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Remote Machine Learning Engineer Jobs in San Jose, CA

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 ...

Senior Machine Learning Engineer At EvenUp, we leverage cutting-edge AI to bring fairness and accessibility to the legal system. Tackling the most complex legal document challenges requires expertise ...

Senior Machine Learning Engineer

Mountain View, CA ยท On-site +1

$123K - $169K/yr

We're looking for a Senior Machine Learning Engineer to lead the development of these foundational AI systems within the Unity engine, empowering creators to build smarter, more responsive in-game ...

Showing results 41-60

Remote Machine Learning Engineer information

See San Jose, CA salary details

$36.9K

$150.9K

$226.8K

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

As of Sep 3, 2026, the average yearly pay for remote machine learning engineer in San Jose, CA is $150,916.00, according to ZipRecruiter salary data. Most workers in this role earn between $119,000.00 and $181,700.00 per year, depending on experience, location, and employer.

What is a remote machine learning engineer?

A Remote Machine Learning Engineer designs, develops, and deploys machine learning models while working from a remote location. They preprocess data, train and optimize models, and integrate them into production systems. Their role often involves collaborating with data scientists, software engineers, and stakeholders to solve complex problems using AI. Strong programming skills in Python, experience with ML frameworks like TensorFlow or PyTorch, and cloud computing knowledge are essential. Remote ML engineers must also communicate effectively and manage their time efficiently to work asynchronously with teams.

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

To thrive as a Remote Machine Learning Engineer, you need a strong background in computer science, mathematics, and experience with machine learning algorithms, typically supported by a relevant degree and prior project work. Proficiency with programming languages like Python, machine learning frameworks such as TensorFlow or PyTorch, and familiarity with cloud computing platforms is crucial, and certifications like AWS Certified Machine Learning can enhance your profile. Excellent communication, self-motivation, and time-management skills are also essential for collaborating across remote teams and meeting project goals. These combined technical and soft skills are vital for developing effective machine learning solutions while ensuring productivity and collaboration in a virtual work environment.

What are some typical challenges faced by remote machine learning engineers, and how are they addressed?

Remote Machine Learning Engineers often face challenges such as coordinating across different time zones, ensuring smooth communication with team members, and accessing large datasets or secure environments remotely. Organizations commonly address these by using robust collaboration tools (like Slack, GitHub, and Jira), establishing clear documentation, and setting regular virtual meetings to maintain alignment. Many companies also provide secure remote environments or VPN access for handling sensitive data and code. Proactive communication and organized workflows help mitigate these challenges, enabling engineers to remain productive and connected to their teams.

Are remote machine learning engineers still in demand?

Remote machine learning engineers are currently in high demand due to the growth of AI and data-driven technologies across industries. Skills in programming, data analysis, and familiarity with tools like Python, TensorFlow, or PyTorch are highly sought after, and many companies continue to hire for remote roles in this field.

Can remote machine learning engineers work remotely?

Yes, remote machine learning engineers can work remotely, as many companies offer flexible work arrangements for this role. The position typically involves tasks such as data analysis, model development, and collaboration through online tools, making remote work feasible with strong communication skills and proficiency in programming languages like Python or frameworks like TensorFlow. However, some roles may require occasional on-site meetings or access to specialized hardware.

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

The most popular types of Machine Learning Engineer jobs in San Jose, CA are:

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

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

What cities near San Jose, CA are hiring for Remote Machine Learning Engineer jobs?

Cities near San Jose, CA with the most Remote Machine Learning Engineer job openings:

Infographic showing various Remote Machine Learning Engineer job openings in San Jose, CA as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% Remote job distribution, with an average salary of $150,916 per year, or $72.6 per hour.

Machine Learning Engineer, Ads

Higgsfield

San Francisco, CA โ€ข Remote

$165K - $230K/yr

Full-time

Posted 15 days ago


Job description

Why work at Higgsfield AI?

