefits Summary (USA Full-Time Exempt Employees):
  • Medical, Dental, Vision, Disability, and Life Insurance
  • Flexible Spending Account / Health Savings Account Options
  • 401(k)
  • Equity
  • Sick Time, Unlimited Flexible Time Off, and Paid Holidays
  • Paid Parental Leave
  • Pre-Tax Commuter Benefit Plan
  • Team lunch in our SoMa office every Tuesday and Thursday

Benefits are subject to change at the company's discretion.
Atoms accepts applications on an ongoing basis.

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