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Research Machine Learning Federated Learning Jobs in Frederick, MD

Axle

AI/ML Scientist/Developer

Frederick, MD · On-site

... research and biomedical informatics. They are seeking an AI/ML Scientist/Developer to develop ... Responsibilities : • The successful candidate will design and implement machine learning models ...

Axle

AI/ML Scientist/Developer

Frederick, MD · On-site

... research, biomedical informatics, and data science applications. They are seeking an AI/ML ... Responsibilities : • The successful candidate will design and implement machine learning models ...

Merck Group

Data Scientist

Rockville, MD · On-site

$95K - $142K/yr

Design, build, and refine machine learning and artificial intelligence models for marketing, operation, R&D, and supply chain optimization. * Work closely with business experts, lab operation ...

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All JobsResearch Machine Learning Federated Learning JobsResearch Machine Learning Federated Learning Jobs in Frederick, MD

Research Machine Learning Federated Learning information

See Frederick, MD salary details

$25.4K

$42.3K

$87.5K

How much do research machine learning federated learning jobs pay per year?

As of Aug 17, 2026, the average yearly pay for research machine learning federated learning in Frederick, MD is $42,340.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,300.00 and $45,700.00 per year, depending on experience, location, and employer.

What is a researcher in machine learning federated learning?

A Researcher in Machine Learning Federated Learning is a professional who investigates and develops methods to train machine learning models across multiple decentralized devices or servers, while keeping data localized and private. Their work focuses on improving algorithms, ensuring data privacy, and addressing challenges related to distributed learning, communication efficiency, and model accuracy. They often collaborate with other researchers, publish findings, and contribute to advancing technologies that make it possible to use sensitive data for AI without compromising privacy.

What are the key skills and qualifications needed to thrive as a researcher in machine learning federated learning?

To thrive as a Researcher in Machine Learning Federated Learning, you need a strong background in computer science, mathematics, and machine learning, typically supported by a relevant advanced degree (e.g., PhD or MSc). Familiarity with Python, TensorFlow, PyTorch, and distributed computing frameworks, as well as knowledge of privacy-preserving techniques and relevant research publications, is essential. Excellent analytical thinking, problem-solving abilities, and clear scientific communication are key soft skills for success in collaborative research environments. These competencies are vital to drive innovation, rigorously evaluate federated learning approaches, and advance privacy-preserving AI technologies.

What are some common challenges faced when implementing federated learning in a research environment?

One of the primary challenges in research-focused federated learning roles is ensuring data privacy and security while maintaining model performance across distributed devices. Researchers must also address issues such as handling heterogeneous data sources, communication bottlenecks between nodes, and the complexity of debugging decentralized systems. Collaborating with cross-functional teams—such as data engineers, privacy experts, and domain specialists—is vital to overcome these hurdles and drive successful outcomes. Staying updated with the latest advancements and actively contributing to open-source initiatives can also help researchers address these evolving challenges.

What is the difference between Research Machine Learning Federated Learning vs Data Scientist?

AspectResearch Machine Learning Federated LearningData Scientist
CredentialsAdvanced degrees in CS, ML, or related fields; research experienceBachelor's or Master's in Data Science, Statistics, or related fields
Work EnvironmentResearch labs, academic institutions, tech companies focusing on privacy-preserving MLBusiness environments, analytics teams, data-driven departments
Industry UsageDeveloping federated algorithms, privacy-preserving ML modelsData analysis, modeling, reporting, and insights generation

Research Machine Learning Federated Learning specialists focus on developing privacy-preserving algorithms across distributed data sources, often in research or R&D settings. Data Scientists analyze and interpret data to inform business decisions. While both roles require strong ML knowledge, federated learning roles emphasize distributed systems and privacy, whereas Data Scientists focus on data analysis and visualization.

What are popular job titles related to Research Machine Learning Federated Learning jobs in Frederick, MD?

For Research Machine Learning Federated Learning jobs in Frederick, MD, the most frequently searched job titles are:

What job categories do people searching Research Machine Learning Federated Learning jobs in Frederick, MD look for?

The top searched job categories for Research Machine Learning Federated Learning jobs in Frederick, MD are:

What cities near Frederick, MD are hiring for Research Machine Learning Federated Learning jobs?