Higgsfield AI is the fastest-scaling generative AI company in history, hitting $700M in annual revenue run rate, 30M+ users worldwide, 6M+ generations per day, and powering 390 of Fortune 500 brands.

We're building at the absolute frontier of AI-powered video creation and next-generation creative tools. Joining Higgsfield means becoming part of a high-impact team shaping the future of AI-native experiences, at a company that isn't just moving fast, but rewriting what fast looks like.

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 machine learning, generative AI, and advertising systems—building the models and infrastructure that determine how creative is generated, ranked, optimized, and ultimately performs.

This role is for someone who understands ads systems deeply and is equally strong in modern generative AI. You should be comfortable moving across ranking and recommendation, targeting and optimization, prompt engineering, post-training, and production ML systems.

You'll help define what an AI-native advertising platform looks like from the ground up.

What you'll do:
  • Build and improve ML systems powering advertising products, including ranking, recommendation, targeting, prediction, and optimization.

  • Develop models that improve ad creative quality, relevance, personalization, and performance at scale.

  • Build systems that connect generative models with real-world advertising performance signals, creating feedback loops that continuously improve model outputs.

  • Apply prompt engineering and post-training techniques to improve generative models for advertising and creative use cases.

  • Work on fine-tuning, preference optimization, evaluation, and other techniques for adapting foundation models to specific creative and advertising objectives.

  • Design and run experiments across creative generation, ranking, targeting, and delivery to understand what drives advertiser performance.

  • Build production ML systems that operate reliably at significant scale, from experimentation through inference and serving.

  • Work closely with Product, Research, Engineering, and GTM teams to turn advances in generative AI into products advertisers can use.

Requirements
  • Deep experience building machine learning systems for advertising.

  • Strong understanding of ads systems, including areas such as ranking, recommendation, targeting, bidding, conversion prediction, creative optimization, or measurement.

  • Hands-on experience with LLMs, multimodal models, or generative AI systems.

  • Strong experience with prompt engineering and model evaluation.

  • Experience with post-training, including techniques such as supervised fine-tuning, preference optimization, reinforcement learning, or related approaches.

  • Strong software engineering fundamentals and experience shipping production ML systems.

  • Ability to operate across research and engineering: you can experiment quickly, identify what works, and turn it into a scalable production system.

  • High agency.

  • Working English.

Nice to have
  • Experience building ads, ranking, or recommendation systems at a major consumer, social, search, or advertising platform.

  • Experience with generative video, image, or multimodal models.

  • Experience using downstream signals such as CTR, CVR, ROAS, engagement, or retention to train or optimize ML systems.

  • Experience with large-scale model training, inference optimization, or distributed ML infrastructure.

  • Experience building AI systems that generate or optimize advertising creative.

Compensation & Benefits

• We offer a competitive and thoughtfully structured compensation package designed to align with impact, experience, and long-term growth.

Base Salary: The anticipated salary range for this role is $165 - $230k, depending on experience, skills, scope, and location.

Equity: In addition to cash compensation, employees are eligible to participate in the company’s stock option program and share in Higgsfield’s long-term growth. •

Benefits: We offer a comprehensive benefits package designed to support employees professionally and personally

• The opportunity to work on ambitious AI products alongside a highly experienced, fast-moving, and international team.

• Significant ownership, direct impact, and opportunities for professional growth as the company scales.

 

This is a hybrid role based in the San Francisco Bay Area. Team members are expected to work from our San Francisco office three full days per week, with the remaining days worked remotely and are expected to be available during agreed working hours and to maintain sufficient overlap with the relevant team’s time zone. We value in-person collaboration, active communication, responsiveness, and close partnership across teams.

Higgsfield AI is an equal opportunity employer. We are committed to building a diverse and inclusive team and do not discriminate on the basis of race, color, religion, sex, gender identity or expression, sexual

Compensation Range: $165K - $230K