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Machine Learning Engineer Quantization Jobs in Birmingham, AL

Data Engineer III

Birmingham, AL · On-site

$107K - $128K/yr

Prepare data pipelines to enable machine learning workflows DevOps & Modern Engineering Practices * Implement CI/CD pipelines for data engineering deployments * Work within Agile development ...

In this role at PwC, you will apply data, algorithms, and software engineering to build and deploy software and platform systems that create Artificial Intelligence and Machine Learning-based ...

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... programming experience using Visual Basic/VB.NET and/or SQL queries . Experience with UiPath, robotic process automation (RPA), artificial intelligence, or machine learning is a significant plus. Key ...

... s Full-Stack Engineer with expertise in IaC (Terraform), Helm, MySQL, Kubernetes, and CI/CD ... Experience with AI/machine learning technologies is strongly preferred. * Familiarity with TCP/IP ...

Showing results 41-60

Machine Learning Engineer Quantization information

See Birmingham, AL salary details

$29.5K

$120.7K

$181.3K

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

As of Sep 7, 2026, the average yearly pay for machine learning engineer quantization in Birmingham, AL is $120,681.00, according to ZipRecruiter salary data. Most workers in this role earn between $95,100.00 and $145,300.00 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 are popular job titles related to Machine Learning Engineer Quantization jobs in Birmingham, AL?

For Machine Learning Engineer Quantization jobs in Birmingham, AL, the most frequently searched job titles are:

What job categories do people searching Machine Learning Engineer Quantization jobs in Birmingham, AL look for?

The top searched job categories for Machine Learning Engineer Quantization jobs in Birmingham, AL are:

Infographic showing various Machine Learning Engineer Quantization job openings in Birmingham, AL as of August 2026, with employment types broken down into 1% As Needed, 70% Full Time, 26% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $120,681 per year, or $58 per hour.

GIS Data Engineer

EBSCO Industries, Inc.

Birmingham, AL • On-site

Full-time

Re-posted 19 days ago


Key responsibilities

  • Support the Senior GIS Developer in building and maintaining GIS data workflows using open-source tools.

  • Acquire, clean, transform, and load geospatial datasets to support product, engineering, and analytics use cases.

  • Perform quality assurance checks to improve data completeness, consistency, and usability.


Job description

Headquartered in Birmingham, Alabama, Moultrie (www.moultrie.com) is the leader in game feeders and cellular camera innovation, building products used by hunters, property owners, and others for real-time remote monitoring.
We take pride in developing deep user understanding, obsessing about the details, and going the extra mile to show our users we love them. Moultrie is customer-driven - hardware, software, marketing, and customer success teams collaborate to deliver a quality user experience.
We are guided by the following principles: Customer Obsession.; Excellence is the Standard.; Bias for Action.; Act Boldly.; Deliver Results.; Hire and Develop the Best.; Be Curious and Learn.; Win as a Team
Job Summary
Moultrie is actively growing its geospatial capabilities across existing Mapbox-based mobile applications, upcoming web experiences, and support for machine learning and data science workflows. This role helps ensure geospatial data is identified, acquired, transformed, documented, and delivered with quality and reliability.
Job Responsibilities
Key Responsibilities
  • Support the Senior GIS Developer in building and maintaining GIS data workflows using open-source tools.
  • Acquire, clean, transform, and load geospatial datasets to support product, engineering, and analytics use cases.
  • Execute against defined priorities and deadlines while raising risks early and communicating status clearly.
  • Perform quality assurance checks to improve data completeness, consistency, and usability.
  • Document data lineage, transformation methods, assumptions, and known gaps (for example, counties/states with missing data).
  • Contribute to repeatable geospatial processes and help improve internal GIS standards over time.
  • Support occasional off-hours on-call needs for geospatial operations.
  • Participate in interviews and provide hiring feedback when requested.

What Success Looks Like
  • Priority geospatial initiatives are delivered by agreed deadlines with clear documentation.
  • Data products are complete where possible, with clear documentation of missing or unavailable data.
  • GIS workflows are repeatable, documented, and trusted by partner teams.
  • Cross-functional teams can reliably use geospatial outputs in products, analytics, and planning.

Job Requirements
Required Qualifications
  • 3+ years of professional GIS experience.
  • Hands-on experience with QGIS, PostGIS, GDAL, Mapbox, Python, and SQL.
  • Demonstrated ability to build or support cloud hosted geospatial ETL/data preparation workflows.
  • Experience collaborating with cross-functional stakeholders and communicating technical details clearly.
  • Strong attention to detail, time management, curiosity, and ownership mindset.

Preferred Qualifications
  • 5+ years of GIS experience.
  • Experience supporting geospatial needs for product teams and/or machine learning/data science initiatives.
  • Familiarity with cloud computing in Microsoft Azure.
  • Experience with Spatiotemporal Asset Catalogs (STAC) and cloud native geospatial formats.

What We Offer
  • The funding and long-term focus of a privately-held company, combined with the energy of a startup.
  • The opportunity to work with cutting edge geospatial tools in an emerging GIS team.
  • Remote-friendly culture with an optional annual hunting trip.

Essential Job Function
We are an equal opportunity employer and comply with all applicable federal, state, and local fair employment practices laws. We strictly prohibit and do not tolerate discrimination against employees, applicants, or any other covered persons because of race, color, sex, pregnancy status, age, national origin or ancestry, ethnicity, religion, creed, sexual orientation, gender identity, status as a veteran, and basis of disability or any other federal, state or local protected class. This policy applies to all terms and conditions of employment, including, but not limited to, hiring, training, promotion, discipline, compensation, benefits, and termination of employment.
We comply with the Americans with Disabilities Act (ADA), as amended by the ADA Amendments Act, and all applicable state or local law.