2

Remote Google Machine Learning Engineer Jobs in Sunnyvale, 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

Mountain View, CA ยท On-site +1

$230K - $265K/yr

As a Senior Machine Learning Engineer, you'll bring your strong software engineering mindset to ... The company is backed by early investors in Google, DeepMind, Zoom, and Tesla. Otter.ai is an equal ...

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 Google Machine Learning Engineer information

See Sunnyvale, CA salary details

$37K

$151.1K

$227.1K

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

As of Sep 6, 2026, the average yearly pay for remote google machine learning engineer in Sunnyvale, CA is $151,130.00, according to ZipRecruiter salary data. Most workers in this role earn between $119,100.00 and $181,900.00 per year, depending on experience, location, and employer.

What is a remote Google machine learning engineer?

A Remote Google Machine Learning Engineer is a professional who designs, builds, and deploys machine learning models and artificial intelligence solutions, often using Google Cloud technologies, while working from a remote location. These engineers collaborate with cross-functional teams to solve complex business problems, optimize data pipelines, and improve model performance. Their responsibilities typically include data preprocessing, model selection, training, evaluation, and deployment, all while ensuring scalability and security. Working remotely allows them to contribute to projects from anywhere, leveraging cloud-based tools and collaboration platforms.

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

To thrive as a Remote Google Machine Learning Engineer, you need a strong background in computer science, mathematics, and machine learning algorithms, typically supported by a relevant degree and experience in building scalable models. Proficiency with tools such as TensorFlow, Python, Google Cloud Platform (GCP), and familiarity with distributed systems is essential. Excellent problem-solving, communication, and self-management skills are crucial for effective remote collaboration and innovation. These capabilities enable engineers to deliver impactful machine learning solutions while seamlessly integrating with global Google teams.

How do remote Google machine learning engineers typically collaborate with cross-functional teams while working from different locations?

Remote Google Machine Learning Engineers often use a combination of video conferencing, cloud-based collaboration tools, and shared code repositories to work closely with data scientists, product managers, and software engineers. Regular stand-up meetings, sprint planning sessions, and detailed documentation help ensure everyone is aligned and project milestones are met. Despite being remote, engineers are encouraged to proactively communicate progress, share insights, and participate in code reviews to maintain a strong team dynamic and drive successful project outcomes.

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

The most popular types of Google Machine Learning Engineer jobs in Sunnyvale, CA are:

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

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

What cities near Sunnyvale, CA are hiring for Remote Google Machine Learning Engineer jobs?

Cities near Sunnyvale, CA with the most Remote Google Machine Learning Engineer job openings:

Infographic showing various Remote Google Machine Learning Engineer job openings in Sunnyvale, CA as of August 2026, with employment types broken down into 50% Full Time, and 50% Contract. Highlights an 100% Remote job distribution, with an average salary of $151,130 per year, or $72.7 per hour.

Machine Learning Engineer, Ads

Higgsfield

San Francisco, CA โ€ข Remote

$165K - $230K/yr

Full-time

Posted 18 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