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Machine Learning Engineer Hybrid Jobs in Ohio (NOW HIRING)

Aivra Health LLC

$28 - $45/hr

Machine Learning Engineer Intern United States Internship | Full-Time (40 hours/week) Pay Range: $28 - $45 per hour Visa: H1B Sponsorship Available | STEM OPT, OPT & CPT Candidates Welcome Position ...

Mimecast

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 ... Our Hybrid Model: We provide you with the flexibility to live balanced, healthy lives through our ...

The Hartford

AI Machine Learning Engineer

Columbus, OH · Hybrid

$100K - $151K/yr

The Hartford is seeking AI Machine Learning Engineer to build Machine Learning Operations (MLOps ... Hybrid work schedule, with the expectation of working in an office (Columbus, OH, Chicago, IL ...

Mimecast

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 ... Our Hybrid Model: We provide you with the flexibility to live balanced, healthy lives through our ...

Bespoke Labs

Machine Learning Engineer

Toledo, OH · On-site

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 ...

Bespoke Labs

Machine Learning Engineer

Columbus, OH · On-site

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 ...

Bespoke Labs

Machine Learning Engineer

Cleveland, OH · On-site

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 ...

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 ... Hybrid work schedule, with the expectation of working in an office (Columbus, OH, Chicago, IL ...

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Machine Learning Engineer Hybrid information

What is the difference between Machine Learning Engineer Hybrid vs Data Scientist?

AspectMachine Learning Engineer HybridData Scientist
Required CredentialsBachelor's/Master's in CS, AI, or related; experience with ML frameworksBachelor's/Master's in CS, Statistics, or related; strong analytical skills
Work EnvironmentDevelops, tests, deploys ML models; collaborates with engineering teamsAnalyzes data, builds models, interprets results; works across departments
Industry UsageTech, finance, healthcare, e-commerceResearch, finance, marketing, tech

Machine Learning Engineer Hybrid focuses on developing and deploying ML models within engineering environments, often requiring coding and deployment skills. Data Scientists analyze data, build models, and interpret results, often in research or strategic roles. While both roles require strong analytical skills and knowledge of ML, the Engineer Hybrid emphasizes deployment and integration, whereas Data Scientists focus on data analysis and insights.

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Machine Learning Engineer Hybrid jobs near you
Machine Learning Engineer

Machine Learning Engineer

Apex Informatics

Cincinnati, OH • On-site

Full-time

Posted 11 days ago

Job description

Below is my newest requirement. Please send Full Legal Name, LinkedIn, Location, Contact Details, C2C rate, and work authorization status with each submittal.
Client: Kroger
Location: Hybrid onsite in Cincinnati OH (local only)
Interview Mode: Virtual Interview
Type: Contract
Work authorization: Cannot work with OPT or CPT
Rate: Open (market rate)
We are seeking a dynamic Senior Machine Learning Engineer to lead the integration and operationalization of machine learning models. This role requires collaboration with data scientists and leadership teams, and a strong foundation in MLOps methodologies. Experience in diverse ML platforms, including Google Vertex AI and other cloud and open-source technologies, is essential. The candidate will bridge MLOps, data science, and leadership to ensure the smooth functioning of our ML infrastructure.
Qualifications:
Minimum of 4 years of experience in MLOps, with a demonstrated ability to work with various ML platforms.
Strong proficiency in Python and familiarity with data science methodologies.
Experience with cloud technologies, particularly Google Cloud and Vertex AI, and adaptability to technologies like Microsoft Azure or open-source tools.
Excellent communication skills, capable of bridging technical and business domains
Experience in developing state-of-the-art techniques for multi-stage, personalized, context-aware, and sequential recommender systems.
Hands-on experience working on recommender systems, drawing from ML techniques such as embedding based retrieval, reinforcement learning, transformers, and LLMs.
Capable software engineering skills to lead a multi stage recommender system model lifecycle from inception to production.

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