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Remote Machine Learning Postdoc Jobs in Santa Clara, CA

Machine Learning Engineer

Mountain View, CA · On-site +1

$117K - $152K/yr

We're looking for a Machine Learning Engineer to join our Offline Infrastructure team. This is an ... Mountain View, SF/Bay: $117,000 - $152,000 gross USD Bellevue, Seattle, NYC, Remote CA: $104,100 ...

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Remote Machine Learning Postdoc information

What is a remote machine learning postdoc?

A Remote Machine Learning Postdoc is a postdoctoral researcher specializing in machine learning who works predominantly or entirely from a location outside their host institution, often from home. Their work involves conducting advanced research, developing new algorithms, analyzing data, and publishing findings related to machine learning while collaborating virtually with faculty and research teams. This role is ideal for researchers seeking flexibility or those who cannot relocate but wish to contribute to academic or industrial research from a distance.

What are the key skills and qualifications needed to thrive as a remote machine learning postdoc?

A Remote Machine Learning Postdoc requires a PhD in computer science, statistics, or a related field, with expertise in machine learning algorithms, statistical modeling, and research methodologies. Proficiency in programming languages like Python or R, experience with machine learning frameworks such as TensorFlow or PyTorch, and familiarity with version control systems (e.g., Git) are typically necessary. Strong written and verbal communication, self-motivation, and collaboration skills are vital for remote research and effective teamwork. These capabilities enable impactful independent research, smooth collaboration across distributed teams, and the successful dissemination of findings to the wider scientific community.

What are some common challenges faced by remote machine learning postdocs when collaborating with research teams?

Remote machine learning postdocs often encounter challenges related to communication and coordination, especially when working across different time zones or with teams that have varying schedules. Effective collaboration usually requires proactive communication through virtual meetings, shared code repositories, and regular progress updates. Building rapport with colleagues and staying engaged with ongoing research discussions can take extra effort remotely, but leveraging collaborative tools and participating in virtual seminars or group chats can help bridge the gap. Being organized and self-motivated is key to ensuring productive contributions to the team’s research objectives.

What are the most commonly searched types of Machine Learning Postdoc jobs in Santa Clara, CA?

The most popular types of Machine Learning Postdoc jobs in Santa Clara, CA are:

What are popular job titles related to Remote Machine Learning Postdoc jobs in Santa Clara, CA?

For Remote Machine Learning Postdoc jobs in Santa Clara, CA, the most frequently searched job titles are:

What job categories do people searching Remote Machine Learning Postdoc jobs in Santa Clara, CA look for?

The top searched job categories for Remote Machine Learning Postdoc jobs in Santa Clara, CA are:

What cities near Santa Clara, CA are hiring for Remote Machine Learning Postdoc jobs?

Cities near Santa Clara, CA with the most Remote Machine Learning Postdoc job openings:

Heavy-Ion Physics and Scientific Machine Learning - Postdoctoral Researcher

LLNL

Livermore, CA • On-site, Remote

$123K/yr

Full-time

Retirement

Posted 7 days ago


Job description

Company Description

Join us and make YOUR mark on the World!

Lawrence Livermore National Laboratory (LLNL) has turned bold ideas into world-changing impact advancing science and technology to strengthen U.S. security and promote global stability. 

Our mission spans four critical national security areas nuclear deterrence, threat preparedness, energy security, and multi-domain defense empowering teams to take on the toughest challenges of today and tomorrow. With a culture built on innovation and operational excellence, LLNL is a place where your expertise can make a real impact.

Job Description

We have an opening for a Postdoctoral Researcher to contribute to experimental heavy-ion physics, detector development, and scientific machine learning within Lawrence Livermore National Laboratory's Particle Physics Group. You will play a leading role in the analysis of data from the sPHENIX experiment at Brookhaven National Laboratory and the ATLAS experiment at CERN, while contributing to DOE Office of Science Nuclear Physics (DOE-NP) and Genesis Mission-funded research milestones focused on advanced AI methods for nuclear physics. Research activities span precision measurements of jet quenching, ultra-peripheral collisions, detector performance studies, and the development of next-generation machine learning techniques for particle reconstruction and multimodal data analysis. This position is in the Particle Physics Group within the Nuclear and Chemical Sciences Division.

Depending on your assignment, this position may offer a hybrid schedule, blending in-person and virtual presence. You may have the flexibility to work from home one or more days per week. 

You will

  • Perform physics analyses using data from the ATLAS and sPHENIX experiments to study the quark-gluon plasma, jet quenching, and heavy-ion collisions.
  • Participate in detector operations, commissioning, calibration, performance studies, and data quality monitoring within the ATLAS and sPHENIX collaborations.
  • Develop reconstruction, simulation, and analysis software using modern C++, Python, ROOT, and HPC/Grid computing resources for processing multi-petabyte experimental datasets.
  • Develop and apply state-of-the-art artificial intelligence and scientific machine learning techniques for particle identification, jet reconstruction, and event interpretation.
  • Contribute to DOE-NP and Genesis-funded project milestones focused on multimodal learning, detector performance improvements, and scalable AI methods for experimental nuclear physics.
  • Present research at collaboration meetings, DOE reviews, workshops, and international conferences.
  • Publish results in leading peer-reviewed journals.
  • Collaborate with physicists, computer scientists, and applied mathematicians across LLNL and external institutions.
  • Perform other duties as assigned.
Qualifications
  • Ph.D. in Physics, Nuclear Physics, High Energy Physics or a closely related discipline.
  • Demonstrated research experience in experimental nuclear or particle physics.
  • Experience analyzing large scientific datasets using ROOT, Python, C++, or similar scientific software frameworks.
  • Experience developing scientific software in Linux environments using modern programming practices.
  • Experience with statistical analysis and uncertainty quantification.
  • Excellent written and verbal communication skills, including publications and scientific presentations.
  • Ability to work effectively in large international collaborations.

