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Deep Learning Scientist Jobs (NOW HIRING)

Senior Machine Learning Scientist

Seattle, WA · Remote

$104K - $142K/yr

  • Medical

  • Dental

  • Vision

  • PTO

Senior Machine Learning Scientist The Senior Machine Learning Scientist is responsible for building ... Applies deep expertise in applied ML, Generative AI, and rigorous experimentation to design robust ...

Deep Learning Engineer

San Francisco, CA · On-site

$161K - $175K/yr

About the Deep Learning Team The Deep learning team's work is at the crux of Hayden AI's solutions ... Bachelors or Masters in Computer Science or related field * Nice to Have : Experience working in ...

Machine Learning Scientist

Culver City, CA

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Overview We're looking for a talented and intensely curious Machine Learning Scientist with deep expertise in building and deploying production machine learning models, particularly reinforcement ...

Audio Deep Learning Engineer

San Bruno, CA · On-site

  • Medical

  • Dental

  • Vision

  • Retirement

About the Role As a Deep Learning Engineer, you will: * Design, develop, and deploy deep-learning ... A background in Computer Science, Mathematics, Electrical Engineering or a related field (BS, MS ...

This role develops and deploys deep learning models across digital pathology, genomics ... You will collaborate with scientists, pathologists, bioinformaticians, and software engineers to ...

Deep Learning Research Scientist

San Francisco, CA · On-site +1

$250K - $510K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Complex multimodal reinforcement learning environments. * High-performance RPC servers for ... We view AI research as an empirical science, which has as much in common with physics and biology ...

Machine Learning Scientist

Culver City, CA · On-site

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

For more information about Spotter, please visit Overview We're looking for a talented and intensely curious Machine Learning Scientist with deep expertise in building and deploying production ...

Applied Scientist, AI

Seattle, WA · On-site

$195K - $205K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Participate in the research, development, and refinement of AI and deep learning models and ... Collaborate with cross-functional teams including data scientists and search/information retrieval ...

Applied Scientist, AI

Seattle, WA

$195K - $205K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Participate in the research, development, and refinement of AI and deep learning models and ... Collaborate with cross-functional teams including data scientists and search/information retrieval ...

Applied Scientist, AI

Seattle, WA · On-site

$195K - $205K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Participate in the research, development, and refinement of AI and deep learning models and ... Collaborate with cross-functional teams including data scientists and search/information retrieval ...

Currently pursuing a Masters or PhD program in Computer Science, Machine Learning, Robotics, or similar field * Strong background in deep learning, with experience in model design, training and ...

Showing results 41-60

Deep Learning Scientist information

See salary details

$37.5K

$122.7K

$196.5K

How much do deep learning scientist jobs pay per year?

As of Aug 14, 2026, the average yearly pay for deep learning scientist 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 are the key skills and qualifications needed to thrive as a deep learning scientist?

To thrive as a Deep Learning Scientist, you need a solid background in machine learning, statistics, and programming, often supported by an advanced degree in computer science or a related field. Familiarity with deep learning frameworks like TensorFlow or PyTorch, experience with cloud computing platforms, and proficiency in Python are typically required. Strong problem-solving skills, creativity, and the ability to communicate complex ideas clearly set outstanding candidates apart. These capabilities are essential for developing innovative AI solutions, interpreting results, and collaborating effectively in multidisciplinary teams.

What is the difference between Deep Learning Scientist vs Machine Learning Engineer?

AspectDeep Learning ScientistMachine Learning Engineer
Required CredentialsMaster's or PhD in Computer Science, Data Science, or related fields; strong background in deep learning frameworksBachelor's or Master's in Computer Science or related fields; proficiency in machine learning algorithms and software engineering
Work EnvironmentResearch-focused, experimental, often in R&D teamsDevelopment and deployment-focused, working on production systems
Employer & Industry UsageTech companies, research labs, AI startupsTech firms, finance, healthcare, and industries deploying ML models

While both roles involve machine learning, Deep Learning Scientists focus on developing advanced neural network models and research, whereas Machine Learning Engineers implement, optimize, and deploy these models in real-world applications.

What is a deep learning scientist?

Deep Learning Scientists are experts who design, develop, and implement advanced machine learning models inspired by the structure and function of the brain, known as artificial neural networks. They work with large datasets to train algorithms that can recognize patterns, make predictions, and solve complex problems in areas such as image recognition, natural language processing, and autonomous systems. Deep Learning Scientists often collaborate with software engineers, data scientists, and domain specialists to deploy models in real-world applications like healthcare, finance, and self-driving cars.

What are some typical challenges faced when working as a deep learning scientist, and how can they be addressed?

Deep Learning Scientists often encounter challenges such as managing large datasets, tuning complex model architectures, and ensuring reproducibility of experiments. Handling these issues requires strong skills in data preprocessing, familiarity with version control systems, and experience with frameworks like TensorFlow or PyTorch. Collaborating closely with cross-functional teams—including data engineers, software developers, and domain experts—can also help in overcoming technical and project-related obstacles. Continuous learning and staying updated with the latest research is essential to excel in this rapidly evolving field.
More about Deep Learning Scientist jobs

What cities are hiring for Deep Learning Scientist jobs?

