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Applied Scientist Machine Learning Jobs (NOW HIRING)

Apple

Applied Scientist

Austin, TX · On-site

We are currently seeking an experienced and passionate Applied Scientist, who will work on innovative products at the intersection of causal inference, statistics, and machine learning to help ...

Ramp

Senior Applied Scientist, Credit Risk

Responsibilities : • Design, build, and optimize machine learning models that support credit risk decisioning and portfolio management at Ramp • Own the full applied science development lifecycle ...

Apple

Applied Scientist

Austin, TX · On-site

We are currently seeking an experienced and passionate Applied Scientist, who will work on innovative products at the intersection of causal inference, statistics, and machine learning to help ...

RAMP

Senior Applied Scientist, Credit Risk

Manhattan, NY · On-site +1

You'll work at the intersection of machine learning, statistics, economics, and product strategy ... Applied scientists at Ramp focus on solving quantitative problems across credit, fraud, growth, and ...

Ramp

Senior Applied Scientist, Credit Risk

New York, NY · Remote

$165K - $228K/yr

You'll work at the intersection of machine learning, statistics, economics, and product strategy ... Applied scientists at Ramp focus on solving quantitative problems across credit, fraud, growth, and ...

Ramp

Senior Applied Scientist, Credit Risk

New York, NY · On-site

$165K - $228K/yr

You'll work at the intersection of machine learning, statistics, economics, and product strategy ... Applied scientists at Ramp focus on solving quantitative problems across credit, fraud, growth, and ...

Grid

Applied Scientist

Seattle, WA

$120K - $200K/yr

Proven experience in Machine Learning and/or Applied Science, including a strong background in statistical inference, machine learning. This is a requirement, a bachelors or master's degree in ...

Grid

Applied Scientist

Seattle, WA · On-site

$120K - $200K/yr

Proven experience in Machine Learning and/or Applied Science, including a strong background in statistical inference, machine learning. This is a requirement, a bachelors or master's degree in ...

Fuze Health

OR · On-site

As a Applied Scientist, you will lead the end-to-end development of advanced machine learning solutions, guiding initiatives from ideation through production, and mentoring peers across the ...

Apple

Applied Scientist

Austin, TX

$171K - $302K/yr

We are currently seeking an experienced and passionate Applied Scientist, who will work on innovative products at the intersection of causal inference, statistics, and machine learning to help ...

Apple

Applied Scientist

Austin, TX · On-site

$171K - $302K/yr

We are currently seeking an experienced and passionate Applied Scientist, who will work on innovative products at the intersection of causal inference, statistics, and machine learning to help ...

Adobe

Applied Scientist 3

San Jose, CA

Join Adobe Firefly's Applied Science & Machine Learning (ASML) group and help advance content generation technologies powered by artificial intelligence. This role involves working closely with a ...

Adobe, Inc.

Applied Scientist 3

San Jose, CA · On-site

Join Adobe Firefly's Applied Science & Machine Learning (ASML) group and help advance content generation technologies powered by artificial intelligence. This role involves working closely with a ...

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All JobsApplied Scientist Machine Learning Jobs

Applied Scientist Machine Learning information

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$22.5K

$129.7K

$204K

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

As of Jun 6, 2026, the average yearly pay for applied scientist machine learning in the United States is $129,694.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,500.00 and $158,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an Applied Scientist in Machine Learning, and why are they important?

To thrive as an Applied Scientist in Machine Learning, you need a solid background in mathematics, statistics, computer science, and typically a master's or PhD in a related field. Proficiency in programming languages like Python or Java, experience with ML frameworks such as TensorFlow or PyTorch, and familiarity with cloud platforms and data processing tools are crucial. Strong problem-solving skills, intellectual curiosity, and the ability to communicate complex ideas clearly make candidates stand out. These skills ensure effective development, implementation, and communication of advanced machine learning solutions that drive business impact.

How do Applied Scientists in Machine Learning typically collaborate with software engineers and data engineers on projects?

Applied Scientists in Machine Learning often work closely with software engineers and data engineers to bring machine learning models from prototype to production. They usually develop and validate models, while data engineers assist in preparing and managing large datasets, and software engineers help integrate models into scalable applications. Effective communication and cross-functional teamwork are essential, as the role requires translating scientific findings into practical solutions that align with business goals. Regular meetings, code reviews, and collaborative problem-solving sessions are common, ensuring smooth transitions between research and deployment phases.

What does an Applied Scientist in Machine Learning do?

An Applied Scientist in Machine Learning develops and implements machine learning models to solve real-world problems. They work on collecting and preprocessing data, designing algorithms, and evaluating model performance. Their work often bridges research and product development, collaborating with engineers and data scientists to deploy solutions in production. Applied Scientists also keep up-to-date with the latest advancements in machine learning to continuously improve systems and outcomes.
More about Applied Scientist Machine Learning jobs
What are the most commonly searched types of Applied Scientist Machine Learning jobs? The most popular types of Applied Scientist Machine Learning jobs are:
What states have the most Applied Scientist Machine Learning jobs? States with the most job openings for Applied Scientist Machine Learning jobs include:
What job categories do people searching Applied Scientist Machine Learning jobs look for? The top searched job categories for Applied Scientist Machine Learning jobs are:
Applied Scientist Machine Learning jobs near you
Infographic showing various Applied Scientist Machine Learning job openings in the United States as of May 2026, with employment types broken down into 38% Full Time, 60% Part Time, and 2% Contract. Highlights an 90% Physical, 3% Hybrid, and 7% Remote job distribution, with an average salary of $129,694 per year, or $62.4 per hour.
Senior Applied Scientist, Machine Learning

Senior Applied Scientist, Machine Learning

McAfee Corp.