Cities near Frederick, MD with the most Research Machine Learning Federated Learning job openings:

Research Machine Learning Federated Learning jobs near you

Senior Data Scientist I - QuantumBlack, AI by McKinsey

McKinsey & Company

Lisbon, MD • On-site

Full-time

Re-posted 6 days ago

McKinsey & Company rating

8.5

Company rating: 8.5 out of 10

Based on 22 frontline employees who took The Breakroom Quiz

20th of 72 rated business consultants

Job description

Do you want to do work that matters, alongside supportive leaders who will help you grow faster than you ever thought possible? Are you a creative problem-solver who is energized by challenges? You've come to the right place.
YOUR IMPACT
You'll lead the development of cutting-edge AI and machine learning solutions that tackle some of the most complex business challenges across industries-delivering measurable impact at scale.
You will leverage the latest advances in deep learning, reinforcement learning, and AI to uncover insights and improve business performance. You will mentor other data scientists, shape QuantumBlack, AI by McKinsey's R&D roadmap, and identify high-potential machine learning initiatives for industry application. Working closely with data engineers, machine learning engineers, and designers, you will build end-to-end analytics solutions that create real-world impact.
Your work will transform industries. By leveraging advanced AI techniques and collaborating with industry leaders, you will help clients gain a competitive edge, solve critical challenges, and achieve lasting improvements in their operations.
You will be based in Lisbon and collaborate closely with data scientists, data engineers, machine learning engineers, designers, and product managers around the world. Together, you'll work on interdisciplinary projects to solve complex business challenges across a range of industries. Collaborating with QuantumBlack, AI by McKinsey leadership, client executives, and technical experts, you will lead the development and application of cutting-edge machine learning and AI solutions to drive measurable business impact.
You'll thrive in an unparalleled environment for growth. You'll work on high-impact projects, connect technology with business value, and collaborate with inspiring multidisciplinary teams, gaining a holistic perspective of AI's transformative potential while advancing as a technologist and leader.
YOUR GROWTH
Driving lasting impact and building long-term capabilities with our clients is not easy work. You are the kind of person who thrives in a high performance/high reward culture - doing hard things, picking yourself up when you stumble, and having the resilience to try another way forward.
In return for your drive, determination, and curiosity, we'll provide the resources, mentorship, and opportunities you need to become a stronger leader faster than you ever thought possible. Your colleagues-at all levels-will invest deeply in your development, just as much as they invest in delivering exceptional results for clients. Every day, you'll receive apprenticeship, coaching, and exposure that will accelerate your growth in ways you won't find anywhere else.
When you join us, you will have:
  • Continuous learning: Our learning and apprenticeship culture, backed by structured programs, is all about helping you grow while creating an environment where feedback is clear, actionable, and focused on your development. The real magic happens when you take the input from others to heart and embrace the fast-paced learning experience, owning your journey.
  • A voice that matters: From day one, we value your ideas and contributions. You'll make a tangible impact by offering innovative ideas and practical solutions, all while upholding our unwavering commitment to ethics and integrity. We not only encourage diverse perspectives, but they are critical in driving us toward the best possible outcomes.
  • Global community: With colleagues across 65+ countries and over 100 different nationalities, our firm's diversity fuels creativity and helps us come up with the best solutions for our clients. Plus, you'll have the opportunity to learn from exceptional colleagues with diverse backgrounds and experiences.
  • World-class benefits: On top of a competitive salary (based on your location, experience, and skills), we provide a comprehensive benefits package to enable holistic well-being for you and your family.

YOUR QUALIFICATIONS AND SKILLS
  • Bachelors, Masters or PhD level in a discipline such as: computer science, machine learning, applied statistics, mathematics, engineering or artificial intelligence
  • 5+ years of deep technical experience in distributed computing, machine learning, and statistics related work
  • Programming experience in languages such as: Python, R, Scala, SQL
  • Proven application of advanced analytical, data science and statistical methods in the commercial world
  • Knowledge of distributed computing or NoSQL technologies is a bonus
  • Client-facing skills e.g. working in close-knit teams on topics such as data warehousing, machine learning
  • While we advocate for using the right tech for the right task, we often leverage the following technologies: Python, PySpark, the PyData stack, SQL, Airflow, Databricks, our own open-source data pipelining framework called Kedro, Dask/RAPIDS, container technologies such as Docker and Kubernetes, cloud solutions such as AWS, GCP, and Azure, and more.
  • Exceptional time management to meet your responsibilities in a complex and largely autonomous work environment.
  • Demonstrated leadership (thought leadership or people leadership e.g. managed project teams or direct reports)
  • Willingness to travel
  • Strong presentation and communication skills, both verbal and written, in English and Portuguese, with the ability to adjust your style to suit different perspectives and seniority levels

Please review the additional requirements regarding essential job functions of McKinsey colleagues.
Our unwavering commitment to integrity drives everything we do, guiding us to always act in the best interests of our clients, our people, and the communities we serve.

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