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Machine Learning Engineer Quantization Jobs in Visalia, CA

DataAnnotation

SDLC Engineer - AI Trainer

Visalia, CA · Remote

$50 - $100/hr

As a DataAnnotation's coder, you'll be part of a growing community of over 100,000 professionals -- including front-end, back-end, full-stack, machine learning, and other engineers -- who are driving ...

DataAnnotation

QA Engineer - AI Trainer

Visalia, CA · Remote

$50 - $100/hr

As a DataAnnotation's coder, you'll be part of a growing community of over 100,000 professionals -- including front-end, back-end, full-stack, machine learning, and other engineers -- who are driving ...

Symbotic

System Engineer

Porterville, CA

The System Engineer focuses on troubleshooting,maintaining, and stabilizing complex electro ... Applying next-gen technology, high-density storage and machine learning to solve today's complex ...

Symbotic

System Engineer

Porterville, CA · On-site

The System Engineer focuses on troubleshooting, maintaining, and stabilizing complex electro ... Applying next-gen technology, high-density storage and machine learning to solve today's complex ...

PG&E Corporation

Data Scientist, Expert

Dinuba, 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

Selma, 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

Corcoran, 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 ...

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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
Algorithm Developer (Quant Researcher) - 2026 PhDs

Algorithm Developer (Quant Researcher) - 2026 PhDs

Hudson River Trading

London, CA • On-site

Other

Posted 3 days ago

Job description

Hudson River Trading (HRT) is seeking exceptional full-time PhD students to join our Algorithm Development team. Algorithm Developers are responsible for building and maintaining the models that drive our trading. A typical day involves applying rigorous statistical analysis to vast quantities of market and financial data to produce predictive trading models. 

In this role, you will work alongside fellow Algorithm Developers and Software Engineers to research, develop, and test novel order execution and model training methods to increase trading efficiency. This will involve running models live on our high-performance trading infrastructure and analyzing daily performance to maintain ongoing profitability. You can expect to apply your advanced academic research experience and expertise to impactful real world problems in trading across time horizons and machine learning strategies.

Profile

  • You're excited to apply your research expertise to identify new opportunities in worldwide markets  
  • You enjoy both self-guided research and collaborating with others to analyze and fix problems efficiently
  • You are a critical thinker who can learn and implement new skills in a fast-changing environment

Qualifications

  • You are a full-time PhD student in a quantitative discipline (math, physics, computer science, statistics, or a related program) who is eligible for full-time roles in 2026
  • Fluency in Python
  • Experience with statistical analysis, numerical programming, or machine learning in Python, Pandas/Numpy, R, and/or MATLAB
  • Brilliant analytical and problem-solving skills
  • Ability to work creatively and independently on long-term technical problems

The estimated base salary for this position is 300,000 USD per year (or local equivalent). The base pay offered may vary depending on multiple individualized factors, including location, job-related knowledge, skills, and experience. This role will also be eligible for discretionary performance-based bonuses and a competitive benefits package.

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