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Phd Computer Science Jobs in Milpitas, CA (NOW HIRING)

Dexmate

Research Intern, PhD (AI, Robotics)

Fremont, CA · On-site

Currently enrolled in a PhD degree in Computer Science, Robotics, Electrical Engineering, Mechanical Engineering, etc., or related technical field. * Passionate about working with robots. * Research ...

(unknown company)

Data Scientist

Sunnyvale, CA · On-site

Sunnyvale Duration: 6 Months + Minimum Qualifications - PhD in Computer Science, Statistics or related field; OR a Master's degree or equivalent in Computer Science, Statistics or related field and 2 ...

(unknown company)

Data Scientist

Sunnyvale, CA · On-site

Sunnyvale Duration: 6 Months + Minimum Qualifications - PhD in Computer Science, Statistics or related field; OR a Master's degree or equivalent in Computer Science, Statistics or related field and 2 ...

Qualcomm

CPU Integration CAD Engineer

Santa Clara, CA · On-site

$167K - $250K/yr

OR PhD in Electrical Engineering, Computer Engineering, Computer Science, or related field and 2+ years of Hardware Engineering, Software Engineering, Electrical Engineering, Systems Engineering, or ...

SETI Institute

Optical Scientist

Mountain View, CA · On-site

$80 - $100/hr

MS or PhD in Optical Science, Astronomy, Electrical Engineering, Physics, or related field. * 1-4 ... Perform desk-based computer tasks for extended periods of time. * Assemble and manipulate optical ...

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$96.9K

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How much do phd computer science jobs pay per year?

As of Sep 9, 2026, the average yearly pay for phd computer science in Milpitas, CA is $96,853.00, according to ZipRecruiter salary data. Most workers in this role earn between $90,300.00 and $109,000.00 per year, depending on experience, location, and employer.

What is a PhD in computer science?

A PhD in Computer Science is the highest academic degree in the field, focused on advanced research and the creation of new knowledge in computing. It typically involves several years of coursework followed by original research culminating in a dissertation. Graduates often pursue careers in academia, research, or advanced industry roles that require deep technical expertise and problem-solving skills.

What are the key skills and qualifications needed to thrive as a PhD in computer science?

To thrive as a PhD in Computer Science, you need advanced expertise in algorithms, programming, and research methodologies, typically supported by a doctoral degree in computer science or a related field. Mastery of programming languages (such as Python, Java, or C++), data analysis tools, and familiarity with version control systems like Git are commonly required, along with experience in publishing academic research. Critical thinking, problem-solving, strong written and verbal communication, and perseverance are vital soft skills for success in research and collaboration. These skills and qualifications are essential for making significant contributions to the field, driving innovation, and effectively sharing knowledge with the academic and professional community.

What are some common challenges faced by PhD computer science students during their research?

PhD Computer Science students often encounter challenges such as defining a clear and impactful research problem, managing long-term projects with limited guidance, and coping with the pressure to publish in top-tier conferences or journals. Balancing coursework, teaching responsibilities, and research can also be demanding. Effective time management, networking with peers and mentors, and seeking regular feedback can help students navigate these challenges and achieve their academic goals.

Is a PhD worth it for computer science?

A PhD in computer science can lead to careers in research, academia, or specialized industry roles, often requiring advanced skills in algorithms, data analysis, and programming. While it offers opportunities for high-level positions and expertise, it typically involves several years of study and may not be necessary for most industry jobs, which often value practical experience and skills. The decision depends on career goals and the desire for research or teaching roles.

What can I do after a PhD in computer science?

A PhD in computer science prepares individuals for careers in academia, research, or advanced industry roles such as data scientist, machine learning engineer, or software architect. Graduates often pursue postdoctoral research, work in R&D departments, or obtain certifications in specialized tools and programming languages to enhance their expertise.

What jobs can I get with a PhD in computer science?

A PhD in computer science qualifies individuals for advanced roles such as research scientist, data scientist, machine learning engineer, or university professor. These positions often require strong analytical skills, programming expertise, and knowledge of algorithms, data structures, and AI tools. Graduates may work in academia, industry research labs, or technology companies focusing on innovation and development.

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What job categories do people searching Phd Computer Science jobs in Milpitas, CA look for?

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Cities near Milpitas, CA with the most Phd Computer Science job openings:

Phd Computer Science jobs near you
Infographic showing various Phd Computer Science job openings in Milpitas, CA as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, 3% Contract, and 1% Nights. Highlights an 80% Physical, 1% Hybrid, and 19% Remote job distribution, with an average salary of $96,853 per year, or $46.6 per hour.

Research Intern, PhD (AI, Robotics)

Fremont, CA • On-site

Dexmate
See more jobs at Dexmateexternal

Other

Re-posted 6 days ago

Job description

Robotics Ai Developer

Dexmate is building the foundation for physical AI — a unified platform that combines high-quality robotic hardware with a universal Physical AI OS, making robots as easy to build and deploy as software. Today, robotics is fragmented, slow, and closed: most builders are forced to reinvent the same stack again and again, and most ideas never make it past the prototype stage. We exist to change that. Our mission is to democratize robotics by lowering the barrier to entry, delivering a plug-and-play platform for developers, researchers, and enterprises, and cultivating an open ecosystem that accelerates the evolution of physical AI. If you want to help shape the next layer of human capability — and believe the future of robotics should be built together, not in isolation — we'd love to build it with you.

Responsibilities
  • Develop new algorithms and methods for training AI models for enhancing the robot dexterity.
  • Conduct cutting edge research across multiple disciplines (Robotics, RL/IL, control, perception, LLM, VLM, etc.).
  • Work with large-scale ML systems and large-scale model training/fine-tuning.
  • Design and implement state-of-the-art learning-based manipulation/navigation/control algorithms on real robots.
  • Work with other teams to develop a diverse set of robust manipulation skills for robots.
Qualifications
  • Currently enrolled in a PhD degree in Computer Science, Robotics, Electrical Engineering, Mechanical Engineering, etc., or related technical field.
  • Passionate about working with robots.
  • Research experience in embodied AI, robotics, computer vision, machine learning, human-AI interaction, and computer science.
  • Experience with deep learning frameworks such as PyTorch.
  • Must obtain work authorization in U.S. at the time of hire and maintain ongoing work authorization during employment.
  • Excellent analytical, problem-solving, and communication skills.
  • At least 2 years of experience conducting independent research.
  • Deep understanding of the SOTA robot learning techniques (reinforcement learning, imitation learning, etc.)
  • A track record of research excellence with your work published in top conferences and journals such as Science Robotics, IJRR, RSS, CoRL, ICRA, NeurIPS, ICML, ICLR, CVPR, etc.
  • Experienced with robot simulators such as Isaac Gym/ Isaac Sim/ SAPIEN/ MuJoCo/Drake, etc.
  • Experience setting up ML experiments and analyze their results.
  • Experience building systems based on machine learning and/or deep learning methods.

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