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Senior Machine Learning Scientist Jobs in Delaware

... a Senior Applied Scientist, Generative AI, you will design, build, and deploy generative and ... Develop machine learning and generative AI models that ship as customer-facing product features

Senior Manager, Statistical Modeling

Newark, DE · On-site

$85.10K - $104.60K/yr

What You'll Contribute The Senior Manager, Statistical Modeling will be responsible for developing ... Stay current with advancements in machine learning and data science, and evaluate new tools and ...

Senior Manager, Statistical Modeling

Newark, DE · On-site

$85.30K - $105K/yr

What You'll Contribute The Senior Manager, Statistical Modeling will be responsible for developing ... Stay current with advancements in machine learning and data science, and evaluate new tools and ...

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Senior Machine Learning Scientist information

See Delaware salary details

$66.6K

$110.6K

$164.6K

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

As of May 29, 2026, the average yearly pay for senior machine learning scientist in Delaware is $110,640.00, according to ZipRecruiter salary data. Most workers in this role earn between $91,600.00 and $125,100.00 per year, depending on experience, location, and employer.

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

To thrive as a Senior Machine Learning Scientist, you need expertise in machine learning algorithms, statistical analysis, programming (usually in Python or R), and an advanced degree (often a Ph.D.) in a quantitative field. Experience with tools such as TensorFlow, PyTorch, scikit-learn, cloud platforms, and version control systems is typically expected, along with knowledge of deploying models in production environments. Exceptional problem-solving, communication, and leadership skills help you translate complex data insights into actionable business solutions and mentor junior team members. These skills are crucial for developing innovative models, ensuring robust deployment, and driving impactful data-driven decisions.

What are some common challenges Senior Machine Learning Scientists face when deploying models to production environments?

Senior Machine Learning Scientists often encounter challenges such as ensuring model scalability, maintaining model performance over time, and addressing data drift once models are deployed to production. Collaborating closely with engineering and operations teams is crucial to streamline deployment pipelines and monitor models for real-world reliability. It’s also important to communicate findings and potential risks to stakeholders, and to regularly update models based on new data or business requirements. These aspects make strong cross-functional teamwork and problem-solving skills essential in this role.

What are Senior Machine Learning Scientists?

Senior Machine Learning Scientists are experienced professionals who design, develop, and implement advanced machine learning models to solve complex business or research problems. They are responsible for leading projects, mentoring junior team members, and staying updated on the latest AI and data science technologies. Their work often involves analyzing large datasets, selecting the right algorithms, and optimizing model performance for real-world applications. In addition to technical expertise, they often collaborate cross-functionally to align machine learning solutions with organizational goals.

What is the difference between Senior Machine Learning Scientist vs Data Scientist?

AspectSenior Machine Learning ScientistData Scientist
CredentialsMaster's or PhD in CS, ML, or related fieldBachelor's or Master's in CS, Statistics, or related field
Work EnvironmentFocus on developing ML models, algorithms, and researchData analysis, visualization, and business insights
Industry UsageUsed in AI-driven companies, tech firms, research labsCommon across industries for data analysis and reporting

While both roles involve working with data, Senior Machine Learning Scientists focus on developing advanced ML models and algorithms, often requiring research and deep technical expertise. Data Scientists typically analyze data to generate insights and support decision-making. The roles overlap but differ mainly in technical depth and focus area.

What are popular job titles related to Senior Machine Learning Scientist jobs in Delaware? For Senior Machine Learning Scientist jobs in Delaware, the most frequently searched job titles are:
What cities in Delaware are hiring for Senior Machine Learning Scientist jobs? Cities in Delaware with the most Senior Machine Learning Scientist job openings:
Infographic showing various Senior Machine Learning Scientist job openings in Delaware as of May 2026, with employment types broken down into 1% Internship, 26% Full Time, 54% Part Time, 15% Contract, and 4% Nights. Highlights an 64% Physical, 10% Hybrid, and 26% Remote job distribution, with an average salary of $110,640 per year, or $53.2 per hour.
Senior Applied Scientist

