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Training Engineer Jobs in California (NOW HIRING)

Sciforium

LLM Training Engineer

San Francisco, CA · On-site

$155K - $220K/yr

About the Role As an LLM Training Engineer , you'll work across the full foundation-model stack: pretraining and scaling , post-training and Reinforcement Learning , sandbox environments for ...

Baseten

Post-Training Research Engineer

San Francisco, CA · On-site

$200K - $275K/yr

We are looking for an engineer with strong experience in machine learning and solid foundations in maths and computer science to join our growing Post-Training team at Baseten. Custom models are ...

OpenAI

Training: ML Framework Engineer

San Francisco, CA · On-site

$205K - $445K/yr

About the Role As a Training: ML Framework Engineer, you will work on improving the training throughput for our internal training framework, while enabling researchers to experiment with new ideas.

Voltai

Research Engineer - Mid-Training

Palo Alto, CA · On-site

You will collaborate with compute engineers to scale efficient training across thousands of GPUs and RL environments. You will build high-performance tools to investigate how data and simulation ...

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All JobsTraining Engineer JobsTraining Engineer Jobs in California

Training Engineer information

See California salary details

$30.1K

$67.7K

$114K

How much do training engineer jobs pay per year?

As of Jul 26, 2026, the average yearly pay for training engineer in California is $67,718.00, according to ZipRecruiter salary data. Most workers in this role earn between $51,300.00 and $73,500.00 per year, depending on experience, location, and employer.

What engineers make $300,000 a year?

Senior engineers in specialized fields such as petroleum, aerospace, or software engineering can earn $300,000 or more annually, especially with extensive experience, advanced skills, and leadership roles. High-paying engineering positions often require advanced degrees, certifications, and working in high-demand industries or managerial capacities.

What engineer makes $500,000 a year?

Highly experienced engineers in specialized fields such as petroleum engineering, aerospace engineering, or certain senior roles in software engineering can earn $500,000 or more annually, often including bonuses and stock options. These positions typically require advanced skills, extensive experience, and often involve leadership or executive responsibilities.

What are the key skills and qualifications needed to thrive as a Training Engineer, and why are they important?

To thrive as a Training Engineer, you need a strong background in engineering principles, adult learning methodologies, and often a relevant engineering degree. Familiarity with technical training tools, e-learning platforms, and certifications like Certified Technical Trainer (CTT+) are commonly required. Excellent communication, adaptability, and interpersonal skills help Training Engineers effectively convey complex concepts and engage diverse learners. These skills ensure that technical knowledge is transferred effectively, supporting both employee development and organizational goals.

What are some typical challenges faced by Training Engineers when developing technical training materials for diverse audiences?

Training Engineers often encounter the challenge of creating instructional materials that are accessible and engaging for participants with varying levels of technical expertise. They must balance depth and clarity, ensuring content is neither too simplistic for advanced learners nor too complex for beginners. Additionally, staying current with rapidly evolving technologies and adapting materials for different learning formats—such as in-person workshops, online modules, and hands-on labs—requires strong organizational and communication skills. Collaborating closely with subject matter experts and receiving feedback from trainees are key to overcoming these challenges and ensuring training effectiveness.

What is a training engineer?

A training engineer is a professional responsible for developing, delivering, and managing technical training programs for employees or clients. They often work with engineering teams to create instructional materials, utilize tools like Learning Management Systems (LMS), and ensure training aligns with technical standards and safety protocols.

What is the difference between Training Engineer vs Training Coordinator?

AspectTraining EngineerTraining Coordinator
Required CredentialsBachelor's degree in engineering, technical field; certifications in training or technical areasBachelor's degree in education, HR, or related field; certifications in training or facilitation
Work EnvironmentTechnical settings, manufacturing plants, engineering firmsCorporate offices, educational institutions, HR departments
Employer & Industry UsageManufacturing, aerospace, engineering companiesCorporate training departments, educational organizations
Common Search & Comparison IntentUnderstanding technical training roles, engineering-focused training jobsLearning and development roles, training program management

Training Engineers focus on developing and delivering technical training in engineering and manufacturing environments, often requiring technical degrees and certifications. Training Coordinators handle organizing and managing training programs across various industries, emphasizing facilitation and administrative skills. While both roles involve training, Training Engineers are more technical and specialized, whereas Training Coordinators focus on logistics and program management.

What are Training Engineers?

Training Engineers are professionals who design, develop, and deliver technical training programs, typically for employees or customers using specialized equipment, software, or systems. They combine subject matter expertise with teaching skills to ensure participants understand and can effectively use complex products or technologies. Training Engineers often assess learning needs, create instructional materials, and evaluate training effectiveness to continuously improve learning outcomes.

