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Contract 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 ...

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 ...

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

$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 · 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, 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, Inc.

Senior Applied Scientist

San Jose, CA · On-site

$107K - $146K/yr

Adobe Firefly's Applied Science & Machine Learning (ASML) group invites an Applied Scientist / Machine Learning Engineer passionate about post-training and distillation of large generative AI models ...

Adobe

Senior Applied Scientist

San Jose, CA

$107K - $146K/yr

Adobe Firefly's Applied Science & Machine Learning (ASML) group invites an Applied Scientist / Machine Learning Engineer passionate about post-training and distillation of large generative AI models ...

Adobe

Senior Applied Scientist

Seattle, WA

$104K - $142K/yr

Adobe Firefly's Applied Science & Machine Learning (ASML) group invites an Applied Scientist / Machine Learning Engineer passionate about post-training and distillation of large generative AI models ...

Apple

Applied ML Science Manager

Cupertino, CA · On-site

We are currently seeking an experienced and passionate Applied ML Science Manager to lead a dynamic ... Scientist, Machine Learning, or Data Scientist roleFamiliarity with a brand range of quasi ...

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All JobsContract Applied Scientist Machine Learning Jobs

Contract Applied Scientist Machine Learning information

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$122.7K

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

As of Jun 7, 2026, the average yearly pay for contract applied scientist machine learning in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

What is a Contract Applied Scientist Machine Learning?

A Contract Applied Scientist in Machine Learning is a professional hired on a temporary or project-specific basis to apply scientific and machine learning techniques to solve real-world problems. They typically work on data analysis, model development, and algorithm implementation to help organizations make data-driven decisions. Unlike full-time employees, contract applied scientists may work for a set duration or specific deliverables and often bring specialized expertise to a project. Their role often requires strong skills in programming, statistics, and experience with machine learning frameworks. This position is common in industries such as technology, healthcare, and finance, where rapid innovation and specialized skills are needed.

What are some common challenges Contract Applied Scientists in Machine Learning face when working with clients, and how can they be addressed?

Contract Applied Scientists in Machine Learning often encounter challenges such as aligning project goals with client expectations, dealing with limited or unstructured data, and adapting to varying organizational processes. Clear communication is essential to define project scope and deliverables from the outset. Building flexible data pipelines and maintaining regular updates with stakeholders help ensure that technical solutions remain relevant to business needs. Additionally, being proactive in suggesting feasible alternatives or improvements can strengthen client relationships and lead to successful project outcomes.

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

To succeed as a Contract Applied Scientist in Machine Learning, you need a strong background in mathematics, statistics, computer science, and experience with designing and deploying ML models, typically supported by an advanced degree in a relevant field. Proficiency with programming languages like Python, ML libraries such as TensorFlow or PyTorch, and experience with cloud platforms or version control systems is crucial. Strong problem-solving abilities, effective communication, and adaptability help you collaborate with teams and deliver solutions on a contract basis. These skills ensure you can quickly contribute impactful, reliable ML solutions that meet client needs in a dynamic and time-sensitive environment.
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Contract Applied Scientist Machine Learning jobs near you
Infographic showing various Contract Applied Scientist Machine Learning job openings in the United States as of May 2026, with employment types broken down into 2% As Needed, 38% Full Time, and 60% Part Time. Highlights an 90% Physical, 3% Hybrid, and 7% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.
Senior Applied Scientist, Machine Learning

Senior Applied Scientist, Machine Learning

McAfee Corp.

Frisco, TX • On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 8 days ago

Job description

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 Frisco, TX. You will be required to be on-site on an as-needed basis; when you are not working on-site, you will work from your home office. You must be within commutable distance of Frisco, TX. We are not offering relocation assistance at this time.
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're proud to be Great Place to Work® Certified in 10 countries, a reflection of the supportive, empowering environment we've built where people feel seen, valued, and energized to reach their full potential and thrive.
We offer a variety of social programs, flexible work hours and family-friendly benefits to all of our employees.
  • Bonus Program
  • Pension and Retirement Plans
  • Medical, Dental and Vision Coverage
  • Paid Time Off
  • Paid Parental Leave
  • Support for Community Involvement

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.

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