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Remote Machine Learning Jobs in Atherton, CA (NOW HIRING)

Higgsfield

Machine Learning Engineer, Ads

San Francisco, CA · Remote

$165 - $230K/hr

About the role We're looking for exceptional Machine Learning Engineers focused on Ads to help take Higgsfield's advertising platform to the next level. You'll work at the intersection of large-scale ...

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All JobsMachine Learning JobsRemote Machine Learning JobsRemote Machine Learning Jobs in Atherton, CA

Remote Machine Learning information

See Atherton, CA salary details

$30.9K

$51.6K

$106.7K

How much do remote machine learning jobs pay per year?

As of Sep 2, 2026, the average yearly pay for remote machine learning in Atherton, CA is $51,611.00, according to ZipRecruiter salary data. Most workers in this role earn between $39,400.00 and $55,800.00 per year, depending on experience, location, and employer.

What is a remote machine learning job?

A remote machine learning job involves working with algorithms, data, and models to develop predictive systems or automate tasks, all while working from a location outside of a traditional office setting. Professionals in this role use techniques from statistics and computer science to analyze data, train machine learning models, and deploy solutions for real-world applications. Remote machine learning jobs can span various industries, including technology, healthcare, finance, and e-commerce. These roles typically require strong programming skills, knowledge of machine learning frameworks, and the ability to communicate findings effectively with team members or stakeholders. Working remotely offers flexibility, but also requires discipline and self-motivation to succeed.

What are some effective strategies for collaborating with team members while working remotely as a machine learning engineer?

Collaboration in a remote Machine Learning role often relies on clear communication through digital tools such as Slack, Zoom, and project management platforms like Jira or Asana. Regular check-ins and stand-up meetings help keep everyone aligned on project goals and timelines. Sharing code and models via version control systems (like Git) and using collaborative notebooks (such as JupyterHub or Google Colab) are also common practices. Building strong documentation habits and proactively seeking feedback can help ensure smooth teamwork and project success, even across different time zones.

What is the difference between Remote Machine Learning vs Data Scientist?

AspectRemote Machine LearningData Scientist
Required CredentialsBachelor's/Master's in CS, ML certificationsBachelor's/Master's in CS, Statistics, or related field
Work EnvironmentRemote, collaborative teams, tech companiesRemote or on-site, diverse industries, analytics focus
Industry UsageTech, AI startups, researchFinance, healthcare, e-commerce, tech
Search & Comparison IntentOften compared for technical roles in AI/MLBroader data analysis roles, but overlapping skills

Remote Machine Learning specialists focus on developing algorithms and models primarily in tech environments, often requiring advanced programming and ML knowledge. Data Scientists analyze data to extract insights, sometimes utilizing ML techniques. While both roles share skills and credentials, Remote Machine Learning emphasizes model development, whereas Data Scientists focus on data analysis and interpretation.

More about Remote Machine Learning jobs

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What cities near Atherton, CA are hiring for Remote Machine Learning jobs?

Cities near Atherton, CA with the most Remote Machine Learning job openings:

Remote Machine Learning jobs near you
Infographic showing various Remote Machine Learning job openings in Atherton, CA as of August 2026, with employment types broken down into 1% As Needed, 63% Full Time, 33% Part Time, and 3% Contract. Highlights an 83% Physical, 3% Hybrid, and 14% Remote job distribution, with an average salary of $51,611 per year, or $24.8 per hour.

Staff Machine Learning Engineer, Applied Research

Pinterest

San Francisco, CA • On-site, Remote

$241K/yr

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

At Pinterest Labs, you'll work on tackling new challenges in machine learning and multi-modal large language models along with a world-class team of research scientists, and machine learning engineers. You'll conduct research that can be applied across Pinterest engineering teams and engage in external collaborations and mentoring, while also performing research in any of the following areas: natural language processing (NLP) and reasoning capability, computer vision for multi-modality, graph neural network, inclusive and responsible AI, reinforcement learning, user modeling, and recommender systems.

What you'll do:

  • Contribute to cutting-edge research in machine learning and LLM that can be applied to Pinterest problems, especially search agent, recommendation agent, reason and planning agent
  • Collect, analyze, and synthesize findings from data and build intelligent data-driven model
  • Write clean, efficient, and sustainable code
  • Use machine learning, natural language processing, and graph analysis to solve modeling and ranking problems across growth, discovery, ads and search
  • Scope and independently solve moderately complex problems

What we're looking for:

  • MS/PhD in Computer Science, ML, NLP, Statistics, Information Sciences or related field
  • 6+ years of industry experience
  • Experience in machine learning/information retrieval 
  • Mastery of at least one systems languages (Java, C++, Python) or one ML framework (Tensorflow, Pytorch, MLFlow)
  • Experience in research and in solving analytical problems
  • Cross-functional collaborator and strong communicator
  • Comfortable solving ambiguous problems and adapting to a dynamic environment

In-Office Requirement Statement:

  • We let the type of work you do guide the collaboration style. That means we're not always working in an office, but we continue to gather for key moments of collaboration and connection.
  • This role will need to be in the office for in-person collaboration 1-2 times/quarter and therefore can be situated anywhere in the country.

Relocation Statement:

  • This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.

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