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Machine Learning Engineer Jobs in Palo Alto, CA (NOW HIRING)

Position Overview We are looking for a Machine Learning Engineer to be responsible for designing and implementing cutting-edge reinforcement learning algorithms, conducting experiments, and ...

Who We're Looking For As a Machine Learning Engineer in Delivery, you are a problem solver who stays anchored to impact. You are someone who can grasp advanced engineering concepts across multiple ...

Machine Learning Engineer

San Francisco, CA · On-site

$225K - $300K/yr

Machine Learning Engineer About Latent Health Healthcare today is only truly personalized for two groups: those with wealth and access, and those with physicians in their immediate family. For ...

Who We're Looking For As a Machine Learning Engineer in Delivery, you are a problem solver who stays anchored to impact. You are someone who can grasp advanced engineering concepts across multiple ...

We're hiring an Machine Learning Engineer as the volume and complexity of legal AI workflows in our system scale rapidly. As more firms rely on Eve to automate high-stakes legal work - from intake ...

They are seeking a Machine Learning Engineer to design and develop scalable training pipelines for multimodal AI systems, collaborating with data engineering and research teams to drive the technical ...

BeeGenius is building the future of work, and they are seeking an AI/Machine Learning Engineer to join their team. In this role, you will be responsible for developing and implementing machine ...

The Machine Learning Engineer will design and develop scalable training pipelines for multimodal AI systems, collaborate with data engineering and research teams, and influence core decisions around ...

We are looking for a Machine Learning Engineer to join and play a big part in the next revolution of Maps; to enable users to find more things in innovative ways. On our team, you will have plenty of ...

Our team comprises a diverse range of backgrounds, including applied machine learning engineers with a focus on ML and LLM, and experienced distributed systems engineers. As such, we are seeking ...

Description Apple's Video Computer Vision (VCV) Face and Body technologies team is looking for a skilled Machine Learning Engineer with experience developing ML models for computer vision and ...

Nace AI is a company focused on machine learning solutions, and they are seeking a Machine Learning Engineer to translate cutting-edge research into scalable, production-ready solutions. The role ...

Role Summary We are seeking a highly motivated Machine Learning Engineer with a strong background in model architecture design and algorithm development, ideally with experience in scientific domains ...

Description Apple's Video Computer Vision (VCV) Face and Body technologies team is looking for a skilled Machine Learning Engineer with experience developing ML models for computer vision and ...

As a Machine Learning Engineer, you will play a central role in translating cutting-edge machine learning research into scalable, production-ready solutions. You will collaborate closely with cross ...

Bee Genius is building the future of work and is seeking an AI/Machine Learning Engineer to join their team. The role involves developing and implementing machine learning models and algorithms to ...

About the Role We're looking for a Machine Learning Engineer to design, build, and deploy production-grade ML systems that power the next generation of Plenful's AI platform. You'll own the end-to ...

Showing results 21-40

Machine Learning Engineer information

See Palo Alto, CA salary details

$37K

$151.4K

$227.5K

How much do machine learning engineer jobs pay per year?

As of Sep 2, 2026, the average yearly pay for machine learning engineer in Palo Alto, CA is $151,371.00, according to ZipRecruiter salary data. Most workers in this role earn between $119,300.00 and $182,200.00 per year, depending on experience, location, and employer.

What is a machine learning engineer?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

What does a machine learning engineer do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

What are the key skills and qualifications needed to thrive as a machine learning engineer, and why are they important?

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

What are some common challenges faced by machine learning engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

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

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

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

The most popular types of Machine Learning Engineer jobs in Palo Alto, CA are:

What are popular job titles related to Machine Learning Engineer jobs in Palo Alto, CA?

For Machine Learning Engineer jobs in Palo Alto, CA, the most frequently searched job titles are:

What job categories do people searching Machine Learning Engineer jobs in Palo Alto, CA look for?

The top searched job categories for Machine Learning Engineer jobs in Palo Alto, CA are:

What cities near Palo Alto, CA are hiring for Machine Learning Engineer jobs?

Cities near Palo Alto, CA with the most Machine Learning Engineer job openings:

Infographic showing various Machine Learning Engineer job openings in Palo Alto, CA as of August 2026, with employment types broken down into 1% As Needed, 66% Full Time, 30% Part Time, 2% Temporary, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $151,371 per year, or $72.8 per hour.

Machine Learning Engineer

Skild AI

San Mateo, CA

Full-time

Re-posted 25 days ago


Job description

Position Overview

We are looking for a Machine Learning Engineer to be responsible for designing and implementing cutting-edge reinforcement learning algorithms, conducting experiments, and optimizing these models to perform efficiently in real-world robotic environments. This will require close collaboration with our robotics, research, and engineering team. Your work will directly impact the development of intelligent, adaptable robots capable of learning and performing complex tasks autonomously.

Responsibilities
  • Develop and implement state-of-the-art reinforcement learning algorithms for robotic applications.
  • Design and conduct experiments to train RL models and conduct real-world tests.
  • Collaborate closely with researchers to explore novel methods of scaling up reinforcement learning model training.
  • Communicate effectively with inference, application, and deployment engineers to integrate RL models into robotic systems and iterate on methods to enable robust deployment.
  • Analyze and interpret experimental results, iterating on model design to achieve desired performance.
  • Stay up-to-date with the latest research and advancements in reinforcement learning.
Preferred Qualifications
  • BS, MS or higher degree in Computer Science, Robotics, Engineering or a related field, or equivalent practical experience.
  • Proficiency in Python, C++, or similar and at least one deep learning library such as PyTorch, TensorFlow, JAX, etc.
  • Deep understanding and practical experience with various reinforcement learning algorithms and techniques (model-free, model-based, multi-task, hierarchical, multi-agent, etc.).
  • Strong background in algorithms, data structures, and software engineering principles.
  • Experience with physics simulation engines and tools for training RL.
  • Deep understanding of state-of-the-art machine learning techniques and models.
  • Extensive industry experience with reinforcement learning and robotic systems.