What engineers make $200,000 a year?

Senior engineers in fields such as software, petroleum, aerospace, and electrical engineering often earn $200,000 or more annually, especially with extensive experience, advanced skills, and relevant certifications. High-paying roles typically involve leadership responsibilities, specialized expertise, or work in high-demand industries and may require advanced degrees or professional licensure.
What are popular job titles related to Training Engineer jobs in California? For Training Engineer jobs in California, the most frequently searched job titles are:
What job categories do people searching Training Engineer jobs in California look for? The top searched job categories for Training Engineer jobs in California are:
What cities in California are hiring for Training Engineer jobs? Cities in California with the most Training Engineer job openings:
What are popular job titles related to Training Engineer jobs in CA? For Training Engineer jobs in CA, the most frequently searched job titles are:
Training Engineer jobs near you
Infographic showing various Training Engineer job openings in California as of July 2026, with employment types broken down into 90% Full Time, 6% Part Time, and 4% Contract. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $67,718 per year, or $32.6 per hour.

LLM Training Engineer

Sciforium

San Francisco, CA • On-site

$155K - $220K/yr

Full-time

Medical, Dental, Vision, Retirement

Posted 19 days ago

Job description

Sciforium is an AI infrastructure company developing next-generation multimodal AI models and a proprietary, high-efficiency serving platform. Backed by multi-million-dollar funding and direct sponsorship from AMD with hands-on support from AMD engineers the team is scaling rapidly to build the full stack powering frontier AI models and real-time applications.
About the Role
As an LLM Training Engineer, you'll work across the full foundation-model stack: pretraining and scaling, post-training and Reinforcement Learning, sandbox environments for evaluation and agentic learning, and deployment + inference optimization. You'll build and iterate quickly on research ideas, contribute production-grade infrastructure, and help deliver models that can serve real-world use cases at scale.
What you'll work on
This role spans multiple tracks - candidates may focus on one or contribute across several. Examples include:
Pretraining & Scaling
  • Train large byte-native foundation models across massive, heterogeneous corpora
  • Design stable training recipes and scaling laws for novel architectures
  • Improve throughput, memory efficiency, and utilization on large GPU clusters
  • Build and maintain distributed training infrastructure and fault-tolerant pipelines

Post-training & RL
  • Develop post-training pipelines (SFT, preference optimization, RLHF/RLAIF, RL)
  • Curate and generate targeted datasets to improve specific model capabilities
  • Build reward models and evaluation frameworks to drive iterative improvement
  • Explore inference-time learning and compute techniques to enhance performance

Sandbox Environments & Evaluation
  • Build scalable sandbox environments for agent evaluation and learning
  • Create realistic, high-signal automated evals for reasoning, tool use, and safety
  • Design offline + online environments that support RL-style training at scale
  • Instrument environments for observability, reproducibility, and iteration speed

Deployment & Inference Optimization
  • Optimize inference throughput/latency for byte-native architectures
  • Build high-performance serving pipelines (KV caching, batching, quantization, etc.)
  • Improve end-to-end model efficiency, cost, and reliability in production
  • Profile and optimize GPU kernels, runtime bottlenecks, and memory behavior

Ideal candidate credentials
Technical strength
  • Strong general software engineering skills (writing robust, performant systems)
  • Experience with training or serving large neural networks (LLMs or similar)
  • Solid grasp of deep learning fundamentals and modern literature
  • Comfort working in high-performance environments (GPU, distributed systems, etc.)

Relevant experience (one or more)
  • Pretraining / large-scale distributed training (FSDP/ZeRO/Megatron-style systems)
  • Post-training pipelines (SFT, RLHF/RLAIF, preference optimization, eval loops)
  • Building RL environments, simulators, or agent frameworks
  • Inference optimization, model compression, quantization, kernel-level profiling
  • Building large ETL pipelines for internet-scale data ingestion and cleaning
  • Owning end-to-end production ML systems with monitoring and reliability

Research orientation
  • Ability to propose and evaluate research ideas quickly
  • Strong experimental hygiene: ablations, metrics, reproducibility, analysis
  • Bias toward building - you can turn ideas into working code and results

Education
  • MS or PhD in Computer Science, Machine Learning, AI, Mathematics, or related field

Benefits include
  • Medical, dental, and vision insurance
  • 401k plan
  • Daily lunch, snacks, and beverages
  • Flexible time off
  • Competitive salary and equity

Equal opportunity
Sciforium is an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.

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