Machine Learning Jobs in Chicago, IL

21,986 open positions · Updated daily

Looking for Machine Learning jobs in Chicago, IL? Browse our curated listings with transparent salary information to find the perfect Machine Learning position in the Chicago, IL area.

Senior Implementation Leader manage relationships with customers coordination with internal partners

Senior Implementation Leader

Company: MetLife

Location: Chicago, IL

Posted Feb 03, 2025

The Senior Implementation Leader role at MetLife involves managing relationships with customers and brokers to implement products within a specific timeline. The leader is the first point of contact for customers, coordinating with internal partners and managing the backend process. Key responsibilities include mentoring associates, leading calls with customers and brokers, and serving as a key relationship liaison with the Sales organization. The role requires strong leadership, communication, and problem-solving skills, as well as proficiency in Microsoft Office products. MetLife offers competitive compensation, comprehensive benefits, and a supportive work environment.

View Details Apply on BuiltIn

Machine Operator I (6:00pm to 6:00am) C Shift

Company:

Location: Joliet, IL

Posted Feb 03, 2025

View Details Apply on The Muse

Customer Experience Assistant Manager

Company: Brilliant Earth

Location: Chicago, IL

Posted Feb 03, 2025

View Details Apply on The Muse

Press Operator I

Company: GANNETT

Location: Peoria, IL

Posted Feb 03, 2025

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Entry Level Sales Representative

Company:

Location: Oak Park, IL

Posted Feb 03, 2025

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Registered Nurse

Company: DaVita

Location: Mount Vernon, IL

Posted Feb 03, 2025

View Details Apply on The Muse

Team Manager

Company:

Location: Park Ridge, IL

Posted Feb 03, 2025

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Sales Professional

Company:

Location: Oak Park, IL

Posted Feb 03, 2025

View Details Apply on The Muse

Client Solutions Manager, B2B

Company: Kepler Group

Location: Chicago, IL

Posted Feb 03, 2025

View Details Apply on The Muse

Sales Intern GSIP

Company:

Location: Rolling Meadows, IL

Posted Feb 03, 2025

View Details Apply on The Muse

Commercial Named Account Executive

Company: Yubico

Location: Chicago, IL

Posted Feb 03, 2025

View Details Apply on The Muse

(USA) Member Specialist

Company: Walmart

Location: Aurora, IL

Posted Feb 03, 2025

View Details Apply on The Muse

Frequently Asked Questions

What are typical salary ranges for ML roles at different seniority levels?
Junior ML Engineers earn $90k–$120k annually, mid‑level engineers $120k–$160k, senior engineers $160k–$220k, and lead or principal ML roles can reach $220k–$300k+. In large tech firms, the upper end can exceed $350k when including equity, while early‑stage startups may offer lower base but higher stock options.
What skills and certifications are required for ML positions?
Core expertise includes Python, Jupyter, TensorFlow, PyTorch, scikit‑learn, and SQL. MLOps proficiency with Docker, Kubernetes, and cloud services (AWS SageMaker, GCP AI Platform, Azure ML) is essential for production roles. Certifications such as TensorFlow Developer, AWS Certified Machine Learning – Specialty, and Google Cloud Professional Machine Learning Engineer can validate knowledge and accelerate hiring.
Are ML jobs available for remote work?
Yes, many ML positions are fully remote or hybrid. Companies like Scale AI, Databricks, and Cohere offer remote‑first policies. Remote work requires high‑speed internet, secure VPN access, and collaboration via tools like JupyterHub, Slack, and Asana, but it also expands the geographic talent pool.
What career progression paths exist in ML?
Typical paths start as ML Engineer or Data Scientist, advance to Senior ML Engineer, Lead Data Scientist, or Research Scientist, then transition into managerial roles such as ML Manager, Director of AI, or VP of Data & AI. Progression hinges on building a strong portfolio, publishing research, mentoring junior teammates, and mastering cross‑functional skills like product strategy and ethics.
What are current industry trends shaping ML careers?
Edge AI and federated learning are driving demand for on‑device models; AutoML platforms reduce time to deployment; responsible AI frameworks (e.g., IBM AI Fairness 360) shape compliance roles; reinforcement learning is expanding into robotics; and interpretability tools like SHAP and LIME are becoming standard in regulated sectors such as finance and healthcare.

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