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Associate Machine Learning Jobs in Skokie, IL (NOW HIRING)

Pwc

AI & GenAI Data Scientist-Senior Associate

Chicago, IL · On-site

$77K - $202K/yr

As a Senior Associate, you will focus on building meaningful client connections and learning how to ... Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS ...

Pwc

AI & GenAI Data Scientist-Senior Associate

Rosemont, IL · On-site

$77K - $202K/yr

As a Senior Associate, you will focus on building meaningful client connections and learning how to ... Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS ...

Samprasoft

Data Engineer 3

Chicago, IL

$118K - $141K/yr

... Associate) Familiarity with machine learning and data design to support machine learning Experience with productionizing machine learning workloads Experience with ElasticSearch/ELK, Kibana, Grafana ...

Deloitte

AI Solutions Architect

Chicago, IL

$65 - $85.50/hr

... Machine Learning Engineer, Microsoft Azure AI Engineer Associate, Microsoft Azure Data Scientist Associate, or Microsoft Azure Solutions Architect Expert The wage range for this role takes into ...

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All JobsAssociate Machine Learning JobsAssociate Machine Learning Jobs in Skokie, IL

Associate Machine Learning information

See Skokie, IL salary details

$30.1K

$127.1K

$300.3K

How much do associate machine learning jobs pay per year?

As of Jun 16, 2026, the average yearly pay for associate machine learning in Skokie, IL is $127,057.00, according to ZipRecruiter salary data. Most workers in this role earn between $43,900.00 and $192,900.00 per year, depending on experience, location, and employer.

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

AspectAssociate Machine LearningData Scientist
Required CredentialsBachelor's degree in CS, Data Science, or related field; some roles may require certifications in ML or AIBachelor's or Master's in CS, Statistics, or related; often requires experience with data analysis and programming
Work EnvironmentEntry-level, team-based projects, focused on supporting ML models and data preprocessingMore autonomous, involved in data analysis, model development, and interpretation
Employer & Industry UsageTech companies, startups, research labs; roles in AI and ML teamsWide range of industries including tech, finance, healthcare, and consulting

While both roles involve working with data and machine learning, an Associate Machine Learning typically focuses on supporting ML projects with less experience, whereas a Data Scientist has broader responsibilities including data analysis, model development, and strategic insights. The roles often overlap but differ in scope and experience level.

What are the key skills and qualifications needed to thrive as an Associate Machine Learning Engineer, and why are they important?

To thrive as an Associate Machine Learning Engineer, you need a solid background in mathematics, programming (especially Python), and foundational machine learning concepts, usually supported by a relevant degree. Familiarity with tools like TensorFlow, PyTorch, scikit-learn, and experience with data processing libraries and version control systems is typically required. Strong analytical thinking, problem-solving ability, and effective collaboration skills help you stand out in this role. These competencies are essential for developing robust models, working efficiently with teams, and delivering impactful data-driven solutions.

What are some common challenges faced by Associate Machine Learning professionals when transitioning from academic projects to real-world business applications?

Associate Machine Learning professionals often find that moving from academic or theoretical projects to business-focused environments introduces new challenges. Real-world datasets can be messy, incomplete, or imbalanced, requiring additional data cleaning and preprocessing. Moreover, business timelines may require rapid prototyping and iterative model development, which is different from the more open-ended nature of academic research. Collaborating with cross-functional teams such as data engineers, product managers, and business stakeholders is also essential to align models with organizational goals. Adapting to these practical aspects is key to succeeding in an Associate Machine Learning role.

What does an Associate Machine Learning Engineer do?

An Associate Machine Learning Engineer assists in designing, developing, and deploying machine learning models under the supervision of senior engineers. They handle tasks such as data preprocessing, model evaluation, and maintaining machine learning pipelines. Associates often collaborate with data scientists, software engineers, and business teams to ensure that machine learning solutions are integrated effectively into products or services. This role is typically entry-level or early career and is a stepping stone toward more advanced machine learning positions.
What are popular job titles related to Associate Machine Learning jobs in Skokie, IL? For Associate Machine Learning jobs in Skokie, IL, the most frequently searched job titles are:
What job categories do people searching Associate Machine Learning jobs in Skokie, IL look for? The top searched job categories for Associate Machine Learning jobs in Skokie, IL are:
What cities near Skokie, IL are hiring for Associate Machine Learning jobs? Cities near Skokie, IL with the most Associate Machine Learning job openings:
Associate Machine Learning jobs near you
Machine Learning Engineering Manager

Machine Learning Engineering Manager

United Airlines, Inc.

