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Remote Embedded Machine Learning Jobs in San Francisco, CA

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Remote Embedded Machine Learning information

See San Francisco, CA salary details

$82.5K

$180.7K

$205K

How much do remote embedded machine learning jobs pay per year?

As of Aug 23, 2026, the average yearly pay for remote embedded machine learning in San Francisco, CA is $180,712.00, according to ZipRecruiter salary data. Most workers in this role earn between $154,900.00 and $203,800.00 per year, depending on experience, location, and employer.

What is a remote embedded machine learning engineer?

A Remote Embedded Machine Learning Engineer is a professional who develops and deploys machine learning models on embedded systems like microcontrollers, IoT devices, and edge hardware, all while working remotely. Their work involves optimizing algorithms to run efficiently on devices with limited computing power, memory, and battery life. These engineers typically use frameworks such as TensorFlow Lite or TinyML to design intelligent features that operate directly on hardware, enabling real-time decision-making without relying heavily on cloud connectivity. They collaborate with cross-functional teams and often troubleshoot both software and hardware issues from a remote location.

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

To thrive as a Remote Embedded Machine Learning Engineer, you need a solid background in embedded systems, machine learning algorithms, and programming languages like C/C++ and Python, often supported by a degree in computer science, electrical engineering, or related fields. Familiarity with microcontrollers, edge AI frameworks (such as TensorFlow Lite or Edge Impulse), and version control systems is typically required. Strong problem-solving skills, effective communication, and self-motivation are essential soft skills for collaborating remotely and troubleshooting complex issues. These skills ensure successful deployment of intelligent solutions on resource-constrained devices and effective teamwork in distributed environments.

What are some common challenges faced by remote embedded machine learning engineers, and how can they be addressed?

Remote Embedded Machine Learning Engineers often encounter challenges related to hardware access, debugging embedded devices remotely, and collaborating with cross-functional teams across time zones. To address these, it's important to set up robust remote development environments, use simulation tools when physical hardware isn't available, and establish clear communication channels for effective teamwork. Regular virtual meetings and detailed documentation also help ensure alignment and smooth progress, despite the remote nature of the work.

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

AspectRemote Embedded Machine LearningRemote Data Scientist
Required CredentialsBachelor's or Master's in Computer Science, Electrical Engineering, or related fields; experience with embedded systems and ML frameworksBachelor's or Master's in Data Science, Statistics, or related fields; proficiency in data analysis and ML algorithms
Work EnvironmentEmbedded hardware devices, IoT systems, real-time processing environmentsCloud platforms, data analysis labs, remote offices
Employer & Industry UsageTech companies, IoT device manufacturers, automotive, roboticsFinance, healthcare, marketing, tech firms

Remote Embedded Machine Learning specialists focus on integrating ML models into embedded hardware for real-time applications, often working with IoT and robotics. In contrast, Remote Data Scientists analyze large datasets to extract insights, primarily working in cloud or office environments. Both roles require strong analytical skills but differ in technical focus and work settings.

What are the most commonly searched types of Embedded Machine Learning jobs in San Francisco, CA?

The most popular types of Embedded Machine Learning jobs in San Francisco, CA are:

What are popular job titles related to Remote Embedded Machine Learning jobs in San Francisco, CA?

For Remote Embedded Machine Learning jobs in San Francisco, CA, the most frequently searched job titles are:

What job categories do people searching Remote Embedded Machine Learning jobs in San Francisco, CA look for?

The top searched job categories for Remote Embedded Machine Learning jobs in San Francisco, CA are:

What cities near San Francisco, CA are hiring for Remote Embedded Machine Learning jobs?

Cities near San Francisco, CA with the most Remote Embedded Machine Learning job openings:

Remote Embedded Machine Learning jobs near you
Infographic showing various Remote Embedded Machine Learning job openings in San Francisco, CA as of June 2026, with employment types broken down into 51% Full Time, 14% Part Time, and 35% Contract. Highlights an 100% Remote job distribution, with an average salary of $180,712 per year, or $86.9 per hour.

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

Ginas Tech Jobs

San Francisco, CA • Remote

Full-time

Medical, Dental, Vision, PTO

Re-posted 14 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

Looking to hire a Machine Learning Technical Lead in San Francisco, CA or in other cities?  Our IT recruiting agencies and staffing companies can help.

We help companies that are looking to hire Machine Learning Technical Leads for jobs in San Francisco, California and in other cities too.  Please contact our IT recruiting agencies and IT staffing companies today!

Additional Information

Please check out all of our jobs at www.ginastechjobs.com.

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