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Machine Learning Engineer Quantization Jobs in Grove City, OH

Machine Learning Tutor

Columbus, OH ยท Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Data Engineer

Columbus, OH ยท On-site

$110K - $132K/yr

Data Engineer - GE08AE We're determined to make a difference and are proud to be an insurance ... The Hartford is developing industry-leading AI and machine learning capabilities to improve ...

This role focuses on engineering production-ready machine learning applications, Large Language Model (LLM) solutions, and cloud-native ML platforms while partnering closely with Data Science teams ...

Work You'll Do As a Senior AI Engineer, you'll work cross-functionally with data scientists, machine learning engineers, project managers, and industry experts to develop robust AI infrastructure and ...

AI Engineer

Columbus, OH ยท On-site

$55K - $187K/yr

Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS ... Google Cloud, Microsoft Azure, Databricks, Snowflake, or related data and AI credentials ...

Senior AI Engineer

Minneapolis, MN

$109K - $149K/yr

Architect and scale machine learning pipelines to support automated workflows across Fund ... Mentor junior engineering staff and advise the Managing Director on technical priorities and secure ...

AI Solutions Engineering Delivery Lead

Columbus, OH ยท On-site

$99K - $130K/yr

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

Build, lead, and develop the team across Machine Learning Engineering, Machine Learning , and AI Engineering. * Recruit, develop, and retain high-performing data scientists, ML engineers, and AI ...

CTIO AI Engineering Manager

Columbus, OH ยท On-site

$73K - $244K/yr

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

Lead Forward Deployed Engineer - AWS

Columbus, OH ยท On-site

$99K - $130K/yr

... Machine Learning Engineer (Associate - MLA-C01) or AWS Certified Data Engineer (Associate) * 1+ years of experience building reliable, maintainable, and well-documented code * Ability to travel 50 ...

... Machine Learning Engineer (Associate - MLA-C01) or AWS Certified Data Engineer (Associate) * 1+ years of experience building reliable, maintainable, and well-documented code * Ability to travel 50 ...

Showing results 21-40

Machine Learning Engineer Quantization information

See Grove City, OH salary details

$29.6K

$120.9K

$181.6K

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

As of Aug 8, 2026, the average yearly pay for machine learning engineer quantization in Grove City, OH is $120,855.00, according to ZipRecruiter salary data. Most workers in this role earn between $95,300.00 and $145,500.00 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 job categories do people searching Machine Learning Engineer Quantization jobs in Grove City, OH look for? The top searched job categories for Machine Learning Engineer Quantization jobs in Grove City, OH are:

Machine Learning Engineer, Robot Learning, Loco-Manipulation

Path Robotics

Columbus, OH โ€ข On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 11 days ago


Job description

Build the Path Forward
At Path Robotics, we're building the future of embodied intelligence. Our AI-driven systems enable robots to adapt, learn, and perform in the real world closing the skilled labor gap and transforming industries. We go beyond traditional methods, combining perception, reasoning, and control to deliver field-ready AI that is risk-aware, reliable, and continuously improving through real-world use.
Big, hard problems are our everyday work, and our team of intelligent, humble, and driven people make the impossible possible together.
We are standing up a new Robot Learning team focused on whole-body loco-manipulation for precision tasks in heavy manufacturing.
We are seeking a Machine Learning Engineer to join us as a founding member. You will be among the first ML engineers on a research stack that does not exist anywhere else in the field built around visual reasoning, learned action policies, and reinforcement-learning fine-tuning from real customer data.
What You'll Do
  • Build the team's robot-learning stack from the ground up. This is a founding role; you are designing the training infrastructure, data pipelines, simulation environments, model architectures, and deployment workflows - not inheriting them. Multi-modal perception, scene understanding, and learned action generation work in tight coordination on the stack you help create.
  • Stand up ML infrastructure - training pipelines, experiment tracking, data versioning, reproducible sim-to-real workflows.
  • Train policies across manipulation, locomotion, and the whole-body control coupling between them. On legged platforms performing precision tasks, manipulation and locomotion are not separable - every arm motion shifts the centre of mass; the whole-body controller compensates in real time to maintain accuracy at the tool. Behavioural cloning, diffusion- and flow-matching action generation, reinforcement-learning fine-tuning. Cobots, industrial arms, and mobile platforms.
  • Deploy in stages - through a phased rollout strategy that builds production trust over time. Every real-world execution accumulates training data for continuous improvement.
  • Collaborate daily with mechanical engineers, perception engineers, robotics engineers, and manufacturing domain experts. Within-department rotation across home teams is expected.

Who You Are
  • Ph.D. or Master's degree in Robotics, Mechanical Engineering, Electrical Engineering, Computer Science, or a related field - or equivalent experience.
  • 2+ years of hands-on robot learning experience. You have trained policies and deployed them on real robot hardware - not just in simulation.
  • Sim-to-real transfer experience - built simulation environments, implemented domain randomisation, transferred policies to physical robots, debugged where it broke.
  • Implementation experience with diffusion-based or flow-matching action policies for robots, and with action chunking.
  • Reinforcement learning for robotics applied on real hardware - sample-efficient on-robot methods, residual RL on top of pretrained policies, on-policy fine-tuning of foundation policies.
  • Strong programming skills in Python; PyTorch and ML training infrastructure at production level.
  • Practical experience with NVIDIA Isaac Sim / Isaac Lab, MuJoCo, or equivalent.
  • Comfort with physical robots - debugging, iterating, deploying.
  • Strong communication skills, able to convey complex technical concepts to a diverse audience.

Strongly Preferred:
  • Edge inference on edge-class hardware (TensorRT, ONNX, FP16 / INT8 quantisation). Real-time on-robot deployment is a core requirement.
  • Visual self-supervised representation learning experience on robot or 3D-vision tasks.
  • Legged-robot or whole-body control experience - locomotion, manipulation on a floating base, or the integration between them on quadrupeds or humanoids.
  • Physics-informed ML - hybrid models where learned components are constrained by known physics.
  • Experience building ML pipelines or infrastructure in a team setting.

Why You'll Love Working Here
  • Daily free lunch to keep you fueled and connected with the team
  • Flexible PTO so you can take the time you need, when you need it
  • Comprehensive medical, dental, and vision coverage
  • 6 weeks fully paid parental leave, plus an additional 6-8 weeks for birthing parents (12-14 weeks total)
  • 401(k) retirement plan through Empower
  • Generous employee referral bonuses-help us grow our team!

Who We Are
At Path Robotics we love coming to work to solve interesting and tough challenges but also because our ideas are welcomed and valued. We encourage unique thinking and are dedicated to creating a diverse and inclusive environment. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.
If you require a reasonable accommodation to participate in the application process or any part of the hiring process, please contact HR@path-robotics.com. We are committed to providing equal access and will work with qualified individuals to ensure a fair and accessible hiring experience. We will respond to your request within 48 hours.