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Machine Learning Engineer Mlops Engineer Jobs (NOW HIRING)

Socket.dev

Machine Learning Engineer

Chicago, IL · On-site

About the role Attain is seeking a Senior/Staff Machine Learning Engineer to own our production ML systems and build out the MLOps platform infrastructure that powers our suite of B2C financial ...

Corning

As a Machine Learning Engineer, you will work within a collaborative technical team to build ... systems, and apply MLOps practices for versioning, orchestration, monitoring, and CI/CD ...

ExaCare AI

Senior Machine Learning Engineer

Manhattan, NY · On-site

$115K - $158K/yr

We are looking for a Senior Machine Learning Engineer, MLOps to help operationalize and scale our machine learning systems. This is an engineering-focused role centered on building the workflows ...

KOHLS

Senior MLOps Engineer (Remote)

Menomonee Falls, WI · On-site

$104K - $144K/yr

Contribute to the roadmap for Machine Learning Engineering and Data Science tools, including ... Experience in MLOps or DevOps practices, including building and operating production ML systems ...

Siri InfoSolutions Inc

MLOPS Engineer

Malvern, PA · On-site

$50 - $60/hr

Role: MLOps Engineer Location: Malvern, PA / Raleigh, NC or USA Any LOcation (Onsite) Duration ... Knowledge in the life cycle management of Machine Learning models. * Proficiency with Machine ...

Speria

Machine Learning Operations Engineer

Atlanta, GA · On-site

$66K - $90K/yr

The MLOps Engineer works closely with Machine Learning Engineers and Data Engineers to ensure that models and decisioning systems are production-ready, observable, cost-efficient, and seamlessly ...

Attain

Senior Machine Learning Engineer

Chicago, IL · On-site

$107K - $147K/yr

About the role Attain is seeking a Senior Machine Learning Engineer to own our production ML systems and build out the MLOps platform infrastructure that powers our suite of B2C financial services.

Attain

Senior Machine Learning Engineer

Chicago, IL · On-site +1

$107K - $147K/yr

About the role Attain is seeking a Senior Machine Learning Engineer to own our production ML systems and build out the MLOps platform infrastructure that powers our suite of B2C financial services.

Kurai

MLOps Engineer MLOps Engineer

Austin, TX · On-site

Join our ML Infrastructure team as an MLOps Engineer where you'll build the pipelines and platforms that deploy, monitor, and scale ML models from research to production. You'll bridge the gap ...

Steampunk

MLOps Engineer

Mclean, VA

$115K - $150K/yr

We are seeking a MLOps Engineer to design, build, and support the infrastructure, tooling, and automation that enable scalable and reliable machine learning systems across our client engagements.

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All JobsTechnology JobsData JobsData Scientist JobsMachine Learning Engineer Mlops Engineer Jobs

Machine Learning Engineer Mlops Engineer information

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$31.5K

$128.8K

$193.5K

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

As of Sep 11, 2026, the average yearly pay for machine learning engineer mlops engineer in the United States is $128,769.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,500.00 and $155,000.00 per year, depending on experience, location, and employer.

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

AspectMachine Learning Engineer Mlops EngineerData Scientist
Primary FocusDeveloping, deploying, and maintaining ML models and MLOps pipelinesAnalyzing data, building models, and deriving insights
Skills & CertificationsMachine learning, software engineering, cloud platforms, MLOps toolsStatistics, data analysis, programming (Python/R), visualization
Work EnvironmentSoftware development teams, cloud infrastructure, production environmentsResearch teams, data analysis projects, exploratory data analysis
Industry UsageTech companies, startups, enterprises deploying ML solutionsResearch institutions, analytics firms, data-driven organizations

While both roles involve working with machine learning, Machine Learning Engineers and MLOps Engineers focus on deploying and maintaining scalable ML systems, whereas Data Scientists primarily analyze data and develop models for insights. MLOps Engineers often work closely with Machine Learning Engineers to ensure models are production-ready and reliable.

What cities are hiring for Machine Learning Engineer Mlops Engineer jobs?

Cities with the most Machine Learning Engineer Mlops Engineer job openings:

What states have the most Machine Learning Engineer Mlops Engineer jobs?

States with the most job openings for Machine Learning Engineer Mlops Engineer jobs include:

What are popular job titles related to Machine Learning Engineer Mlops Engineer jobs?

