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Machine Learning Engineer Quantization Jobs in Lincoln, CA

Micron

SoC Physical Verification Engineer, HBM

Folsom, CA · On-site

$97K - $205K/yr

As a Physical Verification Engineer, you will be a key technical contributor within the ... Drive adoption of machine learning (ML) and artificial intelligence (AI)based physical verification ...

Careers at Teichert

Applied AI Engineer

Sacramento, CA · On-site

The Applied AI Engineer evaluates large language models, agent design patterns, and traditional machine learning approaches, choosing the right tool for each problem and leads governance of AI agents ...

Teichert

Applied AI Engineer

Sacramento, CA · On-site

$117K - $141K/yr

The Applied AI Engineer evaluates large language models, agent design patterns, and traditional machine learning approaches, choosing the right tool for each problem and leads governance of AI agents ...

Deloitte

Sr Databricks Data Engineer

Sacramento, CA · On-site

$122K - $146K/yr

... machine learning solutions The wage range for this role takes into account the wide range of ... As a Databricks Engineer in our AI & Data practice, you will design, build, and optimize cloud ...

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

Machine Learning Engineer Quantization information

See Lincoln, CA salary details

$32.9K

$134.4K

$202K

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

As of Sep 11, 2026, the average yearly pay for machine learning engineer quantization in Lincoln, CA is $134,444.00, according to ZipRecruiter salary data. Most workers in this role earn between $106,000.00 and $161,800.00 per year, depending on experience, location, and employer.

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 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 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 Lincoln, CA look for?

The top searched job categories for Machine Learning Engineer Quantization jobs in Lincoln, CA are:

What cities near Lincoln, CA are hiring for Machine Learning Engineer Quantization jobs?

Cities near Lincoln, CA with the most Machine Learning Engineer Quantization job openings:

Machine Learning Engineer Quantization jobs near you
Infographic showing various Machine Learning Engineer Quantization job openings in Lincoln, CA as of June 2026, with employment types broken down into 2% As Needed, 91% Full Time, 5% Part Time, and 2% Nights. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $134,444 per year, or $64.6 per hour.

Solution Architect

Sacramento, CA

DS Technologies, LLC
See more jobs at DS Technologies, LLCexternal

$62/hr

Full-time

Re-posted 8 days ago

Job description

About US: We are a company that provides innovative, transformative IT services and solutions. We are passionate about helping our clients achieve their goals and exceed their expectations. We strive to provide the best possible experience for our clients and employees. We are committed to continuous improvement and innovation, and we are always looking for ways to improve our services and solutions. We believe in working collaboratively with our clients and employees to achieve success.
 
DS Technologies Inc is looking for Solution Architect role for one of our premier clients.

Job Title: Solution Architect
Location: San Francisco, CA/Sacramento, CA/Plano, TX (Onsite)
Position Type: Contract
Duration: 6 Months
USC/GC Only

Position Overview:
Looking for a seasoned Azure .NET Architect to lead the design and implementation of scalable, secure, and AI-integrated solutions on the Microsoft Azure platform. This role demands a deep understanding of cloud-native architectures, AI/ML technologies, and enterprise-grade .NET development.
Key Responsibilities:

  • Architecture Design: Lead the design of hybrid and multi-cloud environments, integrating AI workloads with Azure services.
  • AI Integration: Architect and implement AI solutions using Azure Machine Learning, Azure OpenAI Service, and Azure Cognitive Services.
  • Cloud Infrastructure: Oversee cloud infrastructure modernization, leveraging Azure Kubernetes Service (AKS), Azure Functions, and microservices.
  • Security & Compliance: Implement and enforce Azure security best practices, identity management, and role-based access controls (RBAC).
  • DevOps & CI/CD: Architect and manage CI/CD pipelines for AI and enterprise applications using Azure DevOps and GitHub Actions.
  • Collaboration: Work closely with AI engineering, data science, and security teams to optimize Azure cloud solutions.
  • Experience: 12–15 years in designing, developing, and supporting enterprise-grade SaaS products using the Microsoft stack on Azure.

Technical Skills:

  • Proficiency in C#, ASP.NET, JavaScript, MVC, and client-side scripting (JavaScript, JQuery, Kendo).
  • Hands-on experience with Azure services including AKS, Azure Functions, Logic Apps, and Azure Machine Learning.
  • Familiarity with AI/ML frameworks and tools such as Infer.NET and ML.NET.
  • Certifications: Microsoft Certified: Azure Solutions Architect Expert (AZ-303/AZ-304) or equivalent.
  • Soft Skills: Strong communication skills to present ideas and solutions, with analytical abilities to troubleshoot issues.

Preferred Qualifications:

  • AI/ML Experience: Exposure to Generative AI technologies and experience in customizing LLM models.
  • Frontend Development: Experience with modern JavaScript frameworks like React
  • Additional Certifications: AI-102 (Azure AI Engineer Associate), DP-100 (Azure Data Scientist Associate), or Databricks ML Data Scientist Certifications. Azure Solutions Architect

Compensation: $62.00 per hour

We are an equal opportunity employer and all qualified applicants will receive
consideration for employment without regard to race, color, religion, sex,
national origin, disability status, protected veteran status, or any other
characteristic protected by law.

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