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Unique Learning System Jobs in California (NOW HIRING)

Segment (Twilio)

Staff Machine Learning Engineer

San Francisco, CA · On-site

$230 - $322/hr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit ... Drive end-to-end model lifecycle execution, including system architecture design, large-scale ...

Collabera Digital

Learning Specialist

Sacramento, CA · On-site

$70K - $79K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

... unique and diverse. The way we share ideas, learning, experiences, successes, and joy allows ... System). * Contribute to the planning and logistics related to onboarding and employee development ...

Jobzhr

Machine Learning Engineer, Drive

San Francisco, CA · On-site

$204 - $299/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

The Drive Machine Learning team builds the prediction and intelligence systems that power this ... Drive presents a unique machine learning challenge. Every merchant has different operational ...

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How much do unique learning system jobs pay per hour?

As of Aug 17, 2026, the average hourly pay for unique learning system in California is $36.79, according to ZipRecruiter salary data. Most workers in this role earn between $27.74 and $46.25 per hour, depending on experience, location, and employer.

What is a Unique Learning System?

A Unique Learning System (ULS) job typically involves working with a cloud-based special education curriculum designed for students with diverse learning needs. Professionals in these roles may include educators, curriculum specialists, or instructional aides who implement and customize ULS materials to support individualized learning. Responsibilities often include lesson planning, progress monitoring, and adapting instructional strategies to meet students' needs. These jobs are commonly found in special education classrooms, therapy settings, and educational organizations focused on differentiated instruction.

What are the typical responsibilities of a Unique Learning System specialist in a school setting?

A Unique Learning System Specialist is responsible for implementing adaptive curriculum solutions, training teachers on proper usage, and providing ongoing support to ensure students' learning needs are met. They analyze student data, tailor instructional plans, and collaborate with special education teams and classroom teachers to maximize educational outcomes. Daily tasks may involve troubleshooting software issues, conducting workshops, and developing resource materials. This collaborative and support-oriented role directly impacts both teacher efficacy and student success.

What are the key skills and qualifications needed to thrive in the Unique Learning System position, and why are they important?

To excel as a Unique Learning System Specialist, you should have a background in education, curriculum development, and adaptive instructional strategies, supported by a relevant degree or teaching certification. Familiarity with learning management systems (LMS), data tracking tools, and digital curriculum platforms is typically required. Strong organizational skills, creativity, and the ability to communicate effectively with students, educators, and support staff are key soft skills in this position. These abilities are critical for designing and delivering personalized learning experiences that meet diverse student needs and achievement goals.

What are the most commonly searched types of Unique Learning System jobs in California?

The most popular types of Unique Learning System jobs in California are:

What are popular job titles related to Unique Learning System jobs in California?

For Unique Learning System jobs in California, the most frequently searched job titles are:

What job categories do people searching Unique Learning System jobs in California look for?

The top searched job categories for Unique Learning System jobs in California are:

What cities in California are hiring for Unique Learning System jobs?

Cities in California with the most Unique Learning System job openings:

Unique Learning System jobs near you
Infographic showing various Unique Learning System job openings in California as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, 2% Temporary, and 2% Contract. Highlights an 92% Physical, 2% Hybrid, and 6% Remote job distribution, with an average salary of $76,530 per year, or $36.8 per hour.

Machine Learning Engineer, Drive

Visa Hunt

Sunnyvale, CA • On-site

$150 - $210/hr

Other

Posted 5 days ago

Job description

About the Team

DoorDash Drive powers deliveries placed through merchants' own channels—including their websites, mobile apps, and phone orders—using DoorDash's logistics network. The Drive Machine Learning team builds the prediction and intelligence systems that power this business, including delivery and pickup time estimation, merchant prep-time prediction, order release optimization, logistics decision‑making, and AI‑powered delivery quality signals.

Drive presents a unique machine learning challenge. Every merchant has different operational workflows, preparation patterns, and customer expectations, requiring models that generalize across millions of deliveries while adapting to highly diverse merchant behavior. Our team has significant opportunities to improve prediction accuracy, optimize logistics decisions, and build AI‑native experiences that directly improve merchant, consumer, and dasher outcomes.

About the Role

As a Machine Learning Engineer on the Drive team, you'll own machine learning systems end-to-end—from feature engineering and model development to experimentation, deployment, monitoring, and continuous iteration.

Your work will span several high-impact problem areas:

  • Build next-generation machine learning models for delivery ETA, pickup ETA, merchant prep‑time estimation, and order release prediction that improve reliability for merchants and consumers.
  • Develop deep learning models that leverage large‑scale spatiotemporal, marketplace, and behavioral signals to improve prediction accuracy.
  • Apply reinforcement learning and optimization techniques to improve logistics decision‑making, assignment strategies, and marketplace efficiency.
  • Build AI‑native product experiences using large language models (LLMs) and vision‑language models (VLMs). For example, transform pickup photos, item verification flows, receipts,
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