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Machine Learning Engineer Quantization Jobs in Plano, TX

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 ...

Sr. Machine Learning Engineer Duration: 12 -24 Months Location: Merrimack, NH/ Smithfield, RI/ Westlake, TX/ Durham, NC/ Covington, KY/ Jersey City, NJ/ Boston, MA Candidate should be local or ...

Machine Learning Engineer Hybrid onsite requirement in either Plano, TX - Irvine, CA - Louisville, KY Company Overview: Yum Brands is a global leader in the fast-food industry, with a portfolio of ...

New

As a Machine Learning Engineer, you will play a crucial role in developing and deploying cutting-edge machine learning models and solutions to enhance various aspects of our business operations, from ...

New

As a Machine Learning Engineer, you will play a crucial role in developing and deploying cutting-edge machine learning models and solutions to enhance various aspects of our business operations, from ...

Lead Machine Learning Engineer

Plano, TX · On-site +1

$98K - $129K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

Machine Learning Engineer We are seeking a Machine Learning Engineer to design and develop robust analytics models using statistical and machine learning algorithms. In this role, you will work ...

As a Machine Learning Engineer, you will play a crucial role in developing and deploying cutting-edge machine learning models and solutions to enhance various aspects of our business operations, from ...

Senior Machine Learning Engineer

Plano, TX · On-site

$100K - $137K/yr

Senior Machine Learning Engineer Location: Ann Arbor, Michigan Experience Level: 7+ Years Department: Data Science / Engineering Employment Type: Full-time About the Role: We are looking for an ...

Come join Intuit as a Staff Machine Learning Engineer! In this role, you'll work alongside AI scientists and machine learning engineers to create AI-powered experiences. You'll be expected to help ...

Overview Come join Intuit as a Staff Machine Learning Engineer! In this role, you'll work alongside AI scientists and machine learning engineers to create AI-powered experiences. You'll be expected ...

Senior Machine Learning Engineer

Plano, TX · On-site

$100K - $137K/yr

We turn enterprise data into real-time decisions using advanced machine learning and GenAI. Our team solves hard engineering problems at scale, with real-world industry impact. We're hiring ...

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Machine Learning Engineer Quantization information

See Plano, TX salary details

$30.1K

$123.2K

$185.2K

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

As of Jun 20, 2026, the average yearly pay for machine learning engineer quantization in Plano, TX is $123,243.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,100.00 and $148,300.00 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 Plano, TX? For Machine Learning Engineer Quantization jobs in Plano, TX, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Quantization jobs in Plano, TX look for? The top searched job categories for Machine Learning Engineer Quantization jobs in Plano, TX are:
What cities near Plano, TX are hiring for Machine Learning Engineer Quantization jobs? Cities near Plano, TX with the most Machine Learning Engineer Quantization job openings:
Machine Learning Engineer

Machine Learning Engineer

Compunnel

Plano, TX • On-site

Contractor

Posted 19 days ago


Job description

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 on building ML-ready data architectures, developing scalable machine learning solutions, and supporting enterprise analytics initiatives. The ideal candidate will possess hands-on experience with Azure Databricks, Python-based model development, Medallion Architecture, and MLOps practices, along with the ability to collaborate effectively with business and technical stakeholders.
Key Responsibilities
  • Design, develop, and maintain machine learning solutions that support advanced analytics and predictive modeling initiatives.
  • Build and optimize ML-ready data pipelines and data architectures using Medallion Architecture principles.
  • Develop and manage data ingestion, transformation, and curation processes across Bronze, Silver, and Gold data layers.
  • Create scalable feature engineering workflows and production-grade machine learning assets.
  • Design and implement machine learning pipelines using Azure Databricks and related cloud technologies.
  • Leverage Delta Lake, MLflow, and workflow orchestration tools to operationalize machine learning models and data transformations.
  • Develop and maintain Python-based machine learning models, feature engineering processes, and MLOps automation solutions.
  • Build and optimize SQL transformations, views, and ELT pipelines to support analytics and machine learning workloads.
  • Design and maintain feature stores, semantic layers, and curated datasets that support enterprise reporting and machine learning initiatives.
  • Integrate machine learning outputs into analytics platforms, dashboards, and business intelligence solutions.
  • Collaborate with business stakeholders, technical teams, and leadership to translate business requirements into scalable data and machine learning solutions.
  • Establish engineering standards, best practices, and scalable development processes for machine learning and data engineering initiatives.
  • Monitor data quality, model performance, and operational effectiveness of machine learning solutions.

Required Qualifications
  • 5-7 years of hands-on experience in machine learning engineering and data engineering.
  • 10+ years of experience delivering enterprise-scale data, analytics, and machine learning solutions.
  • Strong experience building machine learning models and supporting model development using Python.
  • Extensive experience with Azure Databricks for machine learning, feature engineering, and data engineering workloads.
  • Deep understanding of Medallion Architecture, including Bronze, Silver, and Gold data layer design and implementation.
  • Experience designing ML-ready data architectures and scalable data engineering solutions.
  • Experience migrating workloads to Databricks and implementing modern data platform architectures.
  • Hands-on experience with Delta Lake, MLflow, and Databricks Workflows.
  • Strong proficiency in Python for model development, feature engineering, and MLOps automation.
  • Advanced SQL skills with experience building optimized transformations, views, and ELT pipelines.
  • Experience designing feature stores, semantic models, and machine learning-ready datasets.
  • Strong understanding of machine learning lifecycle management, data engineering best practices, and scalable architecture patterns.
  • Ability to lead technical initiatives and establish engineering standards and development practices.
  • Strong business acumen and ability to communicate effectively with technical and business stakeholders.
  • Experience working in collaborative, fast-paced environments that encourage experimentation and innovation.

Preferred Qualifications
  • Experience working within Microsoft Azure cloud environments.
  • Experience integrating machine learning outputs into analytics platforms and business intelligence solutions.
  • Experience designing dashboards and reporting solutions that surface machine learning insights, data quality metrics, and model performance indicators.
  • Familiarity with Power BI, including DAX, semantic modeling, and visualization best practices.
  • Experience supporting enterprise-scale analytics, data science, and AI initiatives.
  • Experience mentoring technical teams and providing technical leadership on machine learning and data engineering projects.

Compunnel logo

About Compunnel

Sourced by ZipRecruiter

Compunnel is a well-known company located in Plainsboro, NJ, US, recognized in the industry of IT Services and Solutions. Established in 1989, Compunnel offers a suite of services that help businesses integrate technology efficiently into their operations, a recognizable name in the IT solutions sphere for over three decades. The company’s service portfolio includes Digital Transformation, Business Intelligence, Cloud Services, Cybersecurity, and Application Modern Services, among others. Guided by its mission "to innovate with industry-leading digital solutions and disruptive tech strategies for unimagining business growth," the company underlines its commitment to offering out-of-the-box solutions to its clients. Remarkable achievements of the company include serving more than 30 Fortune 500 companies and providing job opportunities for over 50,000 individuals.

Industry

It services

Company size

501 - 1,000 Employees

Headquarters location

Plainsboro, NJ, US

Year founded

1994

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