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Applied Machine Learning Intern Jobs (NOW HIRING)

Applied Machine Learning Engineer | Music Software (Multiple Roles open) Role: Applied Machine Learning Engineer (Mid - Senior Opportunity) Company: Splash Employment Type: Contract (3 months ...

A strong focus on applied problem-solving, with a practical approach to integrating existing tools and systems. * A good understanding of music, production, or audio technology processes (or a strong ...

$42.75/hr

Research experience in one or more of the following fields: applied machine learning, machine ... Job Information 【For Pay Transparency】Compensation Description (Hourly) - Campus Intern The ...

Sr. Machine Learning Engineer

Santa Clara, CA · On-site

$143K - $189K/yr

As an Applied ML team, we are pushing the boundaries to provide our users with the utmost optimal ... Our team comprises a diverse range of backgrounds, including applied machine learning engineers ...

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Applied Machine Learning Intern information

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$25.5K

$42.6K

$88K

How much do applied machine learning intern jobs pay per year?

As of Aug 6, 2026, the average yearly pay for applied machine learning intern in the United States is $42,584.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,500.00 and $46,000.00 per year, depending on experience, location, and employer.

What is the difference between Applied Machine Learning Intern vs Data Science Intern?

AspectApplied Machine Learning InternData Science Intern
Required SkillsMachine learning algorithms, programming (Python, R), data analysisStatistical analysis, data visualization, programming (Python, R)
Work EnvironmentDeveloping ML models, experimenting with algorithms, deploying modelsData cleaning, analysis, reporting insights
Industry UsageTech companies, AI startups, research labsBusiness analytics, market research, finance

Applied Machine Learning Interns focus on developing and deploying machine learning models, requiring knowledge of algorithms and programming. Data Science Interns typically handle data analysis, visualization, and reporting. While both roles involve data skills, applied ML interns work more on model implementation, whereas data science interns focus on insights and data interpretation.

More about Applied Machine Learning Intern jobs
What cities are hiring for Applied Machine Learning Intern jobs? Cities with the most Applied Machine Learning Intern job openings:
What states have the most Applied Machine Learning Intern jobs? States with the most job openings for Applied Machine Learning Intern jobs include:
Infographic showing various Applied Machine Learning Intern job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 24% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $42,584 per year, or $20.5 per hour.

Director, Applied Machine Learning

Handshake

San Francisco, CA • On-site

$375K - $400K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 23 days ago


Job description

About Handshake

Handshake was founded on a simple belief that everyone deserves a path to a great career, regardless of where they went to school or who they know. Today, we power 25 million job seekers, 1 million+ employers, and 1,600 educational institutions.

In 2025, we started Handshake AI and built the fastest-growing AI data business in history. We work directly with frontier AI lab researchers to create evaluations, publish benchmarks, and push the boundary of data. We've grown from $0 to ~$1B run rate and pay ~$60M to over 30K individuals every month.

Why join Handshake now:

  • Shape how every career evolves in the AI economy, at global scale, with impact your friends, family and peers can see and feel

  • Partner hand-in-hand with world-class AI labs, Fortune 500 partners and the world's top educational institutions

  • Work together with engineers, scientists, operators, and more from Palantir, Meta, Scale AI, and former YC founders

  • Build a massive, fast-growing business with billions in revenue

About Handshake AI

Human data is the core infrastructure to AI advancement. Frontier AI labs currently improve model capabilities with various data-intensive post-training techniques. We believe that data spend for AI training will increase by 3-5x in the next few years and continue for much longer as models take on new domains. Handshake AI supports all of the frontier AI labs, working on their most complex data at the largest scale.

About the Role

As Director of Applied ML, you'll lead the function that sits at the intersection of frontier AI research and enterprise-scale delivery. You'll own three core pillars: post-training and RL environments, scaled post-training infrastructure, and strategic project support across our lab partnerships. You think like an applied researcher, lead like an operator, and move fluidly between technical depth and client-facing strategy.

You'll build and grow a team, set the technical standards for how the team engages with frontier labs, and help shape the roadmap as we scale, not just execute against it. This is a rare opportunity to lead at the frontier of gen AI, with direct visibility into where model training is headed before the rest of the world sees it.

Location: San Francisco, CA | Hybrid, 3x a week in office

What you'll do:

  • Lead post-training and RL environment strategy — you don't need to be the deepest technical expert, but your team needs to be able to lean on you for real guidance grounded in lab experience

  • Build and scale the infrastructure and team needed to run post-training at scale across multiple applied use cases

  • Own strategic project support across lab engagements — leading your team through a dynamic, evolving roadmap rather than executing the work solo

  • Manage and grow a team including AI Engineers, Research Scientists and AI Forward Deployed Engineers, with a path toward managing managers as the org scales

  • Partner directly with AI lab researchers and internal stakeholders across engineering and operations, translating ambiguous priorities into clear direction for your team

  • Maintain direct customer relationships, following up, communicating progress, and building trust with technical partners

  • Bring organizational maturity to a fast-growing team: solve today's problems with today's resources while planning several steps ahead

  • Stay current on the frontier: RL, post-training, and evaluation methods, bringing relevant insight into both team strategy and customer conversations

What we're looking for:

  • Experience leading and growing technical teams, ideally with a research background in applied ML or AI

  • Technical depth in applied AI systems design and model post-training (GRPO/PPO, SFT, or similar) enough to support a research-leaning team, though you don't need to have trained frontier models yourself

  • Experience building and scaling teams or infrastructure in an applied, production environment

  • Strong cross-functional leadership, comfortable working across engineering and operations, and managing shifting timelines with a team in tow

  • Excellent client-facing communication skills — you can translate technical work into business impact and hold your own with both researchers and customers

  • Organizational maturity and comfort with ambiguity — you'll need to be creative in solving problems as they arrive

Extra Credit:

  • Prior lab experience deploying or training agents for applied, real-world use cases

  • Experience managing managers or scaling a team through multiple growth stages

  • Familiarity with evaluation frameworks, annotation tooling, or human feedback collection at scale

Perks

Handshake delivers benefits that help you feel supported—and thrive at work and in life.

The below benefits are for full-time US employees.

🎯 Ownership: Equity in a fast-growing company

💰 Financial Wellness: 401(k) match, competitive compensation, financial coaching

🍼 Family Support: Paid parental leave, fertility benefits, parental coaching

💝 Wellbeing: Medical, dental, and vision, mental health support, $500 wellness stipend

📚 Growth: $2,000 learning stipend, ongoing development

💻 Office: Commuting support, free lunch, and gym in our SF office

🏝 Time Off: Flexible PTO, 15 holidays + 2 flex days

🤝 Connection: Team outings & referral bonuses

Compensation Range: $375K - $400K