Applied ML Engineer job in Chicago, IL

Are you a passionate problem-solver who thrives at the intersection of data science and software engineering? We are seeking an Applied Machine Learning (ML) Engineer to join a forward-thinking tech team based in Chicago, IL. In this impactful role, you’ll deploy scalable machine learning models that solve complex, real-world challenges across industries. If you’re excited by building intelligent systems, experimenting with state-of-the-art algorithms, and pushing the boundaries of AI implementation, this opportunity is designed for you.

Bring Machine Learning Models to Life in a High-Impact Role

A leading tech-driven company in Chicago, IL is hiring an Applied ML Engineer to bridge the gap between research and production. The ideal candidate will possess a deep understanding of machine learning fundamentals, strong coding skills, and hands-on experience deploying models in production environments. This is your chance to be part of a fast-paced, collaborative environment where your contributions directly impact product performance, customer experience, and business outcomes.

Key Responsibilities of the Applied ML Engineer – Chicago, IL

End-to-End Model Development: Design, develop, and deploy scalable machine learning models from ideation to production. Collaborate with data scientists and engineers to build robust pipelines that drive real-time decision-making and personalized user experiences.

Data Engineering & Feature Design: Work with large, complex datasets to identify relevant features, clean data, and engineer new variables. Optimize data pipelines for performance, reliability, and efficiency to ensure high-quality model inputs.

Model Evaluation & Optimization: Conduct rigorous testing and validation of ML models to ensure accuracy, fairness, and performance. Implement metrics and A/B testing strategies to monitor model behavior and guide continuous improvement.

Cross-Functional Collaboration: Partner with product managers, software engineers, and domain experts to integrate ML solutions into customer-facing applications and internal tools. Translate business requirements into technical implementations.

Scalability & Deployment: Build and maintain production-grade ML systems using tools like Docker, Kubernetes, and cloud services (e.g., AWS, GCP). Ensure models are efficient, scalable, and aligned with system architecture and operational constraints.

Research & Innovation: Stay up to date with the latest trends in machine learning, deep learning, and AI. Apply cutting-edge research techniques to solve practical problems and enhance existing solutions.

Performance Monitoring & Maintenance: Monitor the health of deployed models using real-time dashboards and alerting systems. Troubleshoot and retrain models as necessary to prevent drift and maintain accuracy over time.

Code Quality & Best Practices: Write clean, modular, and well-documented code using version control (Git) and agile methodologies. Contribute to team code reviews and advocate for software engineering best practices.

Ethical AI & Compliance: Ensure models are designed with fairness, transparency, and bias mitigation in mind. Adhere to data privacy standards, regulatory requirements, and ethical guidelines in ML development and deployment.

Mentorship & Knowledge Sharing: Collaborate with and mentor junior team members, contribute to internal documentation, and help build a strong machine learning culture within the organization.

What the Client is Looking for in You

As an Applied Machine Learning Engineer, the client is seeking a technically skilled, innovative, and collaborative professional who can translate cutting-edge machine learning research into impactful, production-ready solutions. You should be a driven engineer with a strong foundation in algorithms and model development, eager to apply your expertise in real-world environments to solve complex problems and drive business value.

Strong Applied ML Experience

The ideal candidate has hands-on experience developing and deploying machine learning models in production. You should have a portfolio of projects that demonstrate your ability to solve real-world problems using supervised and unsupervised learning, NLP, or deep learning techniques. A solid understanding of data preprocessing, feature engineering, model tuning, and model evaluation is essential.

Engineering Mindset with Production-Ready Skills

The client values engineers who can write clean, scalable, and maintainable code. You must be proficient in Python and familiar with ML libraries such as TensorFlow, PyTorch, Scikit-learn, and MLflow. Experience working with REST APIs, containerization (Docker), and cloud services (AWS/GCP/Azure) is highly desirable.

Data-Driven Decision Making

You should be comfortable working with large, complex datasets and using data to inform decisions. The client is looking for a candidate who can design experiments, analyze outcomes, and iterate based on insights. Familiarity with SQL and data visualization tools is a plus.

