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Machine Learning Engineer Quantization Jobs in Ohio

The Hartford

Sr AI Machine Learning Engineer

Columbus, OH · Hybrid

$117K - $175K/yr

The Hartford is seeking Senior AI Machine Learning Engineer to build Machine Learning Operations (MLOps) services for the Global Specialty Applied AI team. The Hartford is developing industryleading ...

Varsity Tutors

Machine Learning Tutor

Cleveland, OH · 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 ...

Varsity Tutors

Machine Learning Tutor

Cincinnati, OH · 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 ...

Varsity Tutors

Machine Learning Tutor

Akron, OH · 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 ...

Varsity Tutors

Machine Learning Tutor

Columbus, OH · 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 ...

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Machine Learning Engineer Quantization information

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 Ohio? For Machine Learning Engineer Quantization jobs in Ohio, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Quantization jobs in Ohio look for? The top searched job categories for Machine Learning Engineer Quantization jobs in Ohio 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 Quantization jobs near you
Sr AI Machine Learning Engineer

Sr AI Machine Learning Engineer

The Hartford

Columbus, OH • Hybrid

$117K - $175K/yr

Full-time

Re-posted 23 days ago

The Hartford rating

8.8

Company rating: 8.8 out of 10

Based on 109 frontline employees who took The Breakroom Quiz

51st of 278 rated insurance

Job description

Sr Data Engineer - GE07BE

We're determined to make a difference and are proud to be an insurance company that goes well beyond coverages and policies. Working here means having every opportunity to achieve your goals - and to help others accomplish theirs, too. Join our team as we help shape the future.

The Hartford is seeking Senior AI Machine Learning Engineer to build Machine Learning Operations (MLOps) services for the Global Specialty Applied AI team.


The Hartford is developing industryleading AI and machine learning capabilities to improve the various facets of the Global Specialty underwriting experience. On the Global Specialty Applied AI team, we utilize the latest AI products and frameworks to accelerate the processes that our partners touch day to day and advance the speed and intelligence with which we make our decisions. As a Senior Machine Learning AI Engineer, you will play a critical role in designing, building, and operationalizing productiongrade AI solutions-partnering closely with product, engineering, and platform leaders to deliver measurable impact.

Our core values

  • We build AI solutions, not models. We are thoughtful in supporting the end-to-end business problem, with an eye to systems design.
  • We are trusted and transparent. We collaborate tightly with our partners and are mindful of their capacity to absorb change.
  • We provide assets that are safe to buy. Our products are delivered with a full monitoring solution to ensure our products continue to deliver as expected.
  • We will earn the right to influence. With humble confidence, we listen carefully to learn from our customers and become partners in problem solving.
  • We are practical and evolutional. We first deliver a minimally viable product and over time expand its sophistication based on feedback.

Responsibilities

  • Research, experiment with, and implement suitable Generative and ML algorithms, tools and technologies.
  • Participate in identifying and assessing opportunities i.e. value of new data sources and analytical techniques and technology, to ensure ongoing competitive advantage.
  • Review work with leadership and partners on an ongoing basis to calibrate deliverables against expectations.
  • Accountable for deployment design, development and maintenance of both traditional ML and AI models.
  • Work with junior engineers and peers to provide mentorship and thought leadership. Be comfortable presenting new concepts to technical audiences.
  • Collaborate with partners Enterprise Data, Applied AI, Business, Cloud Enablement Team, and Enterprise Architecture teams
  • Delivery of critical milestones for model deployment in the AWS and GCP clouds.
  • Adopt and promote MLOps best practices to the Data Science community.

Minimum Requirements

  • Must be authorized to work in the U.S. now and in the future.
  • Master's degree in related field or 5+ years of equivalent experience in a research or DevOps function.
  • Development experience developing solutions within AWS, GCP or both.
  • Experience developing repeatable architectural patterns; ability to identify redundancies and eliminate them with these patterns.
  • Experience building and deploying API services within the Cloud.
  • Experience building CICD pipeline using Jenkins or equivalent
  • Experience with IAC (Infrastructure as Code) including Cloud Formation, Terraform, or equivalents
  • Experience in Unix, git, and strong object oriented development experience using Python
  • Experience in end to end model development lifecycle, from ideation through post production monitoring.
  • Experience with workflow automation platforms (Apache Airflow, Autosys, similar)
  • Basic understanding of Data Science model development life cycle
  • Familiarity with emerging data centric technologies such generative AI, Agentic workflows, and embedding LLM's into automated processes

This role will have a Hybrid work schedule, with the expectation of working in an office (Columbus, OH, Chicago, IL, Hartford, CT or Charlotte, NC) 3 days a week (Tuesday through Thursday).

Candidates must be authorized to work in the US without company sponsorship. The company will not support the STEM OPT I-983 Training Plan endorsement for this position.

Compensation

The listed annualized base pay range is primarily based on analysis of similar positions in the external market. Actual base pay could vary and may be above or below the listed range based on factors including but not limited to performance, proficiency and demonstration of competencies required for the role. The base pay is just one component of The Hartford's total compensation package for employees. Other rewards may include short-term or annual bonuses, long-term incentives, and on-the-spot recognition. The annualized base pay range for this role is:

$117,200 - $175,800

Equal Opportunity Employer/Sex/Race/Color/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age

About Us|Our Culture|What It's Like to Work Here|Perks & Benefits

What The Hartford employees say

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Benefits

Hours and flexibility

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About Hartford

Sourced by ZipRecruiter

Hartford Financial Services Group, widely recognized as The Hartford, is a renowned company based in Hartford, CT, US. Established in 1810, it has evolved into an industry leader in the insurance and financial services sector, proudly serving more than one million businesses in the US. The Hartford is committed to offering a gamut of insurance products that include homeowners, automobile, and business insurance as well as employee benefits and mutual funds. The company’s core values revolve around customer-focused innovations, diversity and inclusion, and ethical dealings that have earned them a customer-centric reputation. This shapes their mission which revolves around aiding their clients to overcome unforeseen obstacles and enhancing their wealth over time. Among the company's noted accomplishments is being consistently listed among the World's Most Ethical Companies, a testament to their unwavering commitment towards responsible business practices.

Industry

Finance and insurance

Company size

10,000+ Employees

Headquarters location

Hartford, CT, US

Year founded

1810

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