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Machine Learning Engineer Quantization Jobs in Georgia

TheTalentos, LLC

Machine Learning Engineer

Atlanta, GA · On-site

Machine Learning Engineer Atlanta, Georgia, United States About the Job We are supporting a client in the Risk and Insurance industry in the search for a driven Machine Learning Engineer to help us ...

Keylent Inc

Machine Learning Engineer

Atlanta, GA · On-site

$110.10K - $132.20K/yr

Machine Learning Engineer TECHM-JOB-30814 Position :- Machine Learning Engineer Location :- Atlanta GA (Day 1 onsite) Preferably 10+ years' experience having strong Data Analytical Skills with Hands ...

Indeed

Machine Learning Engineer

Atlanta, GA · On-site

As a Machine Learning Engineer, you will prepare datasets, train and optimize models, and maintain and improve model inference services. You will learn and apply new techniques from open source ...

CNN

Machine Learning Engineer I

Atlanta, GA · On-site

CNN is a global leader in news and information, seeking a Machine Learning Engineer I to build and deploy ML systems that enhance personalization, search, recommendations, and content understanding ...

Indeed

Machine Learning Engineer III

Atlanta, GA · On-site

Comscore, Total Visits, March 2025) Day to Day As a Machine Learning Engineer III, you will be a team lead. You will own one of the team's major workstreams, help drive technical direction for the ...

Indeed

Staff Machine Learning Engineer

Atlanta, GA · On-site

Comscore, Total Visits, March 2025) Day to Day As a Machine Learning Engineer III you will be a team lead on the Marketplace Efficiency - Job Reach team. Your team will be responsible for maintaining ...

Omnissa

Staff Machine Learning Engineer

Atlanta, GA · On-site +1

$162.51K - $342.75K/yr

Staff Machine Learning Engineer We are Omnissa. The world is evolving quickly, and organizations everywhere--from global enterprises to educational institutions--are under pressure to deliver ...

Omnissa

Staff Machine Learning Engineer

Atlanta, GA · On-site +1

$162.51K - $342.75K/yr

As a Staff Machine Learning Engineer , you will design, build, and deploy machine learning systems that power predictive analytics, personalization, automation, and intelligent platform behaviors.You ...

Saxon Global

Machine Learning Engineer

Atlanta, GA · On-site

We're partnering with a client to hire ML Search Engineers who are excited about building a modern, machine learning-driven search platform that powers intelligent product discovery across a large e ...

Hire Talent

Lead Machine Learning Engineer

Atlanta, GA · On-site

$98.60K - $129.80K/yr

Lead Machine Learning Engineer Location: Atlanta, GA Duration: 5 Months Duties: In new product design roles: develops and programs integrated software algorithms to structure, analyze and leverage ...

Inovalon

Senior Machine Learning Engineer

Atlanta, GA

$117.80K - $155.30K/yr

The Senior Full-Stack Machine Learning Engineer sits within the Insights Business Unit, which serves as Inovalon's central AI and machine learning hub. This team partners with Provider, Payer, and ...

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Machine Learning Engineer Quantization information

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 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 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 Georgia? For Machine Learning Engineer Quantization jobs in Georgia, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Quantization jobs in Georgia look for? The top searched job categories for Machine Learning Engineer Quantization jobs in Georgia are:
What cities in Georgia are hiring for Machine Learning Engineer Quantization jobs? Cities in Georgia with the most Machine Learning Engineer Quantization job openings:
Machine Learning Engineer Quantization jobs near you

Machine Learning Engineer

TheTalentos, LLC

Atlanta, GA • On-site

Other

This job post has expired today. Applications are no longer accepted.

Job description

Machine Learning Engineer

Atlanta, Georgia, United States

About the Job

We are supporting a client in the Risk and Insurance industry in the search for a driven Machine Learning Engineer to help us bring software development rigor to the ML life-cycle within the business insurance industry. As an experienced innovator partnering with the marketing and growth teams, this is a massive opportunity to drive high growth impact at a hyper-growth startup. Your job is to be a full-stack ML engineer, supercharging all aspects of scaling Machine Learning at NEXT: application design and architecture, scalable deployment of inference solutions as APIs, data enrichment as a service, and model monitoring.

You will be joining an innovative division of based in Atlanta: Data Labs. The mandate of Data Labs is to build software and data solutions that meaningfully impact marketing, funnel, risk, and servicing/claims experiences.

What You'll Do:

  • Empower our team of data scientists to rapidly develop and deploy ML solutions.
  • Leverage software engineering best practices to create and deploy data-intensive and machine learning inference products.
  • Understand the data and dig deep to extract actionable insights.
  • Think creatively and outside the box to answer desired experimental questions as well as expose opportunities to create business value.
  • Work cross-functionally with marketing, engineering, product, senior management, and external partners.

What We Need:

  • 3+ years of hands-on experience in the complete software development life-cycle with demonstrated professional experience with machine learning
  • Strong command of Python and the standard web development frameworks (e.g. Django, Flask, FastAPI) & fluency with database technologies, SQL, and Python data packages
  • Demonstrated experience deploying models and applications to a cloud environment using tools like Docker and Kubernetes.
  • Demonstrated experience with software engineering best practices, such as Test-Driven Development and continuous integration/deployment pipeline
  • Experience with ML-oriented data pipelining tools (dbt, Airflow, Prefect, DVC, etc.)

Unstoppable Qualities:

  • Experience in the insurance industry (strong fintech/lending experience will also be considered)
  • Experience with GitLab

Relocation assistance: Limited assistance

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