Chicago, IL • On-site

$118K - $141K/yr

Full-time

Posted 2 days ago

United Airlines rating

7.8

Company rating: 7.8 out of 10

Based on 332 frontline employees who took The Breakroom Quiz

9th of 26 rated airlines

Job description

Description
United's Digital Technology team is comprised of many talented individuals all working together with cutting-edge technology to build the best airline in the history of aviation. Our team designs, develops and maintains massively scaling technology solutions brought to life with innovative architectures, data analytics, and digital solutions.
Job overview and responsibilities
Develops and programs integrated software algorithms to structure, analyze and leverage data in systems applications. Develops and communicates statistical modeling techniques to develop and evaluate algorithms to improve product/system performance, quality, data management and accuracy. Completes programming and implements efficiencies, performs testing and debugging. Completes documentation and procedures for installation and maintenance. Applies deep learning technologies to give computers the capability to visualize, learn and respond to complex situations. Can work with large scale computing frameworks, data analysis systems and modeling environments.
  • Design and implement key components of the Machine Learning Platform infrastructure and establish processes and best practices
  • Work cross-functionally with data scientists, data engineers, and IT teams to design, develop, deploy, and integrate high-performance, production-grade machine learning solutions and data intensive workflow
  • Partner with data scientists and data engineers to create and refine features from underlying data and build reproducible feature pipelines to train models and serve features in production
  • Partner with data platform and operations teams to solve complex data ingestion, pipeline and governance problems for machine learning solutions
  • Take ownership of production systems with a focus on delivery, continuous integration, and automation of machine learning workloads
  • Provide technical mentorship, guidance, and quality-focused code review to data scientists and ML engineers

Qualifications
What's needed to succeed (Minimum Qualifications):
  • Bachelor's degree in computer science, Engineering, or a related technical discipline
  • 4-8 years of experience in managing technical teams and projects
  • 4+ years of experience in full software lifecycle development using Python
  • 4+ years of experience leading an ML Ops team familiar with large cloud environments, Big Data technologies
  • 4+ years in software development in Python, Java, PySpark
  • 4+ Years of Experience with Machine Learning and Machine Learning workflows
  • 3+ years of experience designing an developing using technologies as Docker, Kubernetes
  • Strong software engineering experience with Python and at least one additional language such as Java, Go, Rust, or C/C++
  • Understanding of machine learning principles and techniques
  • Experience with data science tools and frameworks (e.g. PyTorch, Tensorflow, Keras, Pandas, Numpy, Spark)
  • Experience designing and developing scalable cloud native solutions using technologies such as Docker and Kubernetes and serverless services such as AWS Lambda, EKS, ECS, Fargate
  • Experience building infrastructure-as-code templates (e.g. AWS CloudFormation) and cloud-native CI/CD pipelines using tools such as AWS CodePipeline
  • Experience building ETL pipelines and working with big data technologies (e.g. Hadoop, Spark, and serverless technologies such as EMR, Redshift, S3, AWS Glue, and Kinesis)
  • Knowledge of distributed systems as it pertains to compute and data storage
  • Strong desire to experiment with and learn new technologies and stay aligned with the latest community developments in ML Ops/Engineering and cloud native
  • Excellent oral and written communication skills
  • Ability to prepare high-quality presentation materials and explain complex concepts and technical materials to less-technical audiences
  • Must be legally authorized to work in the United States for any employer without sponsorship
  • Successful completion of interview required to meet job qualification
  • Reliable, punctual attendance is an essential function of the position

What will help you propel from the pack (Preferred Qualifications):
  • AWS Certified Solution Architect (Associate or Professional)
  • Experience working as a Machine Learning Engineer or Data Scientist building and productionalizing machine learning solutions
  • Experience building real-time event-driven stream processing solutions with technologies such as Kafka, Flink, and Spark
  • Experience with GPU acceleration (e.g. CUDA and CuDNN)
  • Experience with Kubernetes

What United Airlines employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

United Airlines logo

About United Airlines

Sourced by ZipRecruiter

United Airlines is embarking on an exciting journey to become the best airline in aviation history. Our purpose, "Connecting People, Uniting the World," extends beyond transportation, emphasizing our commitment to uplift and create opportunities in the places we serve. With a global presence and diverse workforce, we value inclusivity and are dedicated to hiring tens of thousands of individuals across various roles. Our comprehensive benefits package, including perks like space available travel, parental leave, and 401k, aims to support your well-being and growth.

Industry

Aviation

Company size

10,000+ Employees

Headquarters location

Chicago, IL, US

Year founded

1926

Social media

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