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Machine Learning Engineer Quantization Jobs in Visalia, CA

PG&E Corporation

Data Scientist, Expert

Springville, CA · Hybrid

Bachelor's Degree in Data Science, Machine Learning, Computer Science, Physics, Econometrics or Economics, Engineering, Mathematics, Applied Sciences, Statistics, or equivalent field * 6 years in ...

New

PG&E Corporation

Data Scientist, Expert

Coalinga, CA · Hybrid

Bachelor's Degree in Data Science, Machine Learning, Computer Science, Physics, Econometrics or Economics, Engineering, Mathematics, Applied Sciences, Statistics, or equivalent field * 6 years in ...

New

PG&E Corporation

Data Scientist, Expert

Lemoore, CA · Hybrid

Bachelor's Degree in Data Science, Machine Learning, Computer Science, Physics, Econometrics or Economics, Engineering, Mathematics, Applied Sciences, Statistics, or equivalent field * 6 years in ...

New

PG&E Corporation

Data Scientist, Expert

Kerman, CA · Hybrid

Bachelor's Degree in Data Science, Machine Learning, Computer Science, Physics, Econometrics or Economics, Engineering, Mathematics, Applied Sciences, Statistics, or equivalent field * 6 years in ...

New

PG&E Corporation

Data Scientist, Expert

Caruthers, CA · Hybrid

Bachelor's Degree in Data Science, Machine Learning, Computer Science, Physics, Econometrics or Economics, Engineering, Mathematics, Applied Sciences, Statistics, or equivalent field * 6 years in ...

New

Trilyon, Inc.

Program/Project Analyst 1

Tulare, CA · On-site

$30 - $32/hr

... Machine Learning, and Technical Writing, we consistently exceed expectations in catering to a wide ... Demonstrates working knowledge of 1 programming language, report production, and database ...

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All JobsMachine Learning Engineer Quantization JobsMachine Learning Engineer Quantization Jobs in Visalia, CA

Machine Learning Engineer Quantization information

See Visalia, CA salary details

$32K

$130.9K

$196.7K

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

As of Jul 8, 2026, the average yearly pay for machine learning engineer quantization in Visalia, CA is $130,916.00, according to ZipRecruiter salary data. Most workers in this role earn between $103,200.00 and $157,600.00 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 job categories do people searching Machine Learning Engineer Quantization jobs in Visalia, CA look for? The top searched job categories for Machine Learning Engineer Quantization jobs in Visalia, CA are:
What cities near Visalia, CA are hiring for Machine Learning Engineer Quantization jobs? Cities near Visalia, CA with the most Machine Learning Engineer Quantization job openings:
Machine Learning Engineer Quantization jobs near you
Data Scientist, Expert

Data Scientist, Expert

PG&E Corporation

Springville, CA • Hybrid

Full-time

Posted 2 days ago

New

Job description

Requisition ID # 173213 

Job Category: Information Technology 

Job Level: Individual Contributor

Business Unit: Energy Delivery

Work Type: Hybrid

Job Location: San Ramon; Alameda; Alta; American Canyon; Angels Camp; Antioch; Auberry; Auburn; Avenal; Avila Beach; Bakersfield; Balch Camp; Bay Point; Bear Valley; Belden; Bellota; Belmont; Benicia; Berkeley; Brentwood; Brisbane; Buellton; Burney; Buttonwillow; Calistoga; Campbell; Canyon Dam; Canyondam; Capitola; Caruthers; Chico; Clearlake; Clovis; Coalinga; Colusa; Concord; Concord; Corcoran; Cottonwood; Cupertino; Daly City; Danville; Davis; Dinuba; Downieville; Dublin; Emeryville; Eureka; Fairfield; Folsom; Fort Bragg; Fortuna; Fremont; French Camp; Fresno; Fresno; Fulton; Garberville; Geyserville; Gilroy; Goodyear; Grass Valley; Guerneville; Half Moon Bay; Hayward; Hinkley; Hollister; Holt; Huron; Jackson; Kerman; King City; Lakeport; Lemoore; Lincoln; Linden; Livermore; Lodi; Loomis; Los Banos; Lower Lake; Madera; Magalia; Manteca; Manton; Mariposa; Martell; Marysville; Maxwell; Menlo Park; Merced; Meridian; Millbrae; Milpitas; Modesto; Monterey; Montgomery Creek; Morgan Hill; Morro Bay; Moss Landing; Mountain View; Napa; Needles; Newark; Newman; Novato; Oakdale; Oakhurst; Oakland; Oakley; Olema; Orinda; Orland; Oroville; Palo Alto; Palo Cedro; Paradise; Parkwood; Paso Robles; Petaluma; Pioneer; Pismo Beach; Pittsburg; Placerville; Pleasant Hill; Pleasanton; Point Arena; Potter Valley; Quincy; Rancho Cordova; Red Bluff; Redding; Richmond; Ridgecrest; Rio Vista; Rocklin; Roseville; Round Mountain; Sacramento; Salida; Salinas; San Bruno; San Carlos; San Francisco; San Francisco; San Jose; San Luis Obispo; San Mateo; San Rafael; Sanger; Santa Cruz; Santa Maria; Santa Nella; Santa Rosa; Selma; Shaver Lake; Sonoma; Sonora; South San Francisco; Springville; Stockton; Storrie; Taft; Tracy; Turlock; Twain; Ukiah; Vacaville; Vallejo; Walnut Creek; Wasco; Watsonville; West Sacramento; Wheatland; Whitmore; Willits; Willow Creek; Willows; Windsor; Winters; Woodland; Yuba City

