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Machine Learning Engineer Quantization Jobs in Ohio

POSITION SUMMARY Flexjet is seeking a motivated Entry-Level Machine Learning Engineer to join our team. In this role, you will work alongside experienced engineers and data scientists to build ...

ClifyX is a company that specializes in AI solutions, and they are seeking a Machine Learning Engineer. The role involves designing advanced ML models, managing MLOps pipelines, and collaborating ...

Machine Learning Engineer II

Columbus, OH

$94K - $128K/yr

Machine Learning II Engineer - Incydr Product Development Mimecast is at the forefront of the cybersecurity industry, delivering innovative solutions to protect businesses and individuals from ...

Machine Learning Engineer II

Columbus, OH · On-site

$94K - $128K/yr

Machine Learning II Engineer - Incydr Product Development Mimecast is at the forefront of the cybersecurity industry, delivering innovative solutions to protect businesses and individuals from ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Machine Learning Engineer

Beavercreek, OH · On-site

$51.75 - $68.50/hr

Etegent is seeking Machine Learning Engineers (MLEs) to work with our Intelligence, Surveillance, and Reconnaissance (ISR) group based in the Beavercreek office. MLEs will work in a team environment ...

Machine Learning Engineer

Cleveland, OH · On-site

$62K - $100K/yr

As an AI Engineering team member, you will be instrumental in advancing new features and/or solutions from the Proof of Concept stage to full production readiness. Your role involves refining and ...

New

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

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Machine Learning Engineer Quantization information

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 Ohio?

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

What cities in Ohio are hiring for Machine Learning Engineer Quantization jobs?

Cities in Ohio with the most Machine Learning Engineer Quantization job openings:

Machine Learning Engineer

Flexjet

Cleveland, OH • On-site

Full-time

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


Flexjet rating

8.2

Company rating: 8.2 out of 10

Based on 24 frontline employees who took The Breakroom Quiz

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Job description

POSITION SUMMARY

Flexjet is seeking a motivated Entry-Level Machine Learning Engineer to join our team. In this role, you will work alongside experienced engineers and data scientists to build, deploy, and maintain machine learning models. This is an excellent opportunity for someone early in their career who is eager to develop hands-on experience with real-world ML systems.

DUTIES & RESPONSIBILITIES

  • Assist in developing and training machine learning models
  • Support the creation and maintenance of data pipelines
  • Help deploy ML models into production under guidance
  • Clean, preprocess, and analyze datasets for model training
  • Collaborate with team members to solve business problems using data
  • Monitor model performance and help troubleshoot issues
  • Document code, processes, and model behavior

REQUIRED SKILLS & QUALIFICATIONS

  • Bachelor's degree in Computer Science, Data Science, Engineering, or related field (or equivalent practical experience)
  • Basic proficiency in Python
  • Familiarity with machine learning concepts (regression, classification, clustering)
  • Experience with libraries such as scikit-learn, TensorFlow, or PyTorch (academic or project-based)
  • Understanding of data structures and algorithms fundamentals
  • Basic knowledge of SQL and data handling

PREFERRED QUALIFICATIONS

  • Internship, academic project, or personal project experience in machine learning
  • Familiarity with Git and version control
  • Exposure to cloud platforms (AWS, Azure, or Google Cloud)
  • Basic understanding of APIs or web services
  • Experience with data visualization tools (e.g., Matplotlib, Seaborn)
  • Strong willingness to learn and grow
  • Problem-solving mindset
  • Good communication and teamwork skills
  • Attention to detail

What Flexjet employees say

Pay

Benefits

Hours and flexibility

Workplace

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