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Director Machine Learning Jobs in California (NOW HIRING)

Qualcomm

Machine Learning Engineer

San Diego, CA · On-site

$122K - $184K/yr

As a Qualcomm Machine Learning Engineer, you will create and implement machine learning techniques ... Level of Responsibility: • Works under supervision. • Decision-making affects direct area of ...

Hive

Machine Learning Manager

San Francisco, CA · On-site

$180K - $250K/yr

Machine Learning Manager In order to execute our vision, we're constantly growing our machine ... The work you do here will have a noticeable and direct impact on the development of the company.

Hive

Machine Learning Manager

San Francisco, CA · On-site

$180K - $250K/yr

Machine Learning Manager In order to execute our vision, we're constantly growing our machine ... The work you do here will have a noticeable and direct impact on the development of the company.

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 ... The work you do here will have a noticeable and direct impact on the development of the company.

EarnIn

Head of Machine Learning

Mountain View, CA · Hybrid

$477K - $583K/yr

As a fintech company where data and machine learning (ML) is integral to both our business strategy and user experience, we depend on robust, scalable systems to drive impactful decisions and deliver ...

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 ... The work you do here will have a noticeable and direct impact on the development of the company.

Apple

Machine Learning Engineer, Proactive

Cupertino, CA · On-site

$212K - $318K/yr

Machine Learning Engineer, Proactive Posted: Jun 03, 2026 Weekly Hours: 40 Role Number: 200622577 ... user with a direct answer that best satisfies their intent and information seeking needs.

Jobs for Humanity

Machine Learning Engineers

San Jose, CA

$136K - $280K/yr

Tiktok Machine Learning Engineer (Search) - E-commerce - San JoseSan JoseRegularR DJob ID: A162279 ... Our company believes that criminal history may have a direct, adverse and negative relationship on ...

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All JobsDirector Machine Learning JobsDirector Machine Learning Jobs in California

Director Machine Learning information

See California salary details

$35.5K

$90.7K

$139.2K

How much do director machine learning jobs pay per year?

As of Jun 13, 2026, the average yearly pay for director machine learning in California is $90,729.00, according to ZipRecruiter salary data. Most workers in this role earn between $70,600.00 and $104,600.00 per year, depending on experience, location, and employer.

What is a $900,000 AI job?

A $900,000 AI job typically refers to senior roles such as Director of Machine Learning or Chief AI Officer, which involve leading AI strategy, managing teams, and developing advanced models. These positions often require extensive experience, expertise in machine learning frameworks, and strong leadership skills, with compensation reflecting high-level responsibilities and industry demand.

Which 3 jobs will survive AI?

For a Director of Machine Learning, roles that require complex problem-solving, strategic oversight, and domain expertise are likely to persist, such as AI research scientists, data science managers, and AI ethics specialists. These positions involve high-level decision-making, creativity, and understanding of nuanced human contexts that are difficult for AI to fully replicate. Skills in leadership, critical thinking, and advanced technical knowledge will remain valuable in these roles.

Is ML a high paying job?

Machine Learning (ML) roles, including positions like ML Engineer or Data Scientist, are generally among the higher-paying jobs in the tech industry due to the specialized skills required, such as programming, statistics, and experience with tools like TensorFlow or PyTorch. Salaries vary based on experience, location, and company size but tend to be significantly above average for many other roles in technology and data analysis.

What are the key skills and qualifications needed to thrive in the Director Machine Learning position, and why are they important?

To thrive as a Director Machine Learning, you need advanced expertise in machine learning, statistics, data science, and leadership, typically supported by a master's or Ph.D. in a related field and several years of relevant industry experience. Familiarity with tools such as Python, TensorFlow or PyTorch, cloud platforms, and data management systems, as well as certifications like AWS Certified Machine Learning or Google Professional Machine Learning Engineer, are commonly required. Exceptional communication, strategic thinking, and team management skills distinguish top candidates in this role. These capabilities are essential for driving organizational AI initiatives, fostering high-performing teams, and delivering impactful business solutions.

How much does an AI director make?

An AI director's salary typically ranges from $120,000 to $200,000 annually, depending on experience, industry, and location. Senior roles with advanced skills in machine learning, deep learning, and leadership often command higher compensation, especially in tech hubs or large organizations.

