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Machine Learning Operations Jobs in Elmhurst, IL

Iterable

Senior Machine Learning Engineer (Nova)

Chicago, IL · On-site

$107K - $147K/yr

They are seeking a Senior Machine Learning Engineer to build core Machine Learning foundations ... operations. • Collaborate with product, design, and engineering to align ML system design with ...

IMC

Machine Learning Research Lead

Chicago, IL · On-site

$250K - $300K/yr

IMC Trading is seeking a Machine Learning Research Lead with proven experience applying ... business operations professionals are united by our uniquely collaborative, high-performance ...

IMC

Hardware Machine Learning Engineer

Chicago, IL · On-site

$200K - $225K/yr

We are deploying machine learning directly onto custom hardware - and we want you to help drive it ... business operations professionals are united by our uniquely collaborative, high-performance ...

IMC

Hardware Machine Learning Engineer

Chicago, IL · On-site

$200K - $225K/yr

We are deploying machine learning directly onto custom hardware - and we want you to help drive it ... business operations professionals are united by our uniquely collaborative, high-performance ...

Career Renew

Senior Machine Learning Engineer

Chicago, IL · Remote

$165K - $225K/yr

... operational efficiency, and expanding diagnostic possibilities. About the Role We are seeking an ... The ideal candidate will have deep expertise in Machine Learning and building generalizable ...

MessageControl

Data Scientist

Chicago, IL

Prior research, data science modeling and taking machine learning features to market. * Outstanding quantitative background (e.g. statistics, math, machine learning, operations research, etc.

MessageControl

Data Scientist

Chicago, IL · On-site

Prior research, data science modeling and taking machine learning features to market. * Outstanding quantitative background (e.g. statistics, math, machine learning, operations research, etc.

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Machine Learning Operations information

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How much do machine learning operations jobs pay per hour?

As of Jul 8, 2026, the average hourly pay for machine learning operations in Elmhurst, IL is $39.73, according to ZipRecruiter salary data. Most workers in this role earn between $33.27 and $42.12 per hour, depending on experience, location, and employer.

Is ML a high paying job?

Machine Learning Operations (MLOps) roles are generally well-paid due to the specialized skills required, such as expertise in cloud platforms, programming, and data management. Salaries tend to be higher than average tech roles and can increase with experience, certifications, and knowledge of tools like TensorFlow or Kubernetes.

What is the difference between Machine Learning Operations vs Data Scientist?

AspectMachine Learning OperationsData Scientist
Primary FocusDeploying, maintaining, and scaling ML models in productionAnalyzing data to develop insights and build models
Required SkillsML deployment, cloud platforms, automation, scriptingStatistical analysis, data visualization, programming (Python/R)
Work EnvironmentOperations teams, cloud infrastructure, production systemsResearch environments, data analysis teams, R&D
Common CertificationsCloud certifications, MLOps tools certificationsData science certifications, statistical courses

Machine Learning Operations and Data Scientists often collaborate, but MLOps focuses on deploying and maintaining models in production, while Data Scientists focus on analyzing data and developing models. Both roles require technical skills, but their day-to-day tasks and environments differ.

What engineer makes $500,000 a year?

Senior machine learning operations engineers with extensive experience, advanced skills in automation, cloud platforms, and deployment pipelines can earn salaries approaching or exceeding $500,000 annually, especially in high-cost-of-living areas or large tech companies. Such roles often require expertise in tools like Kubernetes, Docker, and cloud services, along with strong problem-solving and leadership abilities.

What is a $900000 AI job?

A $900,000 AI job typically refers to high-level roles in artificial intelligence, such as senior machine learning engineers, AI research directors, or chief AI officers, often requiring advanced skills in machine learning, deep learning, and data science. These positions usually involve leadership responsibilities, extensive experience, and may include stock options or bonuses that contribute to the total compensation. Such roles are rare and highly competitive, often found in large tech companies or innovative startups.

Will MLE be replaced by AI?

Machine Learning Engineers (MLEs) design, develop, and maintain AI systems, and while AI automation tools can handle certain tasks, MLEs are essential for creating, tuning, and overseeing complex models. AI may automate some routine aspects, but MLEs' expertise in data engineering, model optimization, and deployment remains critical for effective AI solutions.
Machine Learning Operations jobs near you
Senior Machine Learning Engineer (Nova)

Senior Machine Learning Engineer (Nova)

Iterable

Chicago, IL • On-site

$107K - $147K/yr

Full-time

Re-posted 29 days ago

Job description

Job Summary:
Iterable is the leading AI-powered customer engagement platform that helps brands create dynamic, individualized experiences at scale. They are seeking a Senior Machine Learning Engineer to build core Machine Learning foundations, focusing on applied Machine Learning in production environments, and collaborating with various teams to enhance the Iterable platform.
Responsibilities:
• Design and build Machine Learning platform components that support agentic systems, including retrieval pipelines, indexing strategies, and model integration layers.
• Introduce and operationalize RAG use cases, from data sourcing and embedding generation to runtime retrieval patterns.
• Develop generalized evaluation frameworks for LLM- and agent-based features, including offline metrics, golden datasets, and continuous monitoring.
• Implement abstractions, tooling, and reusable patterns that enable other teams to build ML- and LLM-powered experiences efficiently.
• Partner with backend engineers to productionize ML features with strong reliability, observability, and performance characteristics.
• Prototype applied ML solutions to validate feasibility before investing in full builds.
• Ensure secure, robust handling of data used in ML workflows and retrieval operations.
• Collaborate with product, design, and engineering to align ML system design with user experience and product goals.
• Contribute to iterative improvements of the Nova agent framework, including workflows built with Mastra and TypeScript.
Qualifications:
Required:
• 5+ years experience as a Machine Learning Engineer or similar role focused on production systems.
• Strong engineering skills with Python or TypeScript, including experience building ML workflows in frameworks like Mastra or comparable agent/LLM toolkits.
• Experience with retrieval systems, vector databases, search technologies, or RAG architectures.
• Prior work integrating ML or LLM-powered features into production applications.
• Understanding of ML evaluation techniques, experimentation design, and failure analysis.
• Ability to lead complex projects, make practical trade-offs, and work independently in areas of ambiguity.
• Strong communication and collaboration skills in a distributed environment.
Preferred:
• Experience building ML or LLM platforms, tooling, or developer-facing frameworks.
• Prior work with embeddings, search–ranking systems, or advanced RAG architectures.
• Familiarity with event-driven systems or streaming architectures.
• Experience with model observability, performance monitoring, or proactive regression detection.
• Background in personalization, recommendations, or applied NLP.
• Experience working in remote-first engineering teams.
Company:
Iterable is an AI-powered communication platform that improves customer retention with its marketing. Founded in 2013, the company is headquartered in San Francisco, USA, with a team of 501-1000 employees. The company is currently Late Stage.

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