Reston, VA • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

This job post has expired today. Applications are no longer accepted.

Job description

Job Title:
Senior Applied Scientist, Machine Learning
Role Overview:
We are seeking a Senior Applied Scientist to join McAfee's Consumer ML team and drive AI-powered solutions that deliver personalized experiences, optimize pricing, and improve payment success for millions of global customers. In this role, you will lead the end-to-end development and deployment of high-impact ML models across fraud detection, dynamic pricing, journey optimization, and contextual recommendation systems. You'll design and execute experimentation frameworks, champion GenAI tooling adoption to accelerate development, and apply advanced techniques, including deep learning and reinforcement learning.
This is a hands-on technical leadership role requiring 8+ years of Applied ML experience, proven expertise in personalization, pricing optimization, or churn/propensity modeling for digital subscriptions, and strong cross-functional collaboration skills to translate ML innovation into measurable business outcomes.
This is a hybrid position located in the United States but you will be required to be onsite on an as needed basis. When you are not working onsite you will work from your home office.
About the Role
  • Strategic Vision: Drive the ML science strategy for pricing, recommendation systems, and personalized consumer experiences, to maximize McAfee's customer value.
  • Model Development: Lead the research, implementation, and delivery of Applied AI/ML models using user behavior and subscription data to enhance personalization and product value.
  • Optimization & Experimentation: Lead algorithm development to optimize consumer journeys, increase conversion rates, and drive monetization strategies. Design and execute controlled experiments (A/B and multivariate tests) to validate and enhance model performance.
  • Generative AI Enablement: Leverage GenAI tools-such as GitHub Copilot, Claude Code, and other AI coding assistants-to amplify development productivity in data preparation, model tuning, and orchestration workflows. Champion the integration of GenAI capabilities into the ML lifecycle to accelerate experimentation and reduce time-to-market.
  • Research & Knowledge Sharing: Stay at the forefront of ML science, contributing to the development of new algorithms and applications. Share knowledge through internal presentations, publications, and participation in academic or industry forums.
  • Reinforcement Learning is a Plus: Guide the team in applying reinforcement learning methods such as contextual bandits, SARSA, and Q-learning. Implement exploration-exploitation strategies, including epsilon-greedy, Thompson sampling, and Upper Confidence Bound (UCB) to optimize decision-making for pricing and recommendation engines.
  • Cross-Functional Collaboration: Partner with Marketing, Product, Sales, and Engineering teams to ensure ML solutions align with strategic objectives and deliver measurable business impact.

About You
  • Experience: 8+ years of expertise in Applied AI & ML, complemented by at least 3 years of technical leadership experience mentoring machine learning scientists in technical capacities.
  • Mandatory Qualification: Proven track record in at least one of the following: implementing AI/ML-based personalized messaging techniques to enhance consumer/customer product experiences; developing AI/ML-based dynamic pricing and personalized offer strategies for pricing optimization; or creating customer/consumer churn and propensity models specifically for digital subscription use cases
  • Technical Expertise: Deep proficiency in classical ML and deep learning techniques (e.g., XGBoost, Random Forest, SVMs, deep neural networks), autoencoders, representation learning, and deep recommender system techniques, as well as reinforcement learning methods (contextual bandits, SARSA, Q-learning). Strong programming skills in Python, SQL, and ML frameworks.
  • Tooling & Libraries: Proficient with ML libraries such as PyTorch and Scikit-learn, with a strong background in feature engineering, model validation, and evaluation metrics.
  • Mathematical Foundations: Solid understanding of the mathematical and statistical principles underpinning ML algorithms (linear algebra, calculus, probability) and a passion for solving complex problems through research and application of emerging techniques.
  • Communication & Collaboration: Excellent communicator who can distill complex ML concepts for both technical and non-technical stakeholders and collaborate effectively across cross-functional teams to align ML models with business goals.

#LI-Hybrid
Company Overview
McAfee is a leader in personal security for consumers. Focused on protecting people, not just devices, McAfee consumer solutions adapt to users' needs in an always online world, empowering them to live securely through integrated, intuitive solutions that protects their families and communities with the right security at the right moment.
Company Benefits and Perks:
We work hard to embrace diversity and inclusion and encourage everyone at McAfee to bring their authentic selves to work every day. We offer a variety of social programs, flexible work hours and family-friendly benefits to all of our employees.
  • Bonus Program
  • 401k Retirement Plan
  • Medical, Dental, Vision, Basic Life, Short Term Disability and Long-Term Disability Coverage
  • Paid Parental Leave
  • Support for Community Involvement
  • 14 Paid Company Holidays
  • Unlimited Paid Time Off for Exempt Employees
  • 96 Hours of Sick Time and 120 Hours of Vacation for Non-Exempt Employees Accrued Each Year

We're serious about our commitment to diversity which is why McAfee prohibits discrimination based on race, color, religion, gender, national origin, age, disability, veteran status, marital status, pregnancy, gender expression or identity, sexual orientation or any other legally protected status.
The starting pay range for this position is $123,650.00-$203,150.00. McAfee takes into consideration an individual's skillset, experience and location in making final salary determinations. For further details, please discuss with the Talent Acquisition Partner.
Please click here to view and download the Job Applicant Privacy Notice, which applies to all McAfee job applicants who are residents of the state of California.

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