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

Abaka AI

Machine Learning Engineer

Mountain View, CA · On-site

$175K - $275K/yr

About the Role We're hiring our first Machine Learning Engineer in the United States, a foundational role that will shape how Abaka builds, trains, and optimizes multimodal AI systems. You will own ...

Velo3D

Machine Learning Engineer

Fremont, CA · On-site

$150K - $220K/yr

We are seeking a Machine Learning Engineer to join our team developing machine learning solutions for quality assurance and process monitoring in additive manufacturing. Working closely with process ...

Abaka AI

Machine Learning Engineer

Mountain View, CA

$175K - $275K/yr

About the Role We're hiring our first Machine Learning Engineer in the United States, a foundational role that will shape how Abaka builds, trains, and optimizes multimodal AI systems. You will own ...

Nace AI

Machine Learning Engineer

Palo Alto, CA · On-site

They are seeking a Machine Learning Engineer to translate research into scalable solutions, collaborating with teams to architect robust systems and integrate AI-driven features into applications.

Articul8

Machine Learning Engineer

Dublin, CA · On-site

We are seeking machine learning engineers to join our team full-time. As part of your role, you will help us build pipelines of data collection, data extraction, data filtering/synthetic data ...

Hive

Machine Learning Engineer

San Francisco, CA

$120K - $180K/yr

Machine Learning Role In order to execute our vision, we need to grow our team of best-in-class machine learning engineers. We are looking for developers who are excited about staying at the ...

Hive

Machine Learning Engineer

San Francisco, CA · On-site

$120K - $180K/yr

Machine Learning Role In order to execute our vision, we need to grow our team of best-in-class machine learning engineers. We are looking for developers who are excited about staying at the ...

Capital One

Lead Machine Learning Engineer

San Francisco, CA · On-site +1

$120K - $159K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

Capital One

Lead Machine Learning Engineer

San Jose, CA · On-site

$120K - $158K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

Capital One

Lead Machine Learning Engineer

San Jose, CA · On-site +1

$120K - $158K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

Apple

Machine Learning Engineer (Search)

Cupertino, CA

$150K - $225K/yr

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 ...

Voltai

Machine Learning Engineer

Menlo Park, CA · On-site

The Machine Learning Engineer will architect and develop high-performance AI systems, manage large-scale datasets, and translate state-of-the-art research into production-ready code while ...

Gotion, Inc.

Machine Learning Engineer

Fremont, CA · On-site

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 ...

Spark Tek Inc

Machine Learning Engineer

San Jose, CA · On-site

Spark Tek Inc is seeking a highly skilled Machine Learning Engineer to design and build a low-latency query understanding and intelligent routing system. The role involves working on data modeling ...

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All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in Palo Alto, CA

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.

More about Machine Learning Engineer jobs

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:

Machine Learning Engineer jobs near you
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

Abaka AI

Mountain View, CA • On-site

$175K - $275K/yr

Full-time

Medical, Dental, Vision, PTO

Re-posted 3 hours ago

Job description

About Abaka AI
Abaka AI is built on one mission: to be the world's most trusted data partner for AI companies. More than 1,000 industry leaders across Generative AI, Embodied AI, and Automotive AI rely on us to power their data pipelines. With our headquarters in Silicon Valley-and teams in Paris, Singapore, and Tokyo-we support global partners with fast, reliable, and scalable data solutions.
Our offerings include a diverse catalog of off-the-shelf datasets (image, video, multimodal, reasoning, 3D, and beyond) as well as comprehensive data collection and annotation services. Whether teams need raw data, curated datasets, or full-cycle data engineering, Abaka AI provides the foundation for building high-performance AI systems.
About the Role
We're hiring our first Machine Learning Engineer in the United States, a foundational role that will shape how Abaka builds, trains, and optimizes multimodal AI systems. You will own the design and development of scalable training pipelines, work directly with our data engineering and research teams, and help drive the technical roadmap for model development across multiple modalities.
As an early member of the engineering team, you will influence core decisions around model training strategy, experimentation frameworks, distributed infrastructure, and internal best practices. Your work will directly impact the performance of frontier models trained on Abaka datasets and will help elevate the technical bar for our clients and partners.
If you thrive in high-ownership environments and want to shape the machine learning foundation of a fast-moving AI company, this role offers an opportunity to make an immediate and lasting impact.
Responsibilities
  • Design, build, and optimize scalable machine learning pipelines for multimodal model training, fine-tuning, and evaluation across text, image, audio, video, and 3D data.
  • Work closely with data engineering and research teams to develop efficient data workflows, including collection, preprocessing, annotation, versioning, and model integration.
  • Implement and refine training strategies for large-scale AI systems, including vision, video, and diffusion models, ensuring reproducibility, efficiency, and strong model performance.
  • Develop tools and automation frameworks that accelerate model experimentation, hyperparameter tuning, and deployment.
  • Identify and address performance bottlenecks in data or training pipelines to improve throughput, stability, and resource utilization.
  • Collaborate with product and infrastructure teams to ensure smooth integration of model outputs into both internal and client-facing applications.
  • Support internal best practices for model governance, experiment tracking, and documentation to maintain high engineering standards and reproducibility.

Qualifications
  • Strong academic background in computer science, artificial intelligence, machine learning, or related fields. Master's degree or Ph.D. is preferred.
  • 3+ years of experience in applied machine learning or ML engineering, with a demonstrated ability to deliver production-ready models or pipelines.
  • Proficient in Python and ML frameworks such as PyTorch, TensorFlow, or JAX, with hands-on experience in large-scale distributed training and inference systems.
  • Familiarity with multimodal data processing (e.g., text-image pairing, video understanding, speech-audio modeling) and dataset optimization for model training.
  • Solid understanding of ML system design, including feature pipelines, data loaders, model serving, and evaluation frameworks.
  • Experience with modern infrastructure tools such as Kubernetes, Ray, Airflow, or MLflow, along with cloud-based training environments (AWS, GCP, Azure).
  • Excellent communication and collaboration skills, capable of working effectively across engineering, research, and product teams to accomplish shared goals.
  • Self-driven and adaptable, comfortable operating in a fast-paced startup environment, and able to demonstrate strong ownership and urgency in execution.

Compensation & Benefits
The base salary range for this position is $175,000 - $275,000 USD annually.
Compensation may vary outside of this range depending on a number of factors, including a candidate's qualifications, skills, competencies and experience. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work at Abaka AI. This role is eligible for equity, as well as a comprehensive benefits package (health, dental, vision, PTO, flexible work schedule).

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