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Research Machine Learning Federated Learning Jobs in Oregon

OR · On-site

Candidates should bring some relevant research experience, typically in computationally intensive empirical topics, as well as some exposure to machine learning coursework and applications. The ...

OR · On-site

Machine learning is central to how we build intelligent shopping experiences at Instacart. We use ... Researching techniques to deploy LLMs in high-traffic, latency-sensitive production environments ...

OR

$523K - $920K/yr

We are seeking an experienced Machine Learning leader to lead a team of Research Scientists and Machine Learning Engineers working on multimodal LLM and audio algorithms. You will support a highly ...

Research and Learning: Stay current with advancements in LLMs, agentic frameworks, machine learning, and healthcare technology, and apply new knowledge to contribute ideas for innovation within the ...

Machine Learning Engineer Location: Portland, OR - Onsite (Local only / F2F interview) Duration: 24 Months Contract Experience Level: 5+ years of experience Required Qualifications • Bachelor's or ...

Machine Learning Engineer Location: Portland, OR - Onsite (Local only / F2F interview) Duration: 24 Months Contract Experience Level: 5+ years of experience Required Qualifications • Bachelor's or ...

Machine Learning Engineer Location: Portland, OR - Onsite (Local only / F2F interview) Duration: 24 Months Contract Experience Level: 5+ years of experience Required Qualifications Bachelor's or ...

Design, prototype, research and build AI systems for Vectara. * Train, evaluate and deploy ML ... machine learning to real-world problems, and crafting scalable and effective ML/AI solutions.

The Machine Learning & Inference Research (MLIR) team works on core methodological development in areas of strategic importance to Netflix and translates this research into actionable impact by ...

Senior Machine Learning Test Engineer

OR · On-site +1

$110.40K - $143.40K/yr

United States East Coast Position Overview As a Senior Machine Learning Test Engineer in the Research Enablement team, you will work side-by-side with researchers, Machine Learning developers and ...

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

OR · Remote

$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 ...

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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 Oregon? For Research Machine Learning Federated Learning jobs in Oregon, the most frequently searched job titles are:
What cities in Oregon are hiring for Research Machine Learning Federated Learning jobs? Cities in Oregon with the most Research Machine Learning Federated Learning job openings:
Machine Learning PhD Intern, Economics

Machine Learning PhD Intern, Economics

Instacart

On-site

Other

Posted 8 days ago


Instacart rating

6.7

Company rating: 6.7 out of 10

Based on 29 frontline employees who took The Breakroom Quiz


Job description

Overview

We are looking for interns to join Instacart's Economics team. The ideal candidate for this role will bring a combination of experience in both economics and machine learning. We are in particular looking for current or recently graduated PhD students in economics or related fields like marketing, finance, or operations research. Candidates should bring some relevant research experience, typically in computationally intensive empirical topics, as well as some exposure to machine learning coursework and applications.

The Economics team at Instacart works on a range of interesting and challenging problems at the intersection of machine learning and economics, from aligning the incentives in our multi-sided marketplace to analyzing the impact of behavioral nudges on our customers' and shoppers' decisions. Some of the core areas of focus for our team include online advertising, uplift and long term value modeling, logistics, marketplace optimization (consumers, shoppers, retailers), inventory intelligence, and general causal inference. You can find more information in our blog post that introduces the team and the type of work we do.

About the Job

  • You will help design and build end-to-end machine learning solutions.
  • You will be working in small and cross-functional product teams, with great opportunities for growth and ownership of projects.
  • You will be an active member of an internal community, including economists, data scientists, operations research scientists and machine learning engineers, sharing learnings, best practices and research across many domains.
  • You will develop high impact solutions to support Instacart's ambitious growth plans.
  • You will work closely with engineers, product managers, other teams, and both internal and external stakeholders, owning a large part of the process from problem understanding to recommending a solution and testing it in controlled experiments.
  • You will have the freedom to suggest and drive organization-wide initiatives.

About You

Minimum Qualifications

  • Current or recently graduated PhD student in economics or a related field with focus on data-intense problems.
  • A blend of economic theory, applied econometrics, and business acumen that let you jump into a fast-paced environment and contribute from day one.
  • Expertise in causal inference with observational and experimental data.
  • Expertise in Python or R and fluency in data manipulation (SQL, Pandas) and machine learning (scikit-learn, XGBoost, Keras/Tensorflow) tools.
  • Self-motivation and a strong sense of ownership

What Instacart employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


Instacart logo

About Instacart

Sourced by ZipRecruiter

Instacart, based in San Francisco, CA, US, operates within the retail industry, specifically grocery delivery and pick-up service. It is recognized as a pioneer in this field, delivering fresh groceries from local stores directly to customers' doors. The company, which launched its services in 2012, continues to pioneer change in the online grocery shopping sector through its commitment to cutting-edge technology, new business ideas, and dedicated service.

Industry

Technology, communication and media

Company size

10,000+ Employees

Headquarters location

San Francisco, CA, US

Year founded

2012