What is a Director Machine Learning job?

A Director of Machine Learning leads teams in developing and deploying machine learning models to solve business challenges. They define the AI strategy, oversee research, and ensure models are scalable and ethical. This role requires expertise in machine learning, data science, and leadership, as well as collaboration with cross-functional teams. Directors also stay updated on industry advancements and drive innovation within their organizations.

What are the primary responsibilities and challenges faced by a Director of Machine Learning on a daily basis?

A Director of Machine Learning is typically responsible for overseeing the development and deployment of machine learning solutions, mentoring technical teams, setting strategic direction for AI initiatives, and ensuring the alignment of projects with organizational goals. Challenges often include balancing innovative research with business priorities, navigating evolving technology landscapes, and coordinating efforts across data science, engineering, and stakeholder teams. This role requires regular collaboration with product managers, executives, and cross-functional departments to prioritize initiatives and communicate complex technical concepts. Successful directors excel at fostering a culture of continuous learning, optimizing team productivity, and staying ahead in a fast-paced, rapidly changing field.

What are the most commonly searched types of Machine Learning jobs in California? The most popular types of Machine Learning jobs in California are:
What are popular job titles related to Director Machine Learning jobs in California? For Director Machine Learning jobs in California, the most frequently searched job titles are:
What job categories do people searching Director Machine Learning jobs in California look for? The top searched job categories for Director Machine Learning jobs in California are:
What cities in California are hiring for Director Machine Learning jobs? Cities in California with the most Director Machine Learning job openings:
Director Machine Learning jobs near you
Infographic showing various Director Machine Learning job openings in California as of June 2026, with employment types broken down into 81% Full Time, 13% Part Time, 3% Temporary, and 3% Contract. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $90,729 per year, or $43.6 per hour.
Machine Learning Engineer

Machine Learning Engineer

ARROWCORE GROUP

Fremont, CA

Other

Posted 8 days ago

Job description

Title: Machine Learning Engineer
Location:Fremont, CA
Duration: 12+ Mos
Note - Onsite Interviews

About the Role:

Our direct client is hiring a Machine Learning Engineer for their software machine learning and computer vision team to design, develop, and implement critical machine learning models supporting factory and warehouse operations. You will transform ambiguous problem statements into robust end-to-end solutions using a variety of machine learning techniques and tools, including supervised learning, convolutional neural networks, and modern frameworks such as PyTorch and Pandas.

You will collaborate closely with partners in production, process, controls, and quality to deliver solutions for the most challenging problems in our operations. Your work will involve evaluating and deploying models in production environments, ensuring rapid and reliable alerting systems, and addressing operational issues as they arise. You must be adept at handling diverse, heterogeneous datasets that span multiple modalities, including images, multi-spectral sensor outputs, voice, text, and tabular data.

Responsibilities:

  • Design, develop, and deploy machine learning models for factory and warehouse environments.
  • Collaborate with cross-functional teams to identify, define, and solve high-impact operational challenges.
  • Build and maintain end-to-end machine learning pipelines, from data collection and preprocessing to model deployment and monitoring.
  • Evaluate and compare models using statistical methods to ensure optimal performance and feasibility.
  • Ensure robust alerting and monitoring systems are in place for deployed models to address issues rapidly.
  • Work with diverse datasets, integrating multiple data types such as images, sensor data, voice, text, and tabular information.
  • Write clean, modular, and sustainable code to translate research ideas into production-ready solutions.

Minimum Requirements:

  • In-depth knowledge of Python for high-performance, data-intensive applications.
  • Proficiency with at least one modern deep learning framework (e.g., PyTorch, Jax, TensorFlow).
  • Expertise in one or more of the following areas: computer vision, large language models, recommender systems, or operations research.
  • Foundational knowledge of statistics for model comparison and performance assessment.
  • Real-world experience deploying and maintaining machine learning solutions in production environments.
  • Passion for clean, sustainable, and modular code to bring research concepts to practical implementation.

Preferred Qualifications:

  • Experience working in manufacturing, industrial automation, or warehouse environments.
  • Familiarity with multi-modal data integration and analysis.
  • Strong problem-solving skills and the ability to thrive in ambiguous, fast-paced settings.
  • Excellent communication skills for cross-functional teamwork.
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