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Freelance Applied Scientist Machine Learning Jobs

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 ...

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

New York, NY · Remote

$165.80K - $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

$165.80K - $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

$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 ...

Apple

Applied Scientist

Austin, TX · On-site

$171.60K - $302.20K/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 ...

Fuze Health

OR

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 ...

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 ...

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 ...

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Freelance Applied Scientist Machine Learning information

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

To excel as a Freelance Applied Scientist in Machine Learning, you need a solid background in mathematics, statistics, and computer science, typically supported by an advanced degree and strong programming skills in Python or similar languages. Familiarity with machine learning frameworks (such as TensorFlow or PyTorch), cloud platforms, and data analysis tools is essential, along with relevant certifications like TensorFlow Developer or AWS Machine Learning. Strong problem-solving abilities, self-motivation, and effective communication are crucial for managing projects independently and collaborating with diverse clients. These skills enable successful delivery of high-impact solutions tailored to client needs, ensuring both technical excellence and client satisfaction.

How do freelance applied scientists in machine learning typically collaborate with clients and teams remotely?

Freelance applied scientists in machine learning often work remotely, communicating with clients and teams through regular video calls, messaging platforms, and project management tools. Collaboration usually involves understanding client requirements, clarifying data needs, and providing frequent updates on project progress. Since projects may require input from software engineers, data analysts, or product managers, strong communication skills and the ability to document work clearly are crucial. Freelancers also need to proactively manage their schedules and expectations, as they frequently juggle multiple projects or stakeholders at once.

What does a Freelance Applied Scientist in Machine Learning do?

A Freelance Applied Scientist in Machine Learning is a professional who independently works with clients or organizations to design, develop, and implement machine learning models and solutions. Their responsibilities typically include data analysis, building predictive models, and translating business problems into data-driven solutions. They may also be involved in researching new algorithms, optimizing existing models, and communicating findings to stakeholders. Since they work on a freelance basis, they often manage multiple projects and clients simultaneously.

What is the difference between Freelance Applied Scientist Machine Learning vs Freelance Data Scientist?

AspectFreelance Applied Scientist Machine LearningFreelance Data Scientist
CredentialsAdvanced degrees in ML, AI, or related fieldsDegrees in Data Science, Statistics, or related fields
Work EnvironmentFocus on developing ML models, algorithms, and AI solutionsData analysis, visualization, and statistical modeling
Industry UsageUsed in AI-driven products, research, and advanced analyticsApplied in business insights, reporting, and data-driven decision making

Freelance Applied Scientist Machine Learning professionals specialize in developing and deploying machine learning models and AI solutions, often requiring advanced technical credentials. Freelance Data Scientists focus on analyzing data, creating reports, and deriving insights, with a broader scope of statistical skills. Both roles are in high demand but serve different purposes within data and AI projects.

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What are the most commonly searched types of Applied Scientist Machine Learning jobs? The most popular types of Applied Scientist Machine Learning jobs are:
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Freelance Applied Scientist Machine Learning jobs near you
Infographic showing various Freelance Applied Scientist Machine Learning job openings in the United States as of May 2026, with employment types broken down into 96% Full Time, 1% Part Time, and 3% Contract. Highlights an 93% Physical, 1% Hybrid, and 6% Remote job distribution.
Senior Applied Scientist, Machine Learning

Senior Applied Scientist, Machine Learning

McAfee Corp.

Reston, VA • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 13 days ago

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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