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Mlops Machine Learning Engineer Jobs in Downers Grove, IL

Senior Machine Learning Engineer

Schaumburg, IL ยท On-site

$120K - $159K/yr

Senior Engineer Machine Learning Position Overview Paylocity is growing its Machine Learning Engineering organization! Our machine learning engineering team is responsible for developing ...

Lead Machine Learning Engineer

Chicago, IL ยท On-site

$105K - $139K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

Lead Machine Learning Engineer

Chicago, IL ยท On-site +1

$105K - $139K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

Lead Machine Learning Engineer

Chicago, IL ยท On-site +1

$105K - $139K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

Lead Machine Learning Engineer

Chicago, IL ยท On-site

$105K - $139K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

Machine Learning Engineer

Chicago, IL ยท 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 ...

Machine Learning Engineer

Chicago, IL ยท On-site

$80 - $100/hr

About the Role 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 ...

* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...

* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...

Showing results 21-40

Mlops Machine Learning Engineer information

See Downers Grove, IL salary details

$31.4K

$128.5K

$193.1K

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

As of Sep 7, 2026, the average yearly pay for mlops machine learning engineer in Downers Grove, IL is $128,470.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,300.00 and $154,600.00 per year, depending on experience, location, and employer.

What does an MLOps machine learning engineer do?

An MLOps Machine Learning Engineer bridges the gap between data science and IT operations by developing, deploying, and maintaining machine learning models in production environments. They are responsible for automating workflows, managing model versioning, monitoring performance, and ensuring scalability and reliability of ML systems. Their work enables organizations to deploy machine learning solutions efficiently and consistently, making it easier to update and manage models as business needs evolve.

What are the key skills and qualifications needed to thrive as an MLOps machine learning engineer?

To thrive as an MLOps Machine Learning Engineer, you need a strong background in machine learning concepts, software engineering, and cloud infrastructure, typically supported by a degree in computer science or a related field. Familiarity with tools like Docker, Kubernetes, CI/CD pipelines, cloud platforms (AWS, GCP, Azure), and certifications such as Google Professional Machine Learning Engineer are highly beneficial. Strong problem-solving abilities, collaboration, and communication skills help you work effectively across data science and engineering teams. These skills are essential for reliably deploying, monitoring, and maintaining scalable machine learning solutions in production environments.

How does an MLOps machine learning engineer typically collaborate with data scientists and software engineers during the deployment of machine learning models?

An MLOps Machine Learning Engineer acts as a bridge between data scientists and software engineers, ensuring machine learning models transition smoothly from development to production. They often work closely with data scientists to understand model requirements, data pipelines, and performance metrics, while also collaborating with software engineers to integrate models into scalable systems. Regular communication, shared documentation, and joint troubleshooting sessions are common, as the role requires aligning model performance with system reliability and maintainability. This collaborative environment helps ensure that models are robust, scalable, and impactful in real-world applications.

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

AspectMlops Machine Learning EngineerData Scientist
Required CredentialsBachelor's or master's in CS, data science, or related fields; certifications in cloud platforms or MLOps toolsBachelor's or master's in statistics, data science, or related fields; certifications in data analysis or machine learning
Work EnvironmentFocus on deploying, maintaining, and scaling ML models in production environmentsFocus on data analysis, model development, and insights generation
Employer & Industry UsageTech companies, startups, enterprises implementing ML solutionsResearch institutions, analytics firms, tech companies for data insights

While both roles involve machine learning, Mlops Machine Learning Engineers specialize in deploying and maintaining models in production, ensuring scalability and reliability. Data Scientists primarily focus on developing models and analyzing data to generate insights. The roles often overlap but differ in their core responsibilities and work environments.

Are MLOps machine learning engineers in demand?

MLOps machine learning engineers are in high demand due to the increasing adoption of AI and machine learning across industries. They are needed to develop, deploy, and maintain scalable ML systems, often requiring skills in cloud platforms, automation, and tools like Docker and Kubernetes. The role offers strong job growth prospects and competitive salaries.

Do MLOps Machine Learning Engineers need a degree?

MLOps Machine Learning Engineers typically do not require a formal degree but often have a background in computer science, data science, or related fields. Practical skills in machine learning, cloud platforms, and tools like Docker, Kubernetes, and CI/CD pipelines are highly valued. Certifications and hands-on experience can also enhance job prospects.

What are popular job titles related to Mlops Machine Learning Engineer jobs in Downers Grove, IL?

For Mlops Machine Learning Engineer jobs in Downers Grove, IL, the most frequently searched job titles are:

What job categories do people searching Mlops Machine Learning Engineer jobs in Downers Grove, IL look for?

The top searched job categories for Mlops Machine Learning Engineer jobs in Downers Grove, IL are:

What cities near Downers Grove, IL are hiring for Mlops Machine Learning Engineer jobs?