For Machine Learning Engineer Mlops Engineer jobs, the most frequently searched job titles are:

Infographic showing various Machine Learning Engineer Mlops Engineer job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 74% Full Time, 22% Part Time, and 2% Contract. Highlights an 83% Physical, 2% Hybrid, and 15% Remote job distribution, with an average salary of $128,769 per year, or $61.9 per hour.

Machine Learning Engineer

Oakbrook Terrace, IL • On-site

Darwill, Inc.
Marketing • 201 - 500 employees
Learn more about Darwill, Inc.external

Full-time

Posted 16 days ago

Job description

Overview
Darwill is a nationally recognized print and marketing communications firm based in the west suburbs of Chicago. As a premier provider of complex, data-driven marketing solutions, we help CMOs and marketing leaders drive measurable performance through advanced analytics, automation, and AI-powered insights.
We are seeking a Machine Learning Engineer (MLOps) to support the productionization of traditional machine learning models (e.g., propensity and segmentation models) while also building and maintaining the core data pipelines on Databricks that power our analytics and modeling platforms.
This role is intentionally scoped for a mid-level engineer: someone with enough experience to work independently and make sound engineering decisions, but who is still hands-on, execution-focused, and eager to grow. This is not an entry-level position, and it is not a principal or architect-level role.
Location
Chicago, IL area (Oak Brook / West Suburbs)
Hybrid work model with 1-2 days onsite per week required
Reports To
VP of Data Engineering & Data Science
Responsibilities / Essential Functions
Data Engineering & Platform Foundations
  • Design, build, and maintain ETL pipelines in Databricks using Spark and Delta Lake
  • Independently implement data transformations, joins, and aggregations across large, multi-source datasets
  • Build and maintain data validation and quality checks to ensure reliability of downstream analytics and ML workflows
  • Optimize Databricks jobs for performance, scalability, and cost efficiency
  • Write and maintain clear technical documentation for data pipelines and tables

ML Engineering & MLOps
  • Partner closely with Data Scientists to support traditional ML model development, including feature engineering, training, validation, and deployment
  • Productionize propensity, ranking, and segmentation models used in large-scale marketing campaigns
  • Build and maintain repeatable ML pipelines for training, batch scoring, and inference
  • Implement model versioning, experiment tracking, and reproducibility standards
  • Support model performance monitoring, drift detection, and retraining cycles

Deployment, Monitoring & Operations
  • Deploy data pipelines and ML workflows into production environments serving millions of records
  • Implement monitoring and alerting for data and ML pipelines
  • Support A/B testing and model performance evaluation in partnership with Data Science
  • Troubleshoot production issues independently and collaborate effectively when escalation is needed

GenAI (Secondary / Directional)
  • Contribute to GenAI initiatives as capacity allows
  • Stay informed on emerging AI technologies and tooling
  • (GenAI is not the primary focus of this role today.)

Required Qualifications
Experience
  • 3-6 years of professional experience in machine learning engineering, data engineering, or a closely related role
  • Experience working in production environments with minimal day-to-day supervision
  • Demonstrated ability to collaborate effectively with Data Scientists and translate models into production systems

Technical Skills (Must-Have)
Data Engineering & Platform
  • Apache Spark (PySpark, SparkSQL)
  • Databricks (ETL pipelines, workflows, Delta Lake)
  • Strong SQL skills (complex queries, joins, window functions, optimization)
  • Experience building and maintaining scalable data pipelines

Programming & Machine Learning
  • Python (pandas, numpy, scikit-learn; experience with XGBoost or LightGBM preferred)
  • Feature engineering and data preparation for ML models
  • Working knowledge of supervised learning models (classification, regression, ranking)

MLOps & Production
  • Experience deploying ML models into production
  • Model versioning and experiment tracking (e.g., MLflow or similar)
  • Monitoring data quality and model performance in production
  • Supporting retraining and validation workflows

Cloud & Tooling
  • Experience with a major cloud platform (Databrick, AWS)
  • Familiarity with workflow orchestration tools (Databricks Workflows or similar)

Preferred Qualifications (Nice-to-Have)
  • Experience with propensity modeling, customer segmentation, or marketing analytics
  • Exposure to CI/CD concepts for data and ML pipelines
  • Experience with Docker or containerized deployments
  • Exposure to GenAI, LLMs, or RAG-based systems
  • Master's degree in Computer Science, Statistics, or a related field
  • Seniority Level
    Associate
  • Industry
    • Marketing Services
  • Employment Type
    Full-time
  • Job Functions

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