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Manager Learning Solutions Jobs in California (NOW HIRING)

SKIMS

Manager, Retail Learning Design

Los Angeles, CA

$100K - $120K/yr

Description SKIMS is a solutions-oriented brand creating the next generation of underwear ... Key Responsibilities Position Summary The Manager, Retail Learning Design is responsible for ...

SKIMS

Manager, Retail Learning Design

Los Angeles, CA · On-site

$18.50 - $23.50/hr

SKIMS is a solutions-oriented brand creating the next generation of underwear, loungewear ... Position Summary The Manager, Retail Learning Design is responsible for designing, developing, and ...

Socket.dev

Sr Learning Experience Designer

San Diego, CA · On-site

$90 - $135/hr

Collaborate with Talent Management colleagues, subject matter experts and external partners to develop, test, and deliver learning solutions within established program strategies and standards.

Illumina

Sr Learning Experience Designer

Coronado, CA · On-site

$90 - $135/hr

Collaborate with Talent Management colleagues, subject matter experts and external partners to develop, test, and deliver learning solutions within established program strategies and standards.

SKIMS

Manager, Retail Learning Design

Los Angeles, CA · On-site

$100K - $120K/yr

Manager, Retail Learning Design Department: Retail - Corporate Employment Type: Full Time Location ... Adam farhoud Compensation: $100,000 - $120,000 / year Description SKIMS is a solutions-oriented ...

Illumina

Sr Learning Experience Designer

San Diego, CA · On-site

$90 - $135/hr

Collaborate with Talent Management colleagues, subject matter experts and external partners to develop, test, and deliver learning solutions within established program strategies and standards.Curate ...

Ross Stores

Director, Learning & Development

Dublin, CA · On-site

$119K - $225K/yr

Apply best practices in adult learning theory, learning technology, instructional design, change management, and communication (e.g. micro-learning, peer learning, action learning, blended solutions ...

Ross

Director, Learning & Development

Dublin, CA · On-site

$119K - $225K/yr

Apply best practices in adult learning theory, learning technology, instructional design, change management, and communication (e.g. micro-learning, peer learning, action learning, blended solutions ...

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Showing results 21-40

All JobsLearning Solutions JobsManager Learning Solutions JobsManager Learning Solutions Jobs in California

Manager Learning Solutions information

See California salary details

$30.6K

$76.4K

$128.3K

How much do manager learning solutions jobs pay per year?

As of Aug 22, 2026, the average yearly pay for manager learning solutions in California is $76,366.00, according to ZipRecruiter salary data. Most workers in this role earn between $58,200.00 and $86,400.00 per year, depending on experience, location, and employer.

What does a Manager Learning Solutions do?

A Manager Learning Solutions is responsible for designing, implementing, and overseeing training programs that help employees develop new skills and improve performance. They work closely with stakeholders to assess organizational learning needs, select appropriate instructional methods, and measure the effectiveness of training initiatives. This role often involves managing a team of instructional designers, trainers, or e-learning specialists, as well as coordinating with external vendors. Ultimately, a Manager Learning Solutions ensures that learning strategies align with business goals and support overall organizational growth.

How does a Manager Learning Solutions typically collaborate with subject matter experts and stakeholders when developing training programs?

Managers in Learning Solutions frequently work closely with subject matter experts (SMEs) and stakeholders throughout the design and implementation of training programs. This typically involves conducting needs assessments with stakeholders, facilitating workshops or interviews with SMEs to gather content, and iteratively reviewing training materials to ensure accuracy and alignment with business objectives. Effective collaboration is essential for creating relevant and impactful learning solutions, so strong communication and project management skills are vital. Additionally, Managers often serve as a bridge between technical experts and end-users, translating complex information into engaging, accessible training content.

What are the key skills and qualifications needed to thrive as a Manager Learning Solutions, and why are they important?

To thrive as a Manager Learning Solutions, you need expertise in instructional design, adult learning theory, project management, and usually a degree in education, HR, or a related field. Familiarity with Learning Management Systems (LMS), e-learning authoring tools, and relevant certifications like CPLP or ATD are commonly required. Outstanding communication, leadership, and stakeholder management skills help you collaborate effectively and drive organizational learning initiatives. These skills and qualities ensure the development and delivery of impactful learning programs that align with business goals and foster employee growth.

What is the difference between Manager Learning Solutions vs Learning and Development Manager?

AspectManager Learning SolutionsLearning and Development Manager
Primary FocusDesigning and implementing learning technology and solutionsOverseeing overall employee training and development programs
Required CredentialsOften requires certifications in e-learning, instructional design, or related tech skillsTypically requires HR or training certifications, such as CPLP or SHRM-CP
Work EnvironmentTech-driven, project-based, often in corporate or educational settingsHR departments, corporate offices, or training centers
Employer & Industry UsageCommon in tech, corporate, and educational sectorsWidely used across industries with a focus on employee development

While both roles focus on learning and development, the Manager Learning Solutions specializes in creating and managing learning technology and solutions, whereas the Learning and Development Manager oversees broader employee training programs. The choice depends on whether the focus is on tech-based learning or overall employee development.

What are popular job titles related to Manager Learning Solutions jobs in California?

