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Research Federated Learning Jobs in Oregon (NOW HIRING)

Research Federated Learning information

What is a researcher in federated learning?

A Researcher in Federated Learning is a professional who studies, develops, and improves federated learning algorithms and systems. Federated learning is a machine learning approach where data remains decentralized, allowing multiple devices or organizations to collaboratively train models without sharing raw data. These researchers focus on advancing privacy, efficiency, and performance in distributed AI systems. Their work often involves experimenting with new methods, publishing findings, and contributing to the growing field of privacy-preserving machine learning.

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

To thrive as a Researcher in Federated Learning, you need a strong background in machine learning, distributed systems, and statistics, typically supported by an advanced degree in computer science or a related field. Familiarity with programming languages like Python, frameworks such as TensorFlow Federated, and experience with privacy-preserving algorithms are essential. Critical thinking, collaboration, and effective communication are key soft skills for designing experiments and sharing findings with peers. These competencies are vital for advancing privacy-aware AI solutions and producing impactful research in this rapidly evolving domain.

What are some common challenges faced by professionals working in research federated learning, and how can they be addressed?

Professionals in Research Federated Learning often encounter challenges such as ensuring data privacy across distributed devices, managing non-iid (non-independent and identically distributed) data, and optimizing communication efficiency between clients and servers. Addressing these issues requires strong collaboration with cross-functional teams, including data engineers, security experts, and software developers, to develop robust protocols and algorithms. Staying updated with the latest research and participating in open-source collaborations can also help overcome technical hurdles and drive innovation in this rapidly evolving field.

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

AspectResearch Federated LearningData Scientist
Required CredentialsAdvanced degrees in CS, ML, or related fields; research experienceBachelor's or Master's in Data Science, Statistics, or related fields
Work EnvironmentResearch labs, tech companies, academia; focus on algorithm developmentBusiness environments, analytics teams; focus on data analysis and insights
Industry UsageAI research, privacy-preserving ML, distributed systemsBusiness intelligence, marketing, finance, healthcare

Research Federated Learning involves developing privacy-focused, distributed machine learning algorithms, often in research or specialized tech settings. Data Scientists analyze data to generate insights and support decision-making in various industries. While both roles require strong analytical skills, Research Federated Learning emphasizes algorithm development and privacy, whereas Data Scientists focus on data analysis and reporting.

What are popular job titles related to Research Federated Learning jobs in Oregon?

For Research Federated Learning jobs in Oregon, the most frequently searched job titles are:

What job categories do people searching Research Federated Learning jobs in Oregon look for?

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

What cities in Oregon are hiring for Research Federated Learning jobs?

Cities in Oregon with the most Research Federated Learning job openings:

Manager, Data Science & Engineering - Title & Launch Management

Netflix

OR • On-site, Remote

$480K - $750K/yr

Full-time

Medical, Life, Retirement, PTO

Re-posted 7 days ago


Netflix rating

5.8

Company rating: 5.8 out of 10

Based on 15 frontline employees who took The Breakroom Quiz

72nd of 78 rated media


Job description

At Netflix, our mission is to entertain the world. Together, we are writing the next episode - pushing the boundaries of storytelling, global fandom and making the unimaginable a reality. We are a dream team obsessed with the uncomfortable excitement of discovering what happens when you merge creativity, intuition and cutting-edge technology.

Come be a part of what's next. The Title & Launch Management Data Science and Engineering team is at the forefront of driving operational and creative excellence in how we launch and promote content. We build highly automated systems that power the launch of new content formats, such as fastfollow local broadcasts and video podcasts, and help members discover titles they'll love.

Our interdisciplinary team sits at the intersection of rigorous measurement, advanced analytics, and the latest AI/agentic solutions that enable the ingest, setup, launch, and global distribution of all types of entertainment on Netflix. We are seeking an experienced leader to lead a multidisciplinary team of analytics engineers, data scientists, and machine learning scientists and engineers who build the data products, algorithms, and systems that power title launch. You will guide a highly talented team and partner closely with crossfunctional teams to support Netflix's growing content offerings and partnerships by automating largescale content ingestion and replacing manual processes, developing a flexible, federated system that enables efficient, scalable, and selfservice content ingestion as Netflix continues to grow.

