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Machine Learning Engineer Quantization Jobs in San Marcos, TX

Neuralink

Machine Learning Engineer

Austin, TX · On-site

Engineers on the BCI team utilize signal processing and machine learning to communicate with the brain. You will have access to the most cutting-edge neural interface hardware and develop ...

Koch Industries

Machine Learning Engineer

Austin, TX · On-site

$170K - $250K/yr

Your Job The ML Engineer will build physics-informed surrogate models on Azure Machine Learning that predict engineering simulation outcomes directly from design parameters. They will be pre ...

Rokt

Senior Machine Learning Engineer

Austin, TX · On-site

$210 - $260/hr

We are hiring Senior Machine Learning Engineers We are hiring engineers with significant expertise in both machine learning and software engineering. You will be working with our engineering and ...

Neurophos Inc

Senior ML Engineer, Optimization

Austin, TX · On-site

$160K - $215K/yr

Mathematics and Quantization Lead FLSA Status : Exempt Position Overview We are seeking an experienced machine learning engineer to develop advanced post-training quantization methods for large ...

Socket.dev

Senior ML Engineer, Optimization

Austin, TX · On-site

$150 - $230/hr

Exempt Position Overview We are seeking an experienced machine learning engineer to develop advanced post-training quantization methods for large language models (LLMs), diffusion models, and other ...

Apple

Senior Machine Learning Engineer

Austin, TX · On-site

$121K - $160K/yr

We are looking for a passionate, highly motivated, and hands-on applied Senior Machine Learning Engineer. This role will assist our Online Retail Decision Automation team by helping to research and ...

PTP

Machine Learning Engineer - REMOTE

Austin, TX · On-site +1

We are looking for a Machine Learning Engineer to help us design and deliver CX solutions that provide our clients with a beautiful customer journey that achieves results. At PTP we value aptitude ...

Apple

Senior Machine Learning Engineer

Austin, TX · On-site

$184K - $324K/yr

We are looking for a passionate, highly motivated, and hands-on applied Senior Machine Learning Engineer. This role will assist our Online Retail Decision Automation team by helping to research and ...

Fluidstack

Machine Learning Engineer

Austin, TX · On-site

$130 - $180/hr

Partner with data engineering and product pods to put predictions in the tools people already use. What We're Looking For * The below is a starting point. We always make space for exceptional people ...

Apple

Senior Machine Learning Engineer

Austin, TX

$184K - $324K/yr

We are looking for a passionate, highly motivated, and hands-on applied Senior Machine Learning Engineer. This role will assist our Online Retail Decision Automation team by helping to research and ...

Apple

Senior Machine Learning Engineer

Austin, TX

$184K - $324K/yr

We are looking for a passionate, highly motivated, and hands-on applied Senior Machine Learning Engineer. This role will assist our Online Retail Decision Automation team by helping to research and ...

Adobe

2027 Intern - Machine Learning Engineer

Austin, TX · On-site +1

The Opportunity Adobe is looking for Machine Learning Engineer interns to work on some of the most impactful AI systems in the industry - from generative AI features and intelligent agents to search ...

New

Fluidstack

Machine Learning Engineer

Austin, TX · On-site

$224K - $344K/yr

Partner with data engineering and product pods to put predictions in the tools people already use. What We're Looking For * The below is a starting point. We always make space for exceptional people ...

Roku

Senior Machine Learning Engineer

Austin, TX

$121K - $160K/yr

We're looking for seasoned engineers with a background in machine learning to aid in this mission. Examples of problems include improving ad relevance, inferring demographics, yield optimization, and ...

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Showing results 21-40

All JobsMachine Learning Engineer Quantization JobsMachine Learning Engineer Quantization Jobs in San Marcos, TX

Machine Learning Engineer Quantization information

See San Marcos, TX salary details

$28.5K

$116.6K

$175.2K

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

As of Sep 3, 2026, the average yearly pay for machine learning engineer quantization in San Marcos, TX is $116,585.00, according to ZipRecruiter salary data. Most workers in this role earn between $91,900.00 and $140,300.00 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 cities near San Marcos, TX are hiring for Machine Learning Engineer Quantization jobs?

Cities near San Marcos, TX with the most Machine Learning Engineer Quantization job openings:

Machine Learning Engineer Quantization jobs near you

Machine Learning Engineer

Neuralink

Austin, TX • On-site

Full-time

Re-posted 29 days ago

Job description

About the Team:

The BCI team develops the software and systems that communicate with the brain. These systems decode raw neural signals into useful actions, such as moving a cursor, typing, or actuating a robotic arm. Additionally, real-world data, such as video feeds, can be encoded into neural data to project images into the visual cortex. We also work closely with users to gather feedback, make improvements, and fundamentally reshape the user experience and interface of the BCI.

About the Role:

Engineers on the BCI team utilize signal processing and machine learning to communicate with the brain. You will have access to the most cutting-edge neural interface hardware and develop state-of-the-art neural encoders and decoders. No prior knowledge of neuroscience is required; we value simple solutions grounded in first principles.

Neuralink designs all hardware in-house, from custom ASICs to thin-film arrays. There is no part of the technical design that cannot change. Learnings from your work will directly influence next-generation device architecture.

Job Responsibilities:
  • Telepathy Product: Develop and refine models that decode neural data, enabling individuals with paralysis to reliably type at 35 words per minute or control robotics arms for activities of daily living.
  • Blindsight Product: Formulate research questions to guide the development of neural networks and signal processing algorithms that will restore vision to those affected by blindness.
  • Utilize your fundamental understanding of neural networks and data science to develop models that serve as the foundation for machine learning applications for BCI.
  • Lead the team by performing at a high standard, setting the bar for how we build and operate our systems.
  • Inform our hardware roadmap by understanding users and identifying the product features that would have the greatest impact on their quality of life.
About You:
  • Experience writing production-level C/C++/Rust and Python
  • Proven track record of designing, building, and shipping real-time ML products
  • Strong foundation in signal processing, algorithms, and software engineering principles
  • Bachelor's degree in relevant field or equivalent experience

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