ZipRecruiter

Log In

2

Entry Level Full Stack Machine Learning Engineer Jobs

NTENT

Machine Learning Engineer

Carlsbad, CA · On-site

Machine Learning Engineer Position: Full time Location: Carlsbad office About Us: NTENT provides a ... We offer a full comprehensive benefits package including medical, dental and vision. Employees ...

NTENT

Machine Learning Engineer

Carlsbad, CA

Machine Learning Engineer Position: Full time Location: Carlsbad office About Us: NTENT provides a ... We offer a full comprehensive benefits package including medical, dental and vision. Employees ...

Tech Tammina LLC

Jr. Full-Stack Developer

Warren, MI · On-site

Warren, MI Duration: Long term About the role: · We're looking for an entry-level Full-Stack Developer to join our team and contribute across the stack--from fine-tuning user experiences to enabling ...

Aivra Health LLC

$28 - $45/hr

Machine Learning Engineer Intern United States Internship | Full-Time (40 hours/week) Pay Range ... This role is ideal for students or entry level candidates in STEM fields who are passionate about ...

Aivra Health LLC

$28 - $45/hr

Machine Learning Engineer Intern United States Internship | Full-Time (40 hours/week) Pay Range ... This role is ideal for students or entry level candidates in STEM fields who are passionate about ...

Forhyre

Machine Learning Engineer

New York, NY

We are looking for a Machine Learning Engineer to help us create artificial intelligence products. Machine Learning Engineer responsibilities include creating machine learning models and retraining ...

NT Concepts

Machine Learning Engineer

Chantilly, VA · On-site

... stacks, and constantly challenge each other to grow and improve. If cutting edge data science ... As a Machine Learning Engineer, you'll be part of the Agile team delivering machine learning ...

NT Concepts

Machine Learning Engineer

Chantilly, VA · On-site +1

... stacks, and constantly challenge each other to grow and improve. If cutting edge data science ... As a Machine Learning Engineer, you'll be part of the Agile team delivering machine learning ...

next page

Showing results 1-20

People also search for

All JobsFull Stack Machine Learning Engineer JobsEntry Level Full Stack Machine Learning Engineer Jobs

Entry Level Full Stack Machine Learning Engineer information

See salary details

$44.5K

$134.8K

$190.5K

How much do entry level full stack machine learning engineer jobs pay per year?

As of May 31, 2026, the average yearly pay for entry level full stack machine learning engineer in the United States is $134,771.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,000.00 and $158,000.00 per year, depending on experience, location, and employer.

What is the difference between Entry Level Full Stack Machine Learning Engineer vs Entry Level Data Scientist?

AspectEntry Level Full Stack Machine Learning EngineerEntry Level Data Scientist
Required CredentialsBachelor's in CS, Data Science, or related; knowledge of ML frameworksBachelor's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops ML models, builds backend and frontend applicationsAnalyzes data, creates visualizations, interprets data insights
Employer & Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, tech industries

While both roles require a foundation in data and programming, the Entry Level Full Stack Machine Learning Engineer focuses on developing end-to-end ML solutions, including deployment and integration, whereas the Entry Level Data Scientist primarily analyzes data and creates insights without necessarily building full applications.

More about Entry Level Full Stack Machine Learning Engineer jobs
What are the most commonly searched types of Full Stack Machine Learning Engineer jobs? The most popular types of Full Stack Machine Learning Engineer jobs are:
What job categories do people searching Entry Level Full Stack Machine Learning Engineer jobs look for? The top searched job categories for Entry Level Full Stack Machine Learning Engineer jobs are:
Entry Level Full Stack Machine Learning Engineer jobs near you
Infographic showing various Entry Level Full Stack Machine Learning Engineer job openings in the United States as of May 2026, with employment types broken down into 95% Full Time, 1% Part Time, 1% Temporary, and 3% Contract. Highlights an 99% Physical, and 1% Hybrid job distribution, with an average salary of $134,771 per year, or $64.8 per hour.
Machine Learning Engineer

Machine Learning Engineer

Darwill, Inc.

Oakbrook Terrace, IL • On-site

Full-time

Posted 11 days ago

Job description

MACHINE LEARNING ENGINEER (MLOPS / DATA ENGINEERING)
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

Apply