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Research Machine Learning Federated Learning Jobs in Wyoming

Quora

$139K - $168K/yr

At Poe, we use Machine Learning in various parts of the product - bot routing, agent flow, code editing, RAG, etc. Our team of Machine Learning Engineers have high impact by advancing the current ...

Whiterabbit.ai

Learn and understand a large body of research in deep learning and machine learning * Participate in cutting-edge research for medical applications of computer vision Must Have Experience

TSMG

AI/ML Data Contributor

Cheyenne, WY · On-site

In this role, you will participate in tasks that help improve machine learning models, including data labeling, content evaluation, and user-based testing. Projects may vary in scope and format ...

TSMG

AI/ML Data Contributor

Cheyenne, WY

In this role, you will participate in tasks that help improve machine learning models, including data labeling, content evaluation, and user-based testing. Projects may vary in scope and format ...

TSMG

AI/ML Data Contributor

Cheyenne, WY

In this role, you will participate in tasks that help improve machine learning models, including data labeling, content evaluation, and user-based testing. Projects may vary in scope and format ...

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All JobsResearch Machine Learning Federated Learning JobsResearch Machine Learning Federated Learning Jobs in Wyoming

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 cities in Wyoming are hiring for Research Machine Learning Federated Learning jobs? Cities in Wyoming with the most Research Machine Learning Federated Learning job openings:
Research Machine Learning Federated Learning jobs near you
Infographic showing various Research Machine Learning Federated Learning job openings in Wyoming as of August 2026, with employment types broken down into 80% Full Time, and 20% Contract. Highlights an 80% In-person, and 20% Remote job distribution.

Machine Learning Engineer New Grad 2024-2025 -Remote

Quora

Remote

$139K - $168K/yr

Full-time

Medical, Dental, Vision, PTO

Posted 25 days ago

Job description

About Quora:

Quora’s mission is to grow and share the world’s knowledge. To do so, we have two knowledge sharing products:

  • Quora : a global knowledge sharing platform with over 400M monthly unique visitors, bringing people together to share insights on various topics and providing a unique platform to learn and connect with others.
  • Poe : a platform providing millions of global users with one place to chat, explore and build with a wide variety of AI language models (bots), including o3, o4-mini, Claude 3.7 Sonnet, GPT Image 1 and more. As AI capabilities rapidly advance, Poe provides a single platform to instantly integrate and utilize these new models.

Behind these products are passionate, collaborative, and high-performing global teams. We have a culture rooted in transparency, idea-sharing, and experimentation that allows us to celebrate success and grow together through meaningful work. Join us on this journey to create a positive impact and make a significant change in the world.

This role will be working on our Poe product.

About the Team and Role:

Our small engineering team works on challenging problems every day. We have a culture that's rooted in constantly learning and improving, and our engineers are encouraged to think big and experiment with new ideas. Using continuous deployment, we quickly see our changes in the product and make fast iterations. Our engineers focus on creating polished products and writing high quality code by designing APIs and abstractions that are extensible and maintainable. Everyone on the engineering team has a huge impact on our product and our company.

At Poe, we use Machine Learning in various parts of the product - bot routing, agent flow, code editing, RAG, etc. Our team of Machine Learning Engineers have high impact by advancing the current Machine Learning systems, building performant and reliable LLM applications and collaborating with our product team to uncover new opportunities to the Poe product. You will also play a key role in developing tools and abstractions that our other developers would build on top of.

Responsibilities:
  • Improve our existing Machine Learning systems using your expertise
  • Identify new opportunities to apply Machine Learning to different parts of the Poe product
  • Work with other engineers to implement algorithms and systems in an efficient way
  • Take end-to-end ownership of Machine Learning systems -- from prototyping, data pipelines and training, to realtime LLM application at scale
Minimum Requirements:
  • Ability to be available for meetings and impromptu communication during Quora's “ coordination hours " (Mon-Fri: 9am-3pm Pacific Time)
  • A 2024 or 2025 graduate with or pursuing a B.S., M.S., or Ph.D. in Computer Science, Engineering or a related technical field
  • Strong understanding of mathematical foundations of Machine Learning algorithms
  • Experience of transformer models and LLM applications
  • Strong knowledge of Python or C++, or the ability to learn them quickly
  • A passion for learning and always improving yourself and the team around you
Preferred Requirements:
  • Previous software engineering experience via an internship, work experience, or coding competition
  • Previous industry experience working on natural language processing, language modeling, etc.
  • Passion for Quora's mission and goals

At Quora, we value diversity and inclusivity and welcome individuals from all backgrounds, including marginalized or underrepresented groups in tech, to apply for our job openings. We encourage all candidates who share a passion for growing the world’s knowledge, even those who may not strictly meet all the preferred requirements, to apply, as we know that a diverse range of perspectives can have a significant impact on our products and our culture.

Additional Information:

We are accepting applications on an ongoing basis.

Quora offers a wide range of benefits including medical/dental/vision coverage, equity refreshers, remote work reimbursement, paid time off, employee assistance programs, and more. Benefits are country-specific and may vary. For more information on benefits, visit this link:

There are many factors that will determine the starting pay, including but not limited to experience, location, education, and business needs.

  • US candidates only: For US based applicants, the salary range is $107,660 - $161,700 USD + equity + benefits.
  • Canada candidates only: For Toronto and Vancouver based applicants, the salary range is $139,979 - $168,193 CAD + equity + benefits. For all other locations in Canada, the salary range is $130,647 - $156,980 CAD + equity + benefits.

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

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