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Manager Recommender Systems Jobs in California (NOW HIRING)

Namely

Senior Principal Al Engineer

Mountain View, CA · On-site

$130 - $170/hr

Expertly design, build, and tune production AI/ML models (NLP, Deep Learning, Recommender Systems ... management challenges with next‑gen AI. * Orchestration Tooling: Build frameworks for ...

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Manager Recommender Systems information

What is a manager recommender systems?

A Manager of Recommender Systems is a professional who oversees the development and deployment of algorithms that suggest products, services, or content to users based on their preferences and behavior. They lead teams of data scientists, engineers, and analysts to design, implement, and optimize recommendation engines. Their role involves strategic planning, project management, and ensuring that the recommender systems align with business goals while delivering a personalized user experience.

What are the key skills and qualifications needed to thrive as a manager recommender systems?

To thrive as a Manager, Recommender Systems, you need a solid background in computer science, machine learning, and data analytics, typically supported by a relevant degree and experience in building recommendation algorithms. Familiarity with programming languages like Python or Scala, machine learning frameworks, and big data platforms such as Spark or Hadoop is essential, along with knowledge of A/B testing and model evaluation techniques. Strong leadership, project management, and cross-functional communication skills distinguish top performers in this role. These skills ensure effective team guidance, robust system development, and alignment of technical solutions with business goals in a fast-evolving digital landscape.

How does a manager recommender systems typically collaborate with data scientists and engineers to deliver effective recommendation solutions?

As a Manager of Recommender Systems, you will frequently coordinate cross-functional efforts between data scientists, machine learning engineers, and product teams. Your role involves setting project priorities, facilitating communication to ensure clear understanding of objectives, and removing roadblocks that may impede progress. You’ll also oversee the translation of business requirements into technical solutions, review algorithm performance, and guide the team in iterative model improvements. Regular collaboration ensures that the recommendations delivered align with both user needs and business goals.

What is the difference between Manager Recommender Systems vs Data Scientist?

AspectManager Recommender SystemsData Scientist
CredentialsAdvanced degree in CS, ML, or related field; experience with recommender algorithmsDegree in CS, Statistics, or related; strong programming and analytical skills
Work EnvironmentLeading teams, overseeing recommender system projects, collaborating with product teamsAnalyzing data, building models, interpreting results across various domains
Industry UsageTech companies, e-commerce, streaming services

While both roles require strong technical skills and data expertise, Manager Recommender Systems focus on leading teams and managing recommender system projects, whereas Data Scientists primarily analyze data and develop models across diverse applications.

What are the most commonly searched types of Recommender Systems jobs in California?

The most popular types of Recommender Systems jobs in California are:

What are popular job titles related to Manager Recommender Systems jobs in California?

For Manager Recommender Systems jobs in California, the most frequently searched job titles are:

What job categories do people searching Manager Recommender Systems jobs in California look for?

The top searched job categories for Manager Recommender Systems jobs in California are:

What cities in California are hiring for Manager Recommender Systems jobs?

Cities in California with the most Manager Recommender Systems job openings:

Manager Recommender Systems jobs near you

Principal Technical Program Manager, Relational Deep Learning Platform

Nvidia Corporation

Santa Clara, CA • On-site

$151K - $196K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 10 days ago

Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 18 frontline employees who took The Breakroom Quiz

6th of 247 rated software companies

Job description

NVIDIA is redefining what is possible with AI, and we are building the next generation of relational deep learning for enterprise data. Our platform learns directly from the structure and relationships inside relational databases and heterogeneous graphs, unifying GPU-accelerated graph analytics and graph machine learning in a single stack. It powers high-impact workloads such as fraud detection and recommender systems and helps customers unlock more value from their data. We care deeply about turning frontier AI research into reliable products that teams can trust every day, and we are excited to add a Principal Technical Program Manager who will help us do exactly that!
What you will be doing:
As Principal Technical Program Manager, you will lead the relational deep learning program from research to production. You will connect ML researchers, infrastructure, and platform teams so work stays aligned and delivers real impact.
  • Deliver task-specific models for domains such as fraud detection and recommender systems, moving from problem definition and data requirements through training, benchmarking, and hand-off to product and customer teams.
  • Coordinate closely with infrastructure, systems, and platform groups to align compute capacity, training and serving environments, and platform features that models depend on.
  • Guide release management for both the platform and models, including experiment-to-production hand-offs, versioning, compatibility, model cards, benchmarks, and safety and compliance approvals.
  • Maintain the operating rhythm for the program, leading planning, reviews, risk and dependency tracking, and decision forums across research, engineering, data, product, legal, and other partners.
  • Define and track program health metrics such as model quality, training speed, evaluation coverage, and time-to-release, and share clear status, risks, and decisions in executive reviews.
  • We work as one team, we solve hard problems together, and we celebrate when complex programs ship and make a difference for customers.
  • We believe people who enjoy building, learning, and collaborating across teams will thrive in this role.

What we need to see:
  • Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent experience.
  • 15+ years of experience in technical program management, engineering, or data/ML delivery, including significant time in ML/AI or large-scale data environments.
  • Experience leading complex, multi-stakeholder programs end to end in research and engineering organizations, with evolving requirements and clear delivery timelines.
  • Comfort working with ML researchers, interpreting model and evaluation results, and making decisions about training pipelines, data, and infrastructure trade-offs.
  • Ability to build operating rhythms from scratch, influence without formal authority, and communicate clearly with both highly technical teams and senior executives.
  • Familiarity with modern program-management practices (for example, Agile, roadmapping, risk and dependency management) and the judgment to use them effectively in fast-moving research settings.
  • A hands-on, builder mindset that includes creating automation and tooling, using AI in daily work, and applying AI to streamline program operations, status reporting, risk detection, and release workflows.

Ways to stand out from the crowd:
  • Delivering graph ML, recommender, or fraud-detection systems into production, or shipping ML platforms and frameworks that other teams build on.
  • Working with graph machine learning, GNNs, relational or tabular data, graph analytics libraries such as cuGraph, and the modern data stack (warehouses, feature stores, and data pipelines).
  • Running programs that span platform and infrastructure teams and model and research teams, including GPU and compute capacity planning for training and serving.

NVIDIA offers comprehensive benefits: medical, dental, and vision insurance; a 401(k) with company match; an employee stock purchase plan; flexible, generous paid time off; parental leave; and ongoing learning and development support!
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 240,000 USD - 379,500 USD.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until August 31, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

What Nvidia employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

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About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

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