Cities near Downers Grove, IL with the most Mlops Machine Learning Engineer job openings:

Machine Learning Engineer

Moody's Investors Service

Chicago, IL โ€ข On-site

$100 - $125/hr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 8 days ago


Job description

At Moody's, we unite the brightest minds to turn todayโ€™s risks into tomorrowโ€™s opportunities. We do this by striving to create an inclusive environment where everyone feels welcome to be who they areโ€”with the freedom to exchange ideas, think innovatively, and listen to each other and customers in meaningful ways. Moodyโ€™s is transforming how the world sees risk. As a global leader in ratings and integrated risk assessment, weโ€™re advancing AI to move from insight to actionโ€”enabling intelligence that not only understands complexity but responds to it. We decode risk to unlock opportunity, helping our clients navigate uncertainty with clarity, speed, and confidence.


Employment eligibility to work in the U.S. is required, as Moodyโ€™s will not pursue visa sponsorship for this position

Skills and Competencies
  • Expertise in Python programming, including machine learning libraries such as NumPy, Pandas, and PyTorch
  • Experience with machine learning operations practices, including continuous integration and continuous deployment pipelines, model monitoring, and model maintenance preferred
  • Expertise with modern machine learning tools and platforms, including Jupyter, Docker, Git, and cloud computing environments such as Amazon Web Services or Google Cloud Platform
  • Experience building data tools for extract, transform, and load processes, extracting data from SQL and NoSQL databases, and conducting advanced data analysis
  • Experience with geographic information systems preferred
  • Excellent written and verbal communication skills, with the ability to understand and articulate business requirements and objectives to both technical and non-technical stakeholders
  • Expertise in supervised and unsupervised machine learning algorithms and their implementations, including advanced concepts such as active learning, computer vision, and deployments in complex environments
  • Deep expertise in artificial intelligence, with a track record of implementing advanced AI solutions to drive strategic transformation and operational efficiency. Strong experience using AI tools to lead innovation initiatives. Demonstrated leadership in managing AI-related risks, ensuring ethical governance, and fostering a culture of responsible AI adoption across the organization
Education
  • Advanced degree in a Science, Technology, Engineering, or Mathematics field required
  • Typically requires a minimum of two years of handsโ€‘on industry experience in machine learning, computer vision, data science, or a related field
Responsibilities

Develop practical, scalable, and robust machine learning and computer vision solutions that enhance product capabilities and deliver value to clients.

  • Collect, clean, preprocess, and analyze data to support machine learning model development and maximize data value
  • Create visualizations and conduct exploratory analysis to identify patterns, trends, opportunities, and data quality issues
  • Train, evaluate, refine, and deploy machine learning models aligned with business objectives and product requirements
  • Design, implement, and automate large-scale model training, integration, and evaluation pipelines
  • Collaborate with machine learning, software engineering, product development, sales, and cross-functional stakeholders to deliver innovative solutions
  • Communicate technical findings and recommendations to both technical and non-technical audiences through clear documentation and presentations
  • Design and execute experiments to validate assumptions, improve model performance and support data-driven decision making
  • Ensure projects follow governance, security, ethical AI, and responsible data use practices while identifying and resolving operational inefficiencies
About the Team

Our Machine Learning Technology team is responsible for the core technology behind award-winning property intelligence solutions. We leverage machine learning, geospatial imagery, and computer vision to measure and monitor the built environment while delivering actionable insights to clients. By joining our team, you will contribute to innovative work that helps organizations better understand how homes and workplaces can withstand evolving climate and economic risks, while advancing the responsible adoption of artificial intelligence across our products and solutions.


For US-based roles only: the anticipated hiring base salary range for this position is$95,500.00-$138,550.00, depending on factors such as experience, education, level, skills, and location. This range is based on a full-time position. In addition to base salary, this role is eligible for incentive compensation. Moodyโ€™s also offers a competitive benefits package, including not but limited to medical, dental, vision, parental leave, paid time off, a 401(k) plan with employee and company contribution opportunities, life, disability, and accident insurance, a discounted employee stock purchase plan, and tuition reimbursement.

Moodyโ€™s is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, sex, gender, age, religion or creed, national origin, ancestry, citizenship, marital or familial status,sexual orientation, gender identity, gender expression, genetic information, physical or mental disability, military or veteran status, or any other characteristic protected by law. Moodyโ€™s also provides reasonable accommodation to qualified individuals with disabilities or based on a sincerely held religious belief in accordance with applicable laws. If you need to inquire about a reasonable accommodation, please email accommodations@moodys.com. This contact information is for accommodation requests only, and cannot be used to inquire about the status of applications

For San Francisco positions, qualified applicants with criminal histories will be considered for employment consistent with the requirements of the San Francisco Fair Chance Ordinance.

This position may be considered a promotional opportunity, pursuant to the Colorado Equal Pay for Equal Work Act.

Candidates for Moody's Corporation may be asked to disclose securities holdings pursuant to Moodyโ€™s Policy for Securities Trading and the requirements of the position. Employment is contingent upon compliance with the Policy, including remediation of positions in those holdings as necessary.

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