Qualifications We Desire

  • Experience with the ATLAS, sPHENIX, RHIC, LHC, CMS, ALICE, or STAR collider experiments.
  • Experience with jet physics, heavy-ion collisions, and detector performance studies.
  • Experience in scientific machine learning, deep learning, foundation models, or multimodal AI.
  • Experience with GPU programming, high-performance computing, distributed computing, or large-scale workflow management.
  • Experience developing reconstruction, simulation, or detector calibration software.
  • Familiarity with modern machine learning frameworks such as PyTorch and TensorFlow.

Pay Range

$123,048 Annually 

This is the lowest to highest salary we in good faith believe we would pay for this role at the time of this posting.  An employee's position within the salary range will be based on several factors including, but not limited to, specific competencies, relevant education, qualifications, certifications, experience, skills, seniority, geographic location, performance, and business or organizational needs.

Additional Information

#LI-Hybrid

Position Information

This is a Postdoctoral appointment with the possibility of extension to a maximum of three years, open to those who have been awarded a PhD at time of hire date.

Why Lawrence Livermore National Laboratory?

  • Included in 2026 Best Places to Work by Glassdoor!
  • Flexible Benefits Package
  • 401(k)
  • Relocation Assistance
  • Education Reimbursement Program
  • Flexible schedules (*depending on project needs)
  • Our values - visit https://www.llnl.gov/inclusion/our-values

Security Clearance

None required.  However, if your assignment is longer than 179 days cumulatively within a calendar year, you must go through the Personal Identity Verification process.  This process includes completing an online background investigation form and receiving approval of the background check.  

National Defense Authorization Act (NDAA)

The 2025 National Defense Authorization Act (NDAA), Section 3112, generally prohibits citizens of China, Russia, Iran and North Korea without dual US citizenship or legal permanent residence from accessing specific non-public areas of national security or nuclear weapons facilities.  The restrictions of NDAA Section 3112 apply to this position.  To be qualified for this position, Candidates must be eligible to access the Laboratory in compliance with Section 3112.

Pre-Employment Drug Test

External applicant(s) selected for this position must pass a post-offer, pre-employment drug test. This includes testing for use of marijuana as Federal Law applies to us as a Federal Contractor.

Wireless and Medical Devices

Per the Department of Energy (DOE), Lawrence Livermore National Laboratory must meet certain restrictions with the use and/or possession of mobile devices in Limited Areas. Depending on your job duties, you may be required to work in a Limited Area where you are not permitted to have a personal and/or laboratory mobile device in your possession.  This includes, but not limited to cell phones, tablets, fitness devices, wireless headphones, and other Bluetooth/wireless enabled devices.  

If you use a medical device, which pairs with a mobile device, you must still follow the rules concerning the mobile device in individual sections within Limited Areas.  Sensitive Compartmented Information Facilities require separate approval. Hearing aids without wireless capabilities or wireless that has been disabled are allowed in Limited Areas, Secure Space and Transit/Buffer Space within buildings.

How to identify fake job advertisements

Please be aware of recruitment scams where people or entities are misusing the name of Lawrence Livermore National Laboratory (LLNL) to post fake job advertisements. LLNL never extends an offer without a personal interview and will never charge a fee for joining our company. All current job openings are displayed on the Career Page under "Find Your Job" of our website. If you have encountered a job posting or have been approached with a job offer that you suspect may be fraudulent, we strongly recommend you do not respond.

To learn more about recruitment scams: https://www.llnl.gov/sites/www/files/2023-05/LLNL-Job-Fraud-Statement-Updated-4.26.23.pdf

Equal Employment Opportunity

We are an equal opportunity employer that is committed to providing all with a work environment free of discrimination and harassment. All qualified applicants will receive consideration for employment without regard to race, color, religion, marital status, national origin, ancestry, sex, sexual orientation, gender identity, disability, medical condition, pregnancy, protected veteran status, age, citizenship, or any other characteristic protected by applicable laws.

Reasonable Accommodation

Our goal is to create an accessible and inclusive experience for all candidates applying and interviewing at the Laboratory.  If you need a reasonable accommodation during the application or the recruiting process, please use our online form to submit a request. 

California Privacy Notice

The California Consumer Privacy Act (CCPA) grants privacy rights to all California residents. The law also entitles job applicants, employees, and non-employee workers to be notified of what personal information LLNL collects and for what purpose. The Employee Privacy Notice can be accessed here.