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Machine Learning Engineer Quantization Jobs in Simi Valley, CA

Machine Learning Engineer

Burbank, CA ยท On-site

$109K - $143K/yr

Overview We are seeking a Senior Lead / Lead ML Platform Engineer to architect and own the ... learning. * High-Performance Inference: Design and maintain K8s-based inference servers (e.g ...

Machine Learning Engineer

Burbank, CA ยท On-site

$109K - $143K/yr

Overview We are seeking a Senior Lead / Lead ML Platform Engineer to architect and own the ... learning. * High-Performance Inference: Design and maintain K8s-based inference servers (e.g ...

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Machine Learning Engineer Quantization information

See Simi Valley, CA salary details

$32.5K

$132.9K

$199.8K

How much do machine learning engineer quantization jobs pay per year?

As of Jun 19, 2026, the average yearly pay for machine learning engineer quantization in Simi Valley, CA is $132,928.00, according to ZipRecruiter salary data. Most workers in this role earn between $104,800.00 and $160,000.00 per year, depending on experience, location, and employer.

What are some common challenges Machine Learning Engineers face when implementing quantization techniques in production models?

Machine Learning Engineers working on quantization often encounter challenges such as balancing reduced model size and computational efficiency with maintaining acceptable accuracy levels. Adapting quantization methods to different hardware platforms can also require significant testing and optimization. Additionally, engineers must frequently address compatibility issues with existing deployment pipelines and ensure that quantization-aware training is properly integrated to minimize performance degradation. Collaboration with hardware and software teams is essential to streamline deployment and achieve optimal results.

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

To thrive as a Machine Learning Engineer Quantization, you need a solid background in machine learning, deep learning, and computer science, typically supported by a degree in a related field. Familiarity with quantization techniques, frameworks such as TensorFlow Lite or PyTorch, and experience with hardware accelerators are crucial. Strong problem-solving skills, attention to detail, and effective collaboration set top performers apart. These capabilities are vital for efficiently deploying high-performing models on resource-constrained devices and ensuring scalable, real-world AI solutions.

What does a Machine Learning Engineer Quantization do?

A Machine Learning Engineer specializing in quantization focuses on optimizing machine learning models by reducing their size and computational requirements without significantly sacrificing accuracy. This involves converting model parameters and computations from high-precision formats (like 32-bit floating point) to lower-precision formats (such as 8-bit integers). Quantization enables faster inference, lower memory usage, and allows models to run efficiently on edge devices and mobile platforms. These engineers work closely with data scientists and hardware teams to implement, test, and validate quantized models in production environments.

What is the difference between Machine Learning Engineer Quantization vs Data Scientist?

AspectMachine Learning Engineer QuantizationData Scientist
Required CredentialsBachelor's or master's in CS, ML, or related; certifications in ML or AIBachelor's or master's in statistics, CS, or related; certifications in data analysis or statistics
Work EnvironmentDeveloping optimized ML models, deploying quantized models for efficiencyAnalyzing data, building predictive models, interpreting results
Industry UsageTech companies, AI hardware firms, embedded systemsFinance, healthcare, marketing, research institutions

Machine Learning Engineer Quantization focuses on optimizing ML models for deployment efficiency, often working closely with hardware and software teams. Data Scientists analyze data and build models for insights. While both roles require ML knowledge, quantization engineers specialize in model compression techniques, whereas data scientists focus on data analysis and interpretation.

What are popular job titles related to Machine Learning Engineer Quantization jobs in Simi Valley, CA? For Machine Learning Engineer Quantization jobs in Simi Valley, CA, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Quantization jobs in Simi Valley, CA look for? The top searched job categories for Machine Learning Engineer Quantization jobs in Simi Valley, CA are:
What cities near Simi Valley, CA are hiring for Machine Learning Engineer Quantization jobs? Cities near Simi Valley, CA with the most Machine Learning Engineer Quantization job openings:
Machine Learning Engineer- Remote

