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Machine Learning Engineer Quantization Jobs in Houston, TX

Judge Group, Inc.

W2 Machine Learning Engineer

Houston, TX · On-site

$150K - $220K/yr

Machine Learning Engineer W2- NO SPONSORSHIP AVAILABLE Overview: We are seeking a forward-thinking Machine Learning Engineer to evaluate and integrate emerging and start-up Artificial Intelligence ...

Oxy

AI Machine Learning Engineer

Houston, TX · On-site

We are looking for an experienced and innovative individual contributor to fill the position of AI Machine Learning Engineer within our AI Center of Excellence group based in Houston, TX. The ...

Oxy

AI Machine Learning Engineer

Houston, TX

We are looking for an experienced and innovative individual contributor to fill the position of AI Machine Learning Engineer within our AI Center of Excellence group based in Houston, TX. The ...

Vitol

Senior Machine Learning Engineer

Houston, TX · On-site

$117K - $154K/yr

The Machine Learning Engineer at Vitol has visibility and impact across the full project workflow: from working with business stakeholders to help define the project, to data collation and processing ...

Samprasoft

US|Machine Learning Engineer V

Houston, TX · On-site

Machine Learning Engineer Responsibilities: Develop machine learning workflows to enable an Azure-First approach to computer vision applications. Conduct POCs with different vendors in data science ...

Vitol

Senior Machine Learning Engineer

Houston, TX

$117K - $154K/yr

The Machine Learning Engineer at Vitol has visibility and impact across the full project workflow: from working with business stakeholders to help define the project, to data collation and processing ...

Vitol

Senior Machine Learning Engineer

Houston, TX · On-site

$117K - $154K/yr

The Machine Learning Engineer at Vitol has visibility and impact across the full project workflow: from working with business stakeholders to help define the project, to data collation and processing ...

Bespoke Labs

Machine Learning Engineer

Houston, TX

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Vitol

Senior Machine Learning Engineer

Houston, TX · On-site

$116K - $154K/yr

They are seeking an experienced Machine Learning Engineer to join their data science and machine learning team, responsible for delivering machine learning models and applications across various ...

Beth Page tech

Senior Machine Learning Engineer

Houston, TX · On-site

$99K - $137K/yr

Senior Machine Learning Engineer Location: Houston, TX Environment: Standard, 5-days onsite : Must-Have (Technical Expertise & Core Responsibilities) * Deep Neural Networks (DNN): * Hands-on ...

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All JobsMachine Learning Engineer Quantization JobsMachine Learning Engineer Quantization Jobs in Houston, TX

Machine Learning Engineer Quantization information

See Houston, TX salary details

$30.1K

$123K

$184.8K

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 Houston, TX is $122,971.00, according to ZipRecruiter salary data. Most workers in this role earn between $96,900.00 and $148,000.00 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 Houston, TX? For Machine Learning Engineer Quantization jobs in Houston, TX, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Quantization jobs in Houston, TX look for? The top searched job categories for Machine Learning Engineer Quantization jobs in Houston, TX are:
What cities near Houston, TX are hiring for Machine Learning Engineer Quantization jobs? Cities near Houston, TX with the most Machine Learning Engineer Quantization job openings:
Machine Learning Engineer Quantization jobs near you

Machine Learning Engineer

Mariana Minerals

Houston, TX • On-site

Full-time

Posted 9 days ago

Job description

Job Summary:
Mariana Minerals is a software-first, vertically integrated minerals company focused on supplying critical minerals for modern energy and technology. They are seeking a Machine Learning Engineer to develop and improve machine learning systems for mineral refining facilities, working with real data to enhance operational efficiency.
Responsibilities:
• Run reinforcement learning experiments in our physically realistic simulators of mineral processing operations, and help turn the results into better controllers.
• Build and refine pieces of our training environments—reward functions, observations, and action logic—with guidance from senior engineers.
• Train control models, track and interpret their performance, and dig into why a model underperforms.
• Help close the gap between simulation and reality by comparing model behavior against real plant data and flagging where the physics diverges.
• Write clean, well-tested code and contribute to the services that put models into production.
• Partner with process and chemistry experts to understand the unit operations you're modeling.
Qualifications:
Required:
• 0–4 years of experience (including internships or research) in machine learning, reinforcement learning, or scientific computing—or a strong recent graduate with demonstrated project depth.
• Solid grounding in machine learning fundamentals, with working knowledge of modern deep learning; exposure to reinforcement learning is a strong plus.
• Proficiency in Python and comfort reading and debugging an existing codebase.
• Curiosity about physical, industrial systems and eagerness to learn chemistry and process engineering from experts who will challenge your assumptions.
• A self-starter who asks good questions, ships, and escalates blockers early.
Company:
Mariana Minerals is a software-first, vertically integrated minerals company focused on supplying the minerals critical to modern energy, AI, and defense technologies. Founded in , the company is headquartered in San Francisco, CA, US, , with a team of 51-200 employees. The company is currently Growth Stage.

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