Department Overview

Applied Technology Services (ATS) has been providing technology-based, innovative, high-value services to the company for over 50 years. ATS is a multidisciplinary team of over 130 engineers, scientists, and technicians. The ATS vision is to be a forward-thinking, technological leader providing high-value solutions and services needed across the Company. ATS high value services also help proactively avoid future problems by specifying equipment, materials and methods that are best practices in the industry.

Position Summary

Designs, develops, and executes scripts, programs, models, algorithms, and processes, using structured and unstructured data from disparate sources and sizes, generating for defensible, valid, scalable, reproducible models (predictive or optimization) for problem solving and strategy development. Participates in internal and external communities of practice in data science/artificial intelligence/machine learning to advance knowledge in the field. Educates the non-technical community on advantages, risks, and maturity levels of data science solutions. 

This position is hybrid, working from your remote office and your assigned location based on business need. Regular presence is required in San Ramon, once every two weeks.

PG&E is providing the salary range that the company in good faith believes it might pay for this position at the time of the job posting. This compensation range is specific to the locality of the job.  The actual salary paid to an individual will be based on multiple factors, including, but not limited to, specific skills, education, licenses or certifications, experience, market value, geographic location, and internal equity.  Although we estimate the successful candidate hired into this role will be placed towards the middle or entry point of the range, the decision will be made on a case-by-case basis related to these factors.

Bay Area Minimum: $140,000

Bay Area Mid: $189,000
Bay Area Maximum: $238,000

California Minimum: $133,000

California Mid: $180,000

California Maximum:$226,000

This job is also eligible to participate in PG&E’s discretionary incentive compensation programs. 

Job Responsibilities

  • Researches and applies advanced knowledge of existing and emerging data science principles, theories, and techniques to inform business decisions.
  • Creates advanced data mining architectures / models / protocols, statistical reporting, and data analysis methodologies to identify trends in structured and unstructured data sets
  • Extracts, transforms, and loads data from dissimilar sources from across PG&E
  • Applies data science/ machine learning /artificial intelligence methods to develop defensible and reproducible predictive or optimization models that involve multiple facets and iterations in algorithm development. 
  • Writes and documents reusable python functions and modular python code for data science.
  • Assesses business implications associated with modeling assumptions, inputs, methodologies, technical implementation, analytic procedures and processes, and advanced data analysis.
  • Works with sponsor departments and company subject matter experts to understand application and potential of data science solutions that create value.
  • Presents findings and makes recommendations to senior management.
  • Act as peer reviewer of complex models 

Qualifications

Minimum:

  • Bachelor’s Degree in Data Science, Machine Learning, Computer Science, Physics, Econometrics or Economics, Engineering, Mathematics, Applied Sciences, Statistics, or equivalent field
  • 6 years in data science OR no experience, if possess Doctoral Degree or higher, as described above

Desired:

  • Doctorate Degree in Data Science, Machine Learning, or job-related discipline or equivalent experience
  • Relevant industry (electric or gas utility, renewable energy, analytics consulting, etc.) experience
  • Active participation in the external data science/artificial intelligence/machine learning community of practice, as demonstrated through volunteering in professional organizations for the advancement of the field, presentations in conferences or publications to disseminate data science knowledge and topics, or similar activities.
  • Knowledge of industry trends and current issues in job-related area of responsibility as demonstrated through peer reviewed journal publications, conference presentations, open source contributions or similar activities
  • Competency with commonly used data science and/or operations research programming languages, packages, and tools for building data science/machine learning models and algorithms  
  • Proficiency in explaining in breadth and depth technical concepts including but not limited to statistical inference, machine learning algorithms, software engineering, model deployment pipelines.
  • Mastery in clearly communicating complex technical details and insights to colleagues and stakeholders
  • Mastery of the mathematical and statistical fields that underpin data science, specifically focused in reliability and failure analysis
  • Demonstrated proficiency in enterprise data platforms and analytics tools, including Foundry, SAP, and Power BI, with the ability to integrate and analyze data across ERP systems and visualization environments.

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