Machine Learning Engineer- Remote

Harbor Freight Tools

Calabasas, CA โ€ข On-site, Remote

$110K - $166K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 21 hours ago


Job description

Job Description
The ML Engineer is responsible for the overall development, deployment, and support of our machine learning operations Harbor Freight. This includes the architecture and implementation of tools for model training, model monitoring, feature stores, model deployments, and model maintenance.
This role requires working with multiple levels of the organization, data science teams, application teams, security, software engineering, and business partners. It requires an experienced machine learning engineer with excellent business acumen, very strong technical skills, and data modeling / data warehousing expertise.
This position is technical and analytical in nature.
Duties and Responsibilities
  • Work closely with data scientists and IT in the development and implementation of our Enterprise AI platform.
  • Build and maintain an industry leading MLOps tech stack.
  • Mentor data scientists within the business, ensuring we're building best-in-class models.
  • Optimize the scalability, performance, and reliability of our models by implementing best practices and leveraging industry-standard technologies.
  • Streamline data ingestion, pre-processing, feature engineering, and model training workflows to improve efficiency and reduce latency.
  • Design, build, and maintain a secure and scalable CI/CD framework for data science teams.

Scope
  • Staff supervision and development: No
  • Decision making: Recommends policy and resolves problems
  • Travel: Up to 5%
  • Flex Designation: Anywhere

The anticipated salary range for this position is $110,800 - $166,100 depending on location, knowledge, skills, education and experience. This position is also eligible for an annual discretionary bonus. In addition, we offer comprehensive and competitive benefits to Associates (and their families) such as medical, dental, vision, life insurance, short-term and long-term disability. Eligible Associates are able to enroll in our company's 401k plan. Associates will accrue paid time off up to 236 hours per year (inclusive of PTO, floating holidays, and paid holidays). Paid sick time up to 80 hours per year unless otherwise required by law.
Requirements
Education and Experience
Education Requirements
  • Bachelor's in Computer Science, Mathematics, Statistics, Engineering, or a related field.
  • Master's degree or Ph.D. is a plus.

Years of Experience
  • 2-4 years experience as ML engineer or data scientist in a Big Data ecosystem, with a desire to assume greater responsibilities as a leader and mentor, while still being hands-on.
  • 2-4 years experience developing, tuning, operationalizing, and monitoring enterprise ML models at scale.
  • 2-4 years experience with public cloud platforms & systems (AWS, GCP, Azure).

Skills
  • Strong knowledge of distributed computing, data structures, data mapping, data warehouse, data mining, business analytics, software development, replication, and distributed/relational databases.
  • Strong technical expertise in scripting (Python) database languages (SQL), and PySpark for model development.
  • Excellent time management and planning skills, organized with the ability to multi-task, exceptional follow-up skills and able to meet deadlines.
  • Excellent written, oral, and interpersonal communication skills, with ability to communicate effectively.
  • Experience to tracking projects and goals to successful completion (with visible metrics).
  • Ability to stay abreast of significant technological developments that may impact the business.
  • Equipped to effectively prioritize, collaborate and excel in a fast-paced, high-pressure environment.
  • Highly self-motivated, self-directed, and attentive to detail, with an emphasis on accuracy, detail, and timeliness.
  • Understanding and experience with project management methodologies.
  • Ability to manage multiple projects concurrently.

Physical Requirements
General office environment requiring ability to:
  • Stand, walk, sit for extended periods of time.
  • Speak and listen to others in person and over the phone and video conferencing.
  • Use keyboard and read from computer screen and reports.
  • The ability to lift up to 15 lbs.

Safety
  • Must be able to perform this job safely in accordance with standard operating procedures and good manufacturing practices, without endangering the health or safety of self or others.

About Harbor Freight Tools
We're a 45 year-old, $8 billion national tool retailer with the energy, enthusiasm, and growth potential of a start-up. We have over 1,600 stores in 48 states across the country and are opening several new locations every week. We offer our customers more than 7,000 tools and accessories, from hand tools and generators to air and power tools, from shop equipment to automotive tools. We provide our customers with the right tool for the right job at the right price, always delivering quality and value.