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Vice President Machine Learning Jobs (NOW HIRING)

The new VP must have a history of delivering high-quality work and building ongoing, trust-based ... Moreover, they should possess good knowledge of Data Science, Machine Learning, and Advanced ...

VP, Robot Learning

San Francisco, CA ยท On-site

$250 - $450/hr

VP, Robot Learning Location: San Francisco Bay Area Employment Type: Full-Time Level: Executive ... PhD or equivalent depth in robotics, computer science, machine learning, or a closely related ...

New

$250 - $450/hr

VP, Robot Learning Location: San Francisco Bay Area Employment Type: Full-Time Level: Executive ... PhD or equivalent depth in robotics, computer science, machine learning, or a closely related ...

New

The new VP must have a history of delivering high-quality work and building ongoing, trust-based ... Moreover, they should possess good knowledge of Data Science, Machine Learning, and Advanced ...

Showing results 21-40

Vice President Machine Learning information

See salary details

$35.5K

$114.7K

$181.5K

How much do vice president machine learning jobs pay per year?

As of Sep 4, 2026, the average yearly pay for vice president machine learning in the United States is $114,728.00, according to ZipRecruiter salary data. Most workers in this role earn between $95,000.00 and $143,000.00 per year, depending on experience, location, and employer.

What does a vice president of machine learning do?

A Vice President of Machine Learning leads and oversees the strategic direction of machine learning initiatives within an organization. They manage teams of data scientists, engineers, and researchers to develop and deploy AI-driven solutions that support business goals. This role involves collaborating with other executives, setting research agendas, ensuring best practices, and staying updated with the latest advancements in the field. The VP also plays a key role in resource allocation, talent acquisition, and scaling machine learning systems across the company.

What are the key skills and qualifications needed to thrive as a vice president of machine learning?

To thrive as a Vice President of Machine Learning, you need advanced expertise in machine learning, data science, and computer science, typically backed by a master's or PhD and extensive industry experience. Proficiency with platforms like TensorFlow, PyTorch, cloud computing services, and experience managing large-scale AI projects are crucial, along with a track record in leading technical teams. Exceptional leadership, strategic vision, and strong communication skills set outstanding candidates apart by enabling effective cross-functional collaboration and innovation. These skills are vital for driving organizational AI strategy, ensuring technical excellence, and delivering scalable business impact.

What are some common challenges faced by a vice president of machine learning when leading cross-functional teams?

A Vice President of Machine Learning often encounters challenges such as aligning diverse teams on technical priorities, managing expectations across product, engineering, and business units, and ensuring effective communication between stakeholders with varying levels of technical expertise. Balancing the need for innovation with practical business objectives and resource constraints is also a frequent challenge. Cultivating a collaborative culture and fostering ongoing professional development are key to overcoming these hurdles and driving successful outcomes.

What is the difference between Vice President Machine Learning vs Director of Machine Learning?

AspectVice President Machine LearningDirector of Machine Learning
Required CredentialsAdvanced degrees (Master's/PhD), extensive experience in MLSimilar educational background, less senior experience needed
Work EnvironmentStrategic leadership, cross-departmental collaborationProject management, team oversight
Employer & Industry UsageLarge tech firms, enterprises with AI focusTech companies, startups, research labs
Search & Comparison IntentHigh overlap in responsibilities and qualificationsRelated but more operational role

The Vice President Machine Learning typically holds a senior leadership role focused on strategic planning and cross-functional collaboration, while the Director of Machine Learning manages day-to-day projects and teams. Both roles require advanced degrees and experience in machine learning, but the VP is more involved in high-level decision-making and industry strategy.

What cities are hiring for Vice President Machine Learning jobs?

Cities with the most Vice President Machine Learning job openings:

What are the most commonly searched types of Machine Learning jobs?

The most popular types of Machine Learning jobs are:

What states have the most Vice President Machine Learning jobs?

States with the most job openings for Vice President Machine Learning jobs include:

What job categories do people searching Vice President Machine Learning jobs look for?

The top searched job categories for Vice President Machine Learning jobs are:

Infographic showing various Vice President Machine Learning job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 24% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $114,728 per year, or $55.2 per hour.

Machine Learning Scientist - Natural Language Processing (NLP) - Vice President - Machine Learn[...]

TwinThread

Palo Alto, CA โ€ข On-site

$150 - $200/hr

Other

Posted 17 days ago


Job description

At JPMorgan Chase, AI and technology promote our global operations with unmatched scale and speed. We invest over $18 billion annually in innovation, data leverage, and security to shape the future for our clients, communities, and employees. The Chief Data & Analytics Office (CDAO) accelerates our data and analytics journey, with the Machine Learning Center of Excellence (MLCOE) creating and deploying solutions for complex business challenges. By ensuring data quality and leveraging insights, the CDAO supports our commercial goals, enhancing productivity and risk management through AI and machine learning. The CDAO is also responsible for developing and implementing solutions that support the firmโ€™s commercial goals by harnessing artificial intelligence and machine learning technologies to develop new products, improve productivity, and enhance risk management effectively and responsibly.

As a Machine Learning Scientist โ€“ Natural Language Processing (NLP) - Vice President in the Machine Learning Center of Excellence, you will own the full lifecycle of developing and deploying machine learning solutions, from ideation to production. Acting as a leading voice within JPMC on all things Generative AI (GenAI), you will partner closely with all lines of business to innovate new solutions that drive transformational change for the bank. You will actively participate in our knowledge sharing community, representing your work inside and outside of the firm at leading industry conferences amongst peers and leaders in the space. We seek someone who excels in a highly collaborative, fast-paced environment, and holds a strong passion for machine learning to make a significant impact at a leading global financial institution.

Job responsibilities
  • Research and develop state-of-the-art machine learning models to solve real-world problems and apply them to tasks involving Generative AI (GenAI)
  • Act as a thought partner for JPMC leaders and help the business identify and implement new machine learning methods that deliver impact
  • Drive cross-functional collaboration with multiple partner teams such as Business, Technology, Product Management, Legal, Compliance, Strategy, and Business Management to deploy solutions into production
  • Lead firm-wide initiatives by developing large-scale frameworks to accelerate the application of machine learning models across different areas of the business
Required qualifications, capabilities, and skills
  • PhD in a quantitative discipline, e.g., Computer Science, Electrical Engineering, Mathematics, Operations Research, Optimization, or Data Science with at least 3 years of experience OR an MS with at least 5 years of industry or research experience in the field
  • Solid background in Generative AI (GenAI) and handsโ€‘on experience and solid understanding of machine learning and deep learning methods and toolkits (e.g., TensorFlow, PyTorch, NumPy, Scikitโ€‘Learn, Pandas)
  • Ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals
  • Scientific thinking with the ability to invent and to work both independently and in highly collaborative team environments
  • Solid written and spoken communication to effectively communicate technical concepts and results to both technical and business audiences
Preferred qualifications, capabilities, and skills
  • Strong background in Mathematics and Statistics; familiarity with the financial services industries and continuous integration models and unit test development
  • Knowledge in search/ranking or Meta Learning
  • Experience with A/B experimentation and data/metric-driven product development, cloudโ€‘native deployment in a largeโ€‘scale distributed environment, and ability to develop and debug productionโ€‘quality code
  • Published research in areas of Machine Learning or Deep Learning at a major conference or journal

This position is subject to Section 19 of the Federal Deposit Insurance Act. As such, an employment offer for this position is contingent on JPMorganChaseโ€™s review of criminal conviction history, including pretrial diversions or program entries.

We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicantsโ€™ and employeesโ€™ religious practices and beliefs, as well as mental health or physical disability needs.

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