Cities with the most Deep Learning Scientist job openings:

What states have the most Deep Learning Scientist jobs?

States with the most job openings for Deep Learning Scientist jobs include:

Infographic showing various Deep Learning Scientist 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 $122,738 per year, or $59 per hour.

Senior Machine Learning Scientist

Expedia

Seattle, WA • Remote

$104K - $142K/yr

Full-time

Medical, Dental, Vision, PTO

Re-posted 28 days ago


Expedia Group rating

6.9

Company rating: 6.9 out of 10

Based on 25 frontline employees who took The Breakroom Quiz

8th of 11 rated travel agencies


Job description

At Expedia Group, we help travelers explore the world, one journey at a time. As a global travel company powered by passionate people, trusted partnerships, and leading technology, we connect travelers, partners, and advertisers through our consumer brands, B2B network, and travel advertising business.


Here, you'll do meaningful work that helps millions of people discover, book, and experience travel with more ease, confidence, and joy. Our five Behaviors-Traveler First, Think Big, Operate with Excellence, Ownership Mindset, and Succeed Together-help foster a supportive environment where people can grow their careers and have the flexibility, benefits, and support to do their best work. Join us and build for travelers everywhere.

Senior Machine Learning Scientist

The Senior Machine Learning Scientist is responsible for building and evaluating GenAI- and LLM-powered solutions and AI agents that improve post-booking customer experience, including recommendations, customer service, and trip management. Owns end-to-end ML and GenAI projects-from problem framing and data preparation through model/agent design, orchestration, deployment, and continuous evaluation. Applies deep expertise in applied ML, Generative AI, and rigorous experimentation to design robust evaluation frameworks (A/B tests, offline metrics, qualitative assessments) that ensure agents are safe, effective, and aligned with business goals. Partners closely with product, engineering, and operations while mentoring junior scientists and helping define best practices for AI agent development and evaluation.

Are you passionate about using machine learning to improve customer experience at scale? Would you like to work in the fast-paced, competitive, customer-focused, and data-rich world of online travel?

Our Machine Learning and Data Science team is growing. We are looking for a Senior Machine Learning Scientist to help tackle some of the most complex customer experience problems in the travel domain. You will develop state-of-the-art machine learning and AI solutions to power and enhance the customer experience across highly complex postbooking recommendations, customer service, and trip management use cases.

You will tackle substantial technical challenges, from inference problems on long-tail traveler data to multi-objective optimization in a highly dynamic, operationally complex customer service environment. Your passion for the craft of machine learning, causal inference, and Generative AI will unlock tangible growth for our business by exploiting rich datasets and building effective solutions for travelers and our partners.

This is your opportunity to build core algorithms that help Expedia Group's Post Booking organization bring context and intelligence to every step of the traveler journey and redefine what service excellence in travel can be. We are looking for a hands-on senior scientist who can independently drive impactful projects, mentor others, and collaborate closely with partners to make travel more seamless for millions of customers and partners worldwide.

In this role, you will:

Design & Implement ML Solutions

  • Own the end-to-end ML lifecycle for medium-to-large projects: from problem framing and ideation through research, prototyping, deployment, and post-launch monitoring.

  • Design robust, scalable ML systems (batch and/or streaming) in partnership with engineering, including data pipelines, feature computation, and model serving.

  • Translate ambiguous business problems into well-defined ML problems with clear success metrics and validation strategies.

Applied Machine Learning & Data Science

  • Develop, evaluate, and iterate on supervised, unsupervised, and deep learning models for prediction, recommendation, and optimization.

  • Apply causal inference and experimental design (A/B testing) to accurately measure impact and guide decision-making.

  • Read and apply relevant academic and industry research to improve model architectures, training strategies, and evaluation methods.

  • Contribute to defining best practices for experimentation and modeling within the team; help raise the technical bar for ML development.

Generative AI & Advanced Techniques

  • Build and iterate on models and applications leveraging GenAI / LLM technologies (e.g., OpenAI, Hugging Face, Anthropic, Gemini) for customer support, content generation, and workflow automation.

  • Use prompting, retrieval-augmented generation, and tool/function-calling patterns to integrate LLMs into production systems.

  • Explore and prototype advanced ML techniques (e.g., reinforcement learning, sequence modeling, transformers) where they can provide clear business value.

Statistics, Experimentation & Model Design

  • Design end-to-end modeling approaches, including data selection, feature engineering, algorithm choice, training procedures, and evaluation.

  • Apply statistical rigor in analyzing experiments and observational data; quantify uncertainty, trade-offs, and model risk.

  • Define and monitor offline and online metrics that faithfully reflect business goals (e.g., customer satisfaction, cost-to-serve, operational efficiency).

Collaboration, Communication & Visualization

  • Partner closely with product managers, engineers, analysts, and operations to understand requirements, define roadmaps, and align on priorities.

