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Remote Machine Learning Postdoc Jobs in California

Staff Machine Learning Scientist

Brisbane, CA · On-site +1

$199K - $283K/yr

... remote. What you'll do: * Independently pursue cutting edge research in AI applied to biological ... postdoc or post-PhD industry experience achieving impactful results using relevant modeling ...

Own small to medium components of machine learning systems from technical designthrough ... Ability to work effectively in a remote environment using collaboration tools Preferred Experience ...

Own small to medium components of machine learning systems from technical designthrough ... Ability to work effectively in a remote environment using collaboration tools Preferred Experience ...

Machine Learning Engineer

San Francisco, CA · On-site +1

$164K - $266K/yr

What you'll do As a Machine Learning Engineer on the AI Platform team, you will design and build ... Employee divides their time between in-office and remote work. Access to an office location is ...

$139K - $168K/yr

At Poe, we use Machine Learning in various parts of the product - bot routing, agent flow, code ... LI-SS2 LI-REMOTE

$139K - $168K/yr

At Poe, we use Machine Learning in various parts of the product - bot routing, agent flow, code ... LI-SS2 LI-REMOTE

$139K - $168K/yr

At Poe, we use Machine Learning in various parts of the product - bot routing, agent flow, code ... LI-SS2 LI-REMOTE

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Remote Machine Learning Postdoc information

Is ML a high paying job?

Machine learning postdoctoral positions are generally well-paid compared to many academic roles, with salaries often ranging from $60,000 to over $100,000 annually depending on experience, location, and funding. These roles typically require strong programming skills in Python or R and knowledge of algorithms and data analysis, which can contribute to higher compensation levels.

Is a PhD in ML worth it?

A PhD in machine learning can enhance qualifications for a remote machine learning postdoc position, often leading to higher-level research opportunities and increased earning potential. However, it requires significant time investment and may not be necessary for industry roles that value practical skills and experience with tools like Python and TensorFlow. The decision depends on career goals and the specific requirements of the desired position.

What are the key skills and qualifications needed to thrive as a Remote Machine Learning Postdoc, and why are they important?

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.

Is a postdoc harder than a PhD?

A remote machine learning postdoc typically involves more specialized research, higher expectations for independence, and often requires advanced skills in programming and data analysis. While a PhD focuses on completing a dissertation and gaining foundational expertise, a postdoc emphasizes producing publishable research and may involve longer hours and greater responsibility, making it generally more demanding in terms of research output and expertise. However, the difficulty varies based on individual experience and research environment.

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.

Do you need H-1B for postdoc?

A remote machine learning postdoctoral position typically does not require H-1B sponsorship if the candidate is already authorized to work in the country, such as through a visa or citizenship. However, international candidates may need H-1B or other work visas depending on the employer and local immigration laws. Employers often sponsor visas for postdocs to comply with legal requirements and facilitate employment.

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 California? The most popular types of Machine Learning Postdoc jobs in California are:
What job categories do people searching Remote Machine Learning Postdoc jobs in California look for? The top searched job categories for Remote Machine Learning Postdoc jobs in California are:
What cities in California are hiring for Remote Machine Learning Postdoc jobs? Cities in California with the most Remote Machine Learning Postdoc job openings:
Infographic showing various Remote Machine Learning Postdoc job openings in California as of July 2026, with employment types broken down into 1% As Needed, 71% Full Time, 25% Part Time, 1% Temporary, and 2% Contract. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution.

Machine Learning Technical Lead, Artificial Intelligence (AI) Required, Work From Home

Ginas Tech Jobs

San Francisco, CA • Remote

Full-time

Medical, Dental, Vision, PTO

Posted 17 days ago


Job description

Job Description

Machine Learning Technical Lead, Artificial Intelligence (AI) Required, Work From Home

As Machine Learning Technical Lead, you own the execution layer of intelligence.  You will translate research direction into reliable, scalable, production-grade ML systems.  This role sits at the intersection of research, infrastructure, and product.  You will be responsible for making models trainable, deployable, observable, and performant under real-world constraints.  This position is 100% Remote.

Machine Learning Technical Lead Responsibilities:

- Own end-to-end ML system execution:  data pipelines, training workflows, evaluation systems, inference architecture, and deployment.

- Fine-tune and adapt models using state-of-the-art methods such as LoRA, QLoRA, SFT, DPO, and distillation.

- Architect and operate scalable inference systems, balancing latency, cost, and reliability.

- Design and maintain data systems for high-quality synthetic and real-world training data.

- Implement evaluation pipelines covering performance, robustness, safety, and bias, in partnership with research leadership.

- Own production deployment, including GPU optimization, memory efficiency, latency reduction, and scaling policies.

- Collaborate closely with application engineering to integrate ML systems cleanly into backend, mobile, and desktop products.

- Make pragmatic trade-offs and ship improvements quickly, learning from real usage.

- Work under real production constraints: latency, cost, reliability, and safety

Machine Learning Technical Lead Outcomes:

- Research and models reliably translate into production-ready solutions with clear performance and quality targets.

- ML pipelines, training loops, and inference systems are stable, efficient, and maintainable.

- Production issues are detected, debugged, and resolved quickly, minimizing user impact.

- Team members are supported, aligned, and able to deliver high-impact ML work with minimal friction.

- Iterations on models and systems are measurable, safe, and improve user experience over time.

Qualifications

Machine Learning Technical Lead Qualifications:

- Experience building or shipping real Machine Learning systems used by people, not just demos.

- Artificial Intelligence (AI) experience required.

- Experience working with large models and understanding their failure modes.

- Experience writing strong, production-grade code.

- You are self-directed, pragmatic, and take full ownership of outcomes.

- You communicate clearly and collaborate well in small, high-trust teams.

- Tech Stack:  GPU-based training and inference system, JAX, Python, and PyTorch.

Benefits include medical insurance, Dental, Vision, Savings Plan Options, PTO, etc.

Keywords:  San Francisco CA Jobs, Machine Learning Technical Lead, AI, Artificial Intelligence, Distillation, DPO, GPU Optimization, JAX, LoRA, Machine Learning, Python, PyTorch, QLoRA, SFT, Technical Lead, Work From Home, Remote, California Recruiters, IT Jobs, California Recruiting

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Additional Information

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