For Manager Learning Solutions jobs in California, the most frequently searched job titles are:

What job categories do people searching Manager Learning Solutions jobs in California look for?

The top searched job categories for Manager Learning Solutions jobs in California are:

What cities in California are hiring for Manager Learning Solutions jobs?

Cities in California with the most Manager Learning Solutions job openings:

Manager Learning Solutions jobs near you
Infographic showing various Manager Learning Solutions job openings in California as of August 2026, with employment types broken down into 85% Full Time, 13% Part Time, and 2% Contract. Highlights an 84% Physical, 3% Hybrid, and 13% Remote job distribution, with an average salary of $76,366 per year, or $36.7 per hour.

Senior Systems Software Engineer - Deep Learning Solutions

Nvidia Corporation

Santa Clara, CA • On-site

$65 - $83.75/hr

Full-time

Re-posted 15 days ago

Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

7th of 246 rated software companies

Job description

NVIDIA is a global leader in physical AI, powering self-driving cars, humanoid robots, intelligent environments, and medical devices. Our software platforms are central to this mission. We help innovators build products that save lives, enhance working conditions, and improve living standards globally!
We are hiring a Senior Systems Software Engineer to join our team as a technical expert focused on optimizing deep learning inference for autonomous vehicles and robotics on edge devices. This role requires a hands-on specialist who can examine model architectures at the operator level. They will locate performance issues through kernel trace analysis and evaluate modern architectures (transformers, vision-language models, diffusion/flow matching, state space models) on GPU and SOC. This work directly enhances autonomous vehicles' and robots' ability to perceive and respond in real time, yielding immediate benefits. The group works on some of the hardest optimization challenges in the industry, positioned at the convergence of model frameworks, compiler technology, and embedded hardware. We maintain strong collaboration with automotive OEMs, robotics colleagues, and internal hardware teams to extend edge device capabilities.
What you'll be doing:
  • Address customer and partner optimization challenges: Engage directly with prominent automotive OEMs and robotics associates to analyze, debug, and improve their deep learning models on NVIDIA platforms. We emphasize delivering solutions rather than just recommendations.
  • Own performance benchmarking: Drive efforts to achieve leading results on MLPerf Edge and industry benchmarks, as well as closed-source engagements with key partners. Define methodology, ensure reproducibility, and turn results into actionable optimization priorities.
  • Evaluate emerging model architectures: Investigate new DL architectures, including vision encoders, multi-modal VLMs, hybrid SSM-Transformer backbones, diffusion/flow matching decoders, and multi-camera tokenizers, regarding compilation feasibility, memory footprint, and latency on target SOCs.
  • Collaborate across teams: Work alongside our compiler, runtime, and hardware groups to link model-level insight with platform capabilities.
  • Contribute to build reviews and help develop internal roadmap priorities based on real customer workload patterns.
  • Represent NVIDIA externally: Share our deep learning optimization expertise at conferences, webinars, and partner events. Help elevate the broader team by bringing back insights and establishing guidelines.
  • Deliver TensorRT and compiler-stack solutions for edge: Build and deploy inference solutions on Jetson, DRIVE, and GPU + ARM platforms for AV and robotics workloads. Develop Proofs of Readiness (PORs) and collaborate closely with our compiler team on Torch-TRT, MLIR-TRT, and related frameworks to bridge performance gaps.

What we need to see:
  • Master's degree or equivalent experience in Computer Science, Electrical Engineering, or a related field.
  • Over 12 years working in the industry, including at least 8 years specializing in deep learning model optimization, inference engineering, or neural network compilation. Proficiency in understanding and reviewing model architectures at the operator/kernel level, not merely handling their operation, is required.
  • Over 5 years of validated expertise in embedded/edge software, with experience delivering production inference solutions within power-limited, latency-sensitive deployment environments.
  • Comprehensive knowledge of contemporary DL architectures: transformers, attention variants, vision encoders (ViT), multi-modal/vision-language model frameworks, as well as experience with diffusion models and/or state space models.
  • Expert knowledge of GPU architecture fundamentals, CUDA, and low-level performance optimization using heterogeneous computing. Experience with TensorRT, compiler IRs, or equivalent inference optimization toolchains.
  • Solid understanding of embedded operating system internals (QNX/Linux), memory management, C/C++, and embedded/system software concepts.
  • Background in parallel programming (e.g., CUDA, OpenMP) and experience reasoning about memory hierarchies, data movement, and compute utilization.
  • Demonstrated capability to collaborate directly with external partners and customers in a deep technical role. You solve their workload issues, identify performance problems, and provide solutions within production limitations.

Ways to Stand Out from the Crowd:
  • Experience with ML compiler frameworks (TVM, MLIR, XLA, Triton) or contributing to inference runtime development.
  • Production deployment experience with autonomous vehicle perception or planning stacks, understanding the full pipeline from sensor input through trajectory output.
  • Familiarity with the Physical AI model landscape: VLM + action expert architectures, end-to-end driving models, or robot foundation models.
  • Contributions to MLPerf benchmarks and large-scale industry performance optimization efforts.
  • Experience with automotive safety standards (ISO 26262, SOTIF) and their implications for inference system development.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 224,000 USD - 356,500 USD.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until March 15, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering a diverse 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

Nvidia logo

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

Year founded

1993

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