Senior Applied Scientist

Relativity

Wilmington, DE • On-site, Remote

Other

Medical, Retirement

Posted 6 days ago


Job description

Posting Type

Remote/Hybrid

Job Overview

WHO WE ARE
Relativity is a leading legal data intelligence company building technology that helps users organize data, discover the truth, and act on it with confidence. Our AI-powered, cloud platform, RelativityOne, transforms massive volumes of complex information into actionable insights for litigation, investigations, regulatory inquiries, data breach responses, and other high-stakes legal work where accuracy, trust, and accountability are critical.
Every year, the global justice system benefits from insights generated by Relativity AI across billions of documents. We are just getting started on our journey to use AI to improve the outcome of every discovery, investigation, and analysis performed on our platform.
At Relativity, we develop AI guided by our AI Principles. These principles ensure we build AI with clear purpose, empower customers with transparency and control, treat fairness and privacy as first principles, protect customer data by design, and act with a high standard of responsibility and accountability.
WHAT WE DO
Relativity's AI organization is focused on exploration, experimentation, and turning cutting-edge research into real-world impact. We believe innovation requires experimentation, learning, and iteration. Our teams experiment, evaluate, ship, and learn continuously while maintaining a strong commitment to responsible AI.
Applied Science Team
The Applied Science team operates at the core of Relativity's AI development. Our team includes specialists with advanced postgraduate training and deep experience building and operating machine learning models at scale. We work closely with engineering, product, design, data engineering, machine learning operations, and LLM engineering teams to translate complex AI research into production-ready features used by legal professionals around the world.

Job Description and Requirements

ABOUT THE ROLE

As a Senior Applied Scientist, Generative AI, you will design, build, and deploy generative and machine learning models that power Relativity's next generation of AI-driven product capabilities. You will collaborate closely with applied scientists, engineers, product managers, and designers to build models that help legal professionals organize data, discover the truth, and act on it with confidence.

This role balances research, development, and operational responsibility. You will contribute to Relativity's portfolio of transformational generative AI technologies while adhering to our responsible AI principles and ensuring models perform reliably in real-world, high-stakes environments.

WHAT YOU'LL DO

  • Develop machine learning and generative AI models that ship as customer-facing product features
  • Collaborate closely with engineers to write production-quality code and contribute across the full model deployment lifecycle
  • Design and evaluate models that operate at very large scale, including search and retrieval systems spanning hundreds of millions to billions of documents
  • Contribute to internal standards, processes, and tooling for building, evaluating, and deploying generative AI systems
  • Partner with Product and Data teams to assemble, curate, and synthesize datasets for model development and evaluation
  • Conduct rigorous experimentation, model evaluation, and iteration to improve model quality, explainability, safety, and performance
  • Collaborate across AI, engineering, and product teams to ensure models integrate effectively into larger systems
  • Apply Relativity's AI Principles to ensure responsible, fair, secure, and transparent AI development
  • Communicate complex data science and machine learning concepts clearly and effectively to collaborators with diverse technical backgrounds

WHAT WE'RE LOOKING FOR

Required

  • Experience building search or retrieval systems operating at the scale of hundreds of millions of documents
  • Experience developing and applying generative AI models as part of larger, domain-specific systems
  • Experience across the full machine learning lifecycle, including experimentation, evaluation, deployment, and iteration
  • Experience working in containerized environments using Kubernetes-based tooling and workflows
  • Interest in or experience with the legal industry, eDiscovery, or the broader justice system
  • Strong programming ability in a language such as Python
  • Comfort working in UNIX-based environments using command-line tools
  • Ability to communicate complex data science concepts thoughtfully and inclusively to a wide range of stakeholders

Preferred

  • Master's degree in Computer Science or a quantitative field plus 2 years of relevant industry experience
  • OR Ph.D. in Computer Science or a quantitative field
  • OR the equivalent of 5 years of relevant academic and/or industry experience
  • Experience building and deploying systems that leverage large language models
  • Experience contributing to shared data science or ML engineering standards, tooling, or best practices

WHY WE COULD BE A GREAT FIT

Impactful Mission

  • Your work directly contributes to improving outcomes across the global justice system by helping customers uncover critical insights in massive, complex datasets.

AI at Real Scale

  • You'll work on some of the largest and most complex AI systems in the legal technology market, operating at significant data and computational scale.

Growth and Collaboration

  • You'll collaborate closely with experienced applied scientists, engineers, and product leaders while continuing to grow your expertise in generative AI and production machine learning systems.

Responsible AI Culture

  • You'll be part of an organization deeply committed to building AI that is ethical, transparent, secure, and accountable.

Inclusive Environment

  • We value diverse perspectives, backgrounds, and ways of thinking, and believe they make our teams and products stronger.

Compensation and Benefits

  • Competitive compensation, health and retirement benefits, discretionary time off (DTO), parental leave for primary and secondary caregivers, company-wide breaks, wellness resources, and an equity program.

Relativity is committed to competitive, fair, and equitable compensation practices.

This position is eligible for total compensation which includes a competitive base salary, an annual performance bonus, and long-term incentives.

The expected salary range for this role is between following values:

$146,000 and $218,000

The final offered salary will be based on several factors, including but not limited to the candidate's depth of experience, skill set, qualifications, and internal pay equity. Hiring at the top end of the range would not be typical, to allow for future meaningful salary growth in this position.

Required Skills:

Algorithms, C++ Programming Language, Computer Vision, Data Science, Deep Learning, Machine Learning (ML), Natural Language, Python (Programming Language), Researching, Statistical Models