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Research Machine Learning Federated Learning Jobs in Texas

We're looking for a Machine Learning Engineer to drive our machine learning strategy. We are ... Strong understanding of the state of the art research in robot learning (behavior cloning for ...

Machine Learning Engineer

Austin, TX · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Machine Learning Engineer Remote with occasional travel to Silver Spring, MD About @Orchard ... Experience supporting NOAA, other federal agencies, academic research organizations, or marine ...

New

Senior Manager, Machine Learning

Austin, TX · On-site

  • Medical

  • Dental

  • Vision

  • Retirement

As a key member of the team, you will be responsible for the development of a team to execute on innovative concepts, research, predictive modeling, and machine learning algorithms. You will serve as ...

Senior Manager, Machine Learning

Austin, TX · On-site

$120 - $160/hr

  • Medical

  • Dental

  • Vision

  • Retirement

As a key member of the team, you will be responsible for the development of a team to execute on innovative concepts, research, predictive modeling, and machine learning algorithms. You will serve as ...

Machine Learning Engineer

Houston, TX · On-site

$109K - $131K/yr

  • Medical

  • Life

  • Retirement

  • PTO

As a Machine Learning Engineer in our Data & Analytics Platforms team specializing in data and analytics solutions , you will work with a cross-functional team whoseobjectiveis todeliversolutions ...

Machine Learning Engineer II

Richardson, TX · On-site

$119K - $190K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

As a Machine Learning Engineer II, you will be a key contributor throughout the machine learning lifecycle, from data preparation and model development to deployment and monitoring. You will have the ...

Machine Learning Tutor

Carrollton, TX · 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 ...

Machine Learning Tutor

Dallas, TX · 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 ...

Machine Learning Tutor

Round Rock, TX · 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 ...

Machine Learning Tutor

Fort Worth, TX · 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 ...

Machine Learning Tutor

Lubbock, TX · 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 ...

Machine Learning Tutor

Arlington, TX · 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 ...

Showing results 41-60

Research Machine Learning Federated Learning information

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 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 job categories do people searching Research Machine Learning Federated Learning jobs in Texas look for?

The top searched job categories for Research Machine Learning Federated Learning jobs in Texas are:

What cities in Texas are hiring for Research Machine Learning Federated Learning jobs?

Cities in Texas with the most Research Machine Learning Federated Learning job openings:

Staff Machine Learning Engineer

TalentPros.AI

Austin, TX

$120K - $550K/yr

Full-time

Re-posted 21 days ago


Job description

About the Team

We are at the forefront of artificial intelligence, driving innovation and shaping the future with cutting-edge research. Our mission is to ensure that AI's benefits reach everyone. We are looking for visionary Machine Learning Engineers to join our Applied Group, where you'll transform groundbreaking research into real-world applications that can change industries, enhance human creativity, and solve complex problems.


About the Role

As a Machine Learning Engineer in our Applied Group, you will have the opportunity to work with some of the brightest minds in AI. You'll contribute to deploying state-of-the-art models in production environments, helping turn research breakthroughs into tangible solutions. If you're excited about making AI technology accessible and impactful, this role is your chance to make a significant mark.

In this role, you will:

  • Innovate and Deploy: Design and deploy advanced machine learning models that solve real-world problems. Bring our research from concept to implementation, creating AI-driven applications with a direct impact.
  • Collaborate with the Best: Work closely with researchers, software engineers, and product managers to understand complex business challenges and deliver AI-powered solutions. Be part of a dynamic team where ideas flow freely and creativity thrives.
  • Optimize and Scale: Implement scalable data pipelines, optimize models for performance and accuracy, and ensure they are production-ready. Contribute to projects that require cutting-edge technology and innovative approaches.
  • Learn and Lead: Stay ahead of the curve by engaging with the latest developments in machine learning and AI. Take part in code reviews, share knowledge, and lead by example to maintain high-quality engineering practices.
  • Make a Difference: Monitor and maintain deployed models to ensure they continue delivering value. Your work will directly influence how AI benefits individuals, businesses, and society at large.


You might thrive in this role if you:

  • Master's/ PhD degree in Computer Science, Machine Learning, Data Science, or a related field. 
  • Demonstrated experience in deep learning and transformers models
  • Proficiency in frameworks like PyTorch or Tensorflow
  • Strong foundation in data structures, algorithms, and software engineering principles.
  • Experience with search relevance, ads ranking or LLMs is a plus.
  • Are familiar with methods of training and fine-tuning large language models, such as distillation, supervised fine-tuning, and policy optimization
  • Excellent problem-solving and analytical skills, with a proactive approach to challenges.
  • Ability to work collaboratively with cross-functional teams.
  • Ability to move fast in an environment where things are sometimes loosely defined and may have competing priorities or deadlines
  • Enjoy owning the problems end-to-end, and are willing to pick up whatever knowledge you're missing to get the job done


We are an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity.