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Machine Learning Specialist Jobs in California (NOW HIRING)

HCVT

Senior Data & Analytics Specialist

Irvine, CA · On-site

About the Role The Senior Data & Analytics Specialist is responsible for designing, building, and ... Define data models, standards, and architecture that support reporting, analytics, machine learning ...

HCVT

Senior Data & Analytics Specialist

Irvine, CA · Hybrid

About the Role The Senior Data & Analytics Specialist is responsible for designing, building, and ... Define data models, standards, and architecture that support reporting, analytics, machine learning ...

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All JobsMachine Learning Specialist JobsMachine Learning Specialist Jobs in California

Machine Learning Specialist information

See California salary details

$20.2K

$53.2K

$95.7K

How much do machine learning specialist jobs pay per year?

As of Aug 21, 2026, the average yearly pay for machine learning specialist in California is $53,219.00, according to ZipRecruiter salary data. Most workers in this role earn between $38,500.00 and $59,700.00 per year, depending on experience, location, and employer.

What is a machine learning specialist?

A Machine Learning Specialist is a professional who designs, develops, and implements machine learning models and algorithms to solve complex problems. They work with large datasets, use statistical and computational techniques, and optimize models for accuracy and efficiency. Their role often involves data preprocessing, feature engineering, model selection, and deployment. They collaborate with data scientists, software engineers, and domain experts to integrate machine learning solutions into business applications.

What are the key skills and qualifications needed to thrive as a machine learning specialist?

To thrive as a Machine Learning Specialist, you need a strong background in mathematics, programming (Python, R), and data analysis, typically supported by a relevant degree in computer science or a related field. Experience with machine learning frameworks such as TensorFlow, PyTorch, and knowledge of cloud platforms like AWS or Azure is highly valued, and certifications in these can enhance your qualifications. Strong problem-solving skills, curiosity, and the ability to communicate complex concepts clearly make someone stand out in this field. These skills and qualifications are crucial for effectively developing, deploying, and explaining machine learning solutions to diverse stakeholders.

What are some common challenges a machine learning specialist might face?

Machine Learning Specialists often encounter challenges such as ensuring data quality, selecting appropriate algorithms, and scaling solutions for real-world application. Navigating the complexities of messy or incomplete datasets and tuning models for optimal performance can be demanding. Balancing innovation with practical deployment constraints, such as computational resources and integration with existing systems, is also common. To address these challenges, collaboration with data engineers, domain experts, and product teams is essential, and ongoing professional development helps specialists stay ahead in this rapidly evolving field.

Is machine learning a high paying job?

Machine learning specialists typically earn high salaries due to the specialized skills required, such as programming, data analysis, and knowledge of algorithms. Salaries vary by experience, location, and industry, but overall, the role is considered well-compensated within the tech field.

What are popular job titles related to Machine Learning Specialist jobs in California?

For Machine Learning Specialist jobs in California, the most frequently searched job titles are:

What job categories do people searching Machine Learning Specialist jobs in California look for?

The top searched job categories for Machine Learning Specialist jobs in California are:

Machine Learning Specialist jobs near you
Infographic showing various Machine Learning Specialist job openings in California as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 18% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $53,219 per year, or $25.6 per hour.

AI Engineer - Reinforcement Learning

Logical Intelligence

San Francisco, CA

Full-time

Re-posted 3 days ago

Job description

Who we are

At Logical Intelligence, we're revolutionizing software development with AI-powered formal verification. We've developed groundbreaking agents that provide mathematical guarantees of code correctness, ensuring that software behaves exactly as intended while proactively identifying bugs and security vulnerabilities. Our novel foundation model enables scalable, precise reasoning for formally verifiable code across Rust, Golang, and smart contract VMs. We've won ​​a well-known formal verification benchmark called PutnamBench, which consists of 672 hard math problems from the William Lowell Putnam Exam, the oldest collegiate mathematics competition in North America. Backed by a world-class team – including ICPC champions, a Fields Medalist and an ACM Turing Award winner – we're building the future where all code is provably correct.

About the role

Join our team as an AI Engineer and help us push the boundaries of what's possible in logical reasoning! We're looking for a motivated individual to design, implement, and refine efficient Large Language Models (LLMs) pipelines for scaled distributed training. You'll be at the forefront of designing and refining algorithms that go beyond the capabilities of traditional LLMs. You'll work closely with a talented team of AI experts, EBM specialists, formal verification engineers, and software developers to create groundbreaking solutions.

What you'll do
  • Implement new reasoning algorithms and models
  • Evaluate reasoning approaches, including latent space reasoning
  • Pre-train, fine-tune, and modify the State-of-the-Art LLMs
  • Optimizing and scaling LLM pipelines
  • Adjust frameworks and interfaces to accelerate machine learning development
  • Derive practical solutions and integrate them with the results of other teams to provide the best overall resolution
Qualifications
  • Deep understanding of transformers' internals, and ability to make radical changes to the architecture and handle higher-order derivatives
  • Expertise in programming languages and tools critical for high-performance computing in Python/C++ and machine learning including Deep Learning frameworks like PyTorch /TensorFlow/JAX
  • Expertise in optimizing machine learning systems, including general techniques and LLM-specific optimizations
  • Understanding state-of-the-art approaches in LLM reasoning
  • Ability to understand complex learning approaches, such as energy-based models
  • Experience with basic distributed optimization techniques
  • Familiarity with torch.compile or similar performance optimization tools
  • Understanding of LLM architectures and LLM fine tuning internals
  • 3+ years of production experience in ML Infra, DataOps, distributed training. Proficiency with Kubernetes clusters and distributed compute assets
  • Strong communication and teamwork skills
  • Readiness to explore and promote cutting edge technologies in ML Infrastructure domain and beyond

Bonus Points:

  • Demonstrated publications in any of the major conferences
  • Experience in EBM or latent reasoning
  • Demonstrated publications in any of the major conferences
  • Mathematical Reasoning – discrete math and logic

logicalintelligence.com