Responsibilities Oversee a diverse portfolio of end-to-end efforts to design, deploy, and rigorously evaluate autonomous AI solutions, advancing Netflix's title launch strategy and supporting our rapidly expanding slate of content. Coach, empower, and elevate a team of analytics engineers, data scientists, and machine learning practitioners, increasing their impact and supporting their career development. Collaborate with a cross-functional team to shape the vision and roadmap for the area, prioritize and drive execution.

Define and cultivate a high standard for both velocity and technical excellence, while nurturing a culture grounded in strong engineering and scientific rigor. Leverage advanced technical skills and deep product and domain insight to surface new problem spaces and make bold, high-conviction decisions. Cultivate durable partnerships with stakeholders across product, engineering, and content to align on long-term goals and jointly deliver outcomes.

Act as a visible leader and subject-matter expert, advocating for the team's work and strengthening its reputation across and beyond Netflix. About you Proven track record of successfully leading data and ML-focused teams, with a strong emphasis on rigorous measurement and agentic/AI-driven solutions. Deep expertise in autonomous agentic systems and applied ML, with a demonstrated commitment to staying current on the latest research and having led teams that launch and iterate on production ML services.

Passion for guiding teams through ambiguous, complex technical and business problems, bringing clarity, structure, and disciplined execution. Strong track record of mentoring and developing talent, including successfully recruiting and growing researchers and engineers across multiple levels. Master's or PhD in Machine Learning, Computer Science, or a closely related field.

6+ years of hands-on ML experience (or 4+ years with a relevant PhD). 2+ years of experience leading ML teams. Exceptional verbal and written communication skills, with the ability to influence and align diverse stakeholders.

Deep commitment to driving end-to-end business impact, not just building models. Netflix culture resonates with you, and you're excited to model and reinforce it within your team. Generally, our compensation structure consists solely of an annual salary; we do not have bonuses.

You choose each year how much of your compensation you want in salary versus stock options. To determine your personal top of market compensation, we rely on market indicators and consider your specific job family, background, skills, and experience to determine your compensation in the market range. The range for this role is $480,000.00 - $750,000.00

This compensation range will vary based on location. Netflix provides comprehensive benefits including Health Plans, Mental Health support, a 401(k) Retirement Plan with employer match, Stock Option Program, Disability Programs, Health Savings and Flexible Spending Accounts, Family-forming benefits, and Life and Serious Injury Benefits. We also offer paid leave of absence programs.

Full-time hourly employees accrue 35 days annually for paid time off to be used for vacation, holidays, and sick paid time off. Full-time salaried employees are immediately entitled to flexible time off. See more details about our Benefits here.

Netflix is a unique culture and environment. Learn more here. Inclusion is a Netflix value and we strive to host a meaningful interview experience for all candidates.

If you want an accommodation/adjustment for a disability or any other reason during the hiring process, please send a request to your recruiting partner. We are an equal-opportunity employer and celebrate diversity, recognizing that diversity builds stronger teams. We approach diversity and inclusion seriously and thoughtfully.

We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service. Job is open for no less than 7 days and will be removed when the position is filled.


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About Netflix

Sourced by ZipRecruiter

Netflix is the world's leading streaming entertainment service with 222 million paid memberships in over 190 countries enjoying TV series, documentaries, feature films and mobile games across a wide variety of genres and languages. Members can watch as much as they want, anytime, anywhere, on any Internet-connected screen. Members can play, pause and resume watching, all without commercials or commitments.

Industry

Arts, entertainment, and recreation

Company size

5,001 - 10,000 Employees

Headquarters location

Los Gatos, CA, US

Year founded

1997