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Machine Learning Engineer Quantization Jobs in Texas

Machine Learning Engineer

Austin, TX ยท On-site

$140K - $180K/yr

๐Ÿš€ Machine Learning Engineer ๐Ÿ“ Austin, TX (Hybrid/Remote Considered) ๐Ÿ’ฐ $140,000 - $180,000 Base We're partnering with a fast-growing energy firm looking to hire a Machine Learning Engineer to ...

Job Summary We are seeking a Machine Learning Engineer with strong expertise in machine learning model development, data engineering, and modern cloud-based analytics platforms. This role will focus ...

Position Summary We are seeking a Machine Learning Engineer to help design, implement, and scale AI-enabled solutions that improve software delivery workflows, automate operational processes, and ...

Machine Learning Engineer LOCATIONSan Antonio, TX 78208 CLEARANCETS/SCI Full Poly (Please note this position requires full U.S. Citizenship) KEY SUMMARYWe are seeking a talented and innovative ...

Senior Machine Learning Engineer

Austin, TX ยท On-site

$103K - $142K/yr

We are seeking a Senior Machine Learning Engineer to support our Public Sector initiatives focused ... Implement model optimization techniques such as quantization, pruning, distillation, and hardware ...

About the role We are looking for an experienced Machine Learning Engineer with a strong background in developing and deploying modern machine learning solutions for complex real-world challenges. In ...

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

Machine Learning Engineer LOCATION San Antonio, TX 78208 CLEARANCE TS/SCI Full Poly (Please note this position requires full U.S. Citizenship) KEY SUMMARY We are seeking a talented and innovative ...

About the role We are looking for an experienced Machine Learning Engineer with a strong background in developing and deploying modern machine learning solutions for complex real-world challenges. In ...

SUMMARY The Machine Learning Engineer provides hands-on expertise in designing, implementing, and scaling AI solutions, while collaborating with cross-functional teams to advance machine learning ...

About the Role As a Machine Learning Engineer at Shipwell, you'll play a pivotal role in building and scaling our AI-powered logistics solutions. You'll design, develop, and maintain the data ...

SUMMARY The Machine Learning Engineer provides hands-on expertise in designing, implementing, and scaling AI solutions, while collaborating with cross-functional teams to advance machine learning ...

Machine Learning Engineer

Addison, TX ยท On-site +1

$110K - $130K/yr

... machine learning models and algorithms that will improve Confie's business outcome/customer experience Perform data cleansing, analysis, and feature engineering using Python Ability to work with ...

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

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

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

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Machine Learning Engineer Quantization information

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 Texas look for? The top searched job categories for Machine Learning Engineer Quantization jobs in Texas are:
What cities in Texas are hiring for Machine Learning Engineer Quantization jobs? Cities in Texas with the most Machine Learning Engineer Quantization job openings:

Machine Learning Engineer

X4 Engineering

Austin, TX โ€ข On-site

$140K - $180K/yr

Other

Posted 5 days ago


Job description

๐Ÿš€ Machine Learning Engineer

๐Ÿ“ Austin, TX (Hybrid/Remote Considered)

๐Ÿ’ฐ $140,000 - $180,000 Base


We're partnering with a fast-growing energy firm looking to hire a Machine Learning Engineer to join a highly technical platform engineering team supporting traders, analysts, and quantitative researchers.


This is not a pure data science role. We're looking for an engineer who enjoys building robust production systems, scaling data and ML infrastructure, and working closely with front-office stakeholders to deliver real business impact.


What you'll be doing:

  • Building and maintaining ML and data platforms used for forecasting, optimization, and trading workflows
  • Designing scalable cloud-native infrastructure and deployment pipelines
  • Productionizing quantitative models and analytics tools
  • Developing distributed data and compute systems
  • Working directly with traders and business users to deliver reliable solutions
  • Driving engineering best practices across CI/CD, observability, testing, and automation


Tech stack includes:

Python | AWS | Kubernetes | Docker | Terraform | Airflow | Spark | MLflow | Databricks | Kafka | CI/CD

We're interested in people from backgrounds such as:

โœ” Machine Learning Engineering

โœ” MLOps Engineering

โœ” Platform Engineering

โœ” Software Engineering (with ML/Data exposure)

โœ” Quant Development

โœ” Infrastructure Engineering


Ideal candidates will have strong Python skills, cloud and DevOps experience, and a track record of building production systems. Experience within energy, trading, forecasting, or quantitative environments is beneficial but not essential.


If you'd like to learn more, please send me a message or apply directly.


They prefer the role to be worked on a hybrid model of 1-2 days a week. Salary offered is $140,000-$180,000.