1

Research Machine Learning Federated Learning Jobs in Tennessee

Senior Machine Learning Engineer

Nashville, TN · On-site

$100K - $138K/yr

Research, evaluate, and select appropriate machine learning approaches and architectures based on the problem definition * Supervised, unsupervised, and reinforcement learning * Neural networks ...

Research, evaluate, and select appropriate machine learning approaches and architectures based on the problem definition * Supervised, unsupervised, and reinforcement learning * Neural networks ...

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for online Machine Learning tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the ...

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for online Machine Learning tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the ...

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for online Machine Learning tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the ...

Machine Learning Tutor

Memphis, TN · Remote

$18 - $40/hr

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for online Machine Learning tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the ...

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for online Machine Learning tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the ...

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for online Machine Learning tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the ...

About Us We are AI researchers and builders who understand how to curate data and RL environments ... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ...

About Us We are AI researchers and builders who understand how to curate data and RL environments ... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ...

About Us We are AI researchers and builders who understand how to curate data and RL environments ... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ...

About Us We are AI researchers and builders who understand how to curate data and RL environments ... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ...

About Us We are AI researchers and builders who understand how to curate data and RL environments ... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ...

Senior Machine Learning Engineer

Franklin, TN · Remote

$118K - $155K/yr

Use yourexpertisein machine learning, exploratory data analysis, and software engineering to ... Research, implement, and launch new model architectures that drive business impact. Partner and ...

next page

Showing results 1-20

Research Machine Learning Federated Learning information

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

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 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 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 Tennessee? For Research Machine Learning Federated Learning jobs in Tennessee, the most frequently searched job titles are:
What job categories do people searching Research Machine Learning Federated Learning jobs in Tennessee look for? The top searched job categories for Research Machine Learning Federated Learning jobs in Tennessee are:
What cities in Tennessee are hiring for Research Machine Learning Federated Learning jobs? Cities in Tennessee with the most Research Machine Learning Federated Learning job openings:

SR DIRECTOR, MACHINE LEARNING

∙ Elijah House Foundation

Goodlettsville, TN • On-site

$180 - $280/hr

Other

Posted yesterday

New


Job description

Company Overview

General Summary: This role exists to build, scale, and operationalize Dollar General’s enterprise machine learning capabilities that directly drive measurable business outcomes. The Senior Director owns the ML strategy, platforms, and teams required to move from isolated models to production-grade, governed, reusable ML systems. This leader ensures ML investments are aligned to enterprise priorities, value realization, and responsible AI standards.

Job Details Duties and Responsibilities
  • Lead enterprise machine learning strategy spanning applied ML, MLOps, experimentation, and platform capabilities aligned to business priorities.
  • Build, mentor, and scale high-performing ML engineering and data science leaders across centralized and embedded delivery models
  • Own end-to-end lifecycle of ML systems from problem framing and modeling through deployment, monitoring, and continuous optimization
  • Partner with product, IT, security, legal, and business leaders to ensure governed, responsible, and scalable ML adoption.
  • Establish standards for model evaluation, experimentation, monitoring, and value measurement tied to financial and operational impact
Qualifications Knowledge, Skills and Abilities
  • Deep expertise in machine learning systems, model development, and production ML architectures
  • Strong understanding of MLOps, model monitoring, experimentation, and CI/CD for ML
  • Proven ability to translate business problems into scalable ML solutions with measurable impact
  • Experience leading senior technical managers and principal-level engineers
  • Strong judgment around responsible AI, model risk, data privacy, and governance
  • Ability to influence executive stakeholders and align cross-functional teams
  • Experience operating ML platforms in cloud-native environments
  • Excellent communication skills bridging technical and non-technical audiences
Work Experience and/or Education
  • Bachelor’s degree in Computer Science, Engineering, Mathematics, or related field
  • Advanced degree (Master’s / MBA) in a quantitative or AI-related discipline preferred
  • 10+ years of experience in machine learning, data science, or applied AI roles
  • 5+ years leading ML engineering or data science teams at scale
  • Demonstrated experience deploying and operating production ML systems

Experience in retail, e-commerce, supply chain, or large-scale consumer data environments preferred

#J-18808-Ljbffr