  • Communicate complex technical concepts in a clear, concise way to technical and non-technical stakeholders.

  • Build intuitive dashboards and visualizations to explain model behavior, experiment results, and business impact.

Stakeholder & Project Management

  • Lead cross-functional projects involving multiple partners (e.g., product, engineering, operations), driving them from conception to measurable impact.

  • Manage project scope, timelines, and communication, proactively surfacing risks and trade-offs.

  • Mentor junior scientists and engineers on modeling approaches, experimentation, and analytical problem solving.

Experience & Qualifications:

Experience & Education

  • PhD in a quantitative field (e.g., Computer Science, Statistics, Mathematics, Physics, Economics, Operations Research) and ~3+ years of industry experience;
    or Master's degree in a quantitative field with ~5+ years of relevant industry experience.

  • Proven track record of building and deploying ML models that meaningfully impact business metrics in a production environment.

Functional & Technical Skills

Applied ML & Statistics

  • Strong knowledge of machine learning theory and practice (e.g., supervised learning, representation learning, ranking/recommendation, deep learning).

  • Solid grounding in statistics, experimental design (A/B testing), and basic causal inference; comfortable designing and analyzing online experiments.

  • Able to design end-to-end ML solutions: frame the problem, choose data sources, select algorithms, define evaluation strategies, and iterate based on results.

Engineering & Tooling

  • Strong programming skills in Python and its data/ML ecosystem (e.g., pandas, scikit-learn, PyTorch/TensorFlow, PySpark), plus proficiency in SQL.

  • Experience working with cloud-based data/compute platforms and modern data/ML tooling (e.g., Spark, Airflow, feature stores, model serving frameworks).

  • Follow software engineering best practices (version control, code reviews, testing, documentation) and contribute to shared libraries and tooling.

Generative AI & Advanced Methods

  • Hands-on experience using GenAI / LLM APIs (e.g., OpenAI, Hugging Face, Anthropic, Gemini) in prototypes or production is highly desired.

  • Familiarity with concepts like prompt engineering, retrieval-augmented generation, function/tool calling, and evaluation of LLM-based systems.

  • Experience with reinforcement learning, bandits, or other advanced ML techniques is a plus.

Problem Solving & Communication

  • First-principles problem solver: able to decompose ambiguous problems, identify key assumptions, and design pragmatic, iterative solutions.

  • Excellent written and verbal communication skills; able to tell a compelling story with data and models and influence decisions.

  • Collaborative and customer-obsessed, with the ability to balance scientific rigor and engineering pragmatism in a product environment.

Highly Desired Experience

  • Domain experience in customer service, recommendations, personalization, or e-commerce applications.

  • Experience building ML systems for operational decision-making (e.g., contact routing, triage, capacity/effort prediction, workflow optimization).

  • Experience mentoring other scientists or engineers and contributing to technical culture (e.g., brown bags, tech talks, documentation, best practices).

If you're excited about building impactful ML and AI solutions that improve how millions of travelers are served every day, we'd love to hear from you.

The total cash range for this position in Seattle is $173,000.00 to $242,500.00. Employees in this role have the potential to increase their pay up to $277,000.00, which is the top of the range, based on ongoing, demonstrated, and sustained performance in the role. The total cash range for this position in San Jose is $187,000.00 to $261,500.00. Employees in this role have the potential to increase their pay up to $299,000.00, which is the top of the range, based on ongoing, demonstrated, and sustained performance in the role.

Starting pay for this role will vary based on multiple factors, including location, available budget, and an individual's knowledge, skills, and experience. Pay ranges may be modified in the future.


Benefits and perks

Expedia Group offers benefits and perks designed to support employees and their families, including medical, dental, and vision coverage, paid time off, an Employee Assistance Program, wellness and travel reimbursement, travel discounts, and International Airlines Travel Agent Network (IATAN) membership. Learn more about life at Expedia Group at https://careers.expediagroup.com/life.


Accommodation requests

Expedia Group is committed to providing an inclusive and accessible recruiting experience. If you need an accommodation or adjustment due to a disability during the application or recruiting process, please submit a request at https://expedia.service-now.com/askeg?id=job_accommodation.


About Expedia Group

Expedia Group includes three flagship consumer brands - Expedia, Hotels.com, and Vrbo - along with a leading B2B travel business and travel advertising offerings. Across our brands and business, we help travelers explore the world with confidence and ease.


Important notice

Employment opportunities and job offers at Expedia Group will always come from Expedia Group's Talent Acquisition and hiring teams. Never share sensitive personal information unless you are confident of the recipient. Expedia Group does not extend job offers via email or messaging tools to individuals with whom we have not made prior contact. Our email domain is @expediagroup.com. The official place to find and apply for roles is https://careers.expediagroup.com/jobs/.


Equal Opportunity

Expedia is committed to creating an inclusive work environment with a diverse workforce. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, veteran status, or any other characteristic protected by law. This employer participates in E-Verify. The employer will provide the Social Security Administration (SSA) and, if necessary, the Department of Homeland Security (DHS) with information from each new employee's I-9 to confirm work authorization.

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