Collaborative Communicator and Problem Solver

The client is looking for a team player who can communicate complex ML concepts to non-technical stakeholders and collaborate effectively with product managers, designers, and backend engineers. You should be proactive in identifying opportunities to apply machine learning and capable of aligning solutions with business goals.

Continuous Learner with an Innovative Edge

The field of machine learning evolves rapidly, and the client is looking for someone who stays current with the latest research and tools. A passion for learning, experimenting, and sharing knowledge is key. You should be comfortable implementing novel approaches when appropriate and adapting solutions to the task at hand.

Ethical AI and Model Accountability

Understanding the social and ethical implications of ML is important. The client values individuals who develop fair, unbiased models and implement mechanisms for transparency, interpretability, and accountability.

FAQs About the Role – Applied Machine Learning Engineer – Chicago, IL

1. What are the key responsibilities of an Applied ML Engineer in this role?

As an Applied ML Engineer, you will be responsible for developing, testing, and deploying machine learning models that solve real-world problems. You’ll work closely with data scientists, engineers, and product teams to build scalable ML systems, improve model performance, and integrate ML solutions into customer-facing products. You will also help maintain model health post-deployment and contribute to ongoing research and innovation efforts.

2. What qualifications and experience are required for this position?

The ideal candidate should have a strong background in computer science, data science, or a related field, with hands-on experience building and deploying machine learning models. Proficiency in Python and ML frameworks like TensorFlow, PyTorch, or Scikit-learn is essential. Experience working with large datasets, cloud platforms (e.g., AWS, GCP), and containerization tools like Docker is highly preferred. A bachelor’s degree is required; a master’s or Ph.D. in a relevant field is a plus.

3. What technical and soft skills are essential for this role?

Technical skills include model development, data preprocessing, performance optimization, and software engineering best practices. Familiarity with version control, experimentation, and continuous deployment tools is beneficial. Soft skills such as collaboration, communication, adaptability, and problem-solving are equally important, as the role requires cross-functional teamwork and clear communication of complex ideas to diverse stakeholders.

4. What kind of projects will I be working on?

You will work on a variety of high-impact projects that may include personalization engines, fraud detection systems, predictive analytics, natural language processing (NLP), or computer vision applications—depending on the company’s domain. These projects will involve both greenfield development and enhancing existing ML solutions in production.

5. What are the main challenges of this role?

You may face challenges such as handling noisy or incomplete data, deploying models at scale, managing model drift, and ensuring fairness and transparency in ML decisions. Balancing performance, interpretability, and system constraints while working in a fast-paced, collaborative environment is also part of the role.

6. What is the company’s culture and team environment like?

The company promotes a collaborative, innovative, and inclusive environment where experimentation and continuous learning are encouraged. You’ll be part of a cross-functional team that values knowledge sharing, open communication, and creative problem-solving. Engineers are empowered to take ownership of projects and contribute to strategic decisions.

What Remuneration Can You Expect from This Job?

As an Applied Machine Learning Engineer in Chicago, IL, you can expect a competitive compensation package reflective of your technical expertise, experience, and the high demand for advanced ML talent. The remuneration typically includes the following components:

1. Base Salary

The base salary for an Applied ML Engineer in Chicago generally ranges from $110,000 to $160,000 per year, depending on experience, industry, and company size. Candidates with advanced degrees (Master’s or Ph.D.) or experience deploying ML models at scale may command higher salaries.

2. Performance-Based Bonuses

Many employers offer annual performance bonuses based on individual contributions and company-wide performance. These bonuses can range from 10% to 25% of the base salary and may increase based on milestones achieved, model success metrics, or cross-functional impact.

3. Equity & Stock Options

For companies in the tech or startup ecosystem, equity compensation (such as stock options or RSUs) is often included as part of the total package. Equity aligns your success with the company’s growth and may significantly enhance long-term earnings, especially in high-growth or pre-IPO environments.

4. Benefits & Perks

Applied ML Engineers typically receive a robust benefits package, including:

Health, dental, and vision insurance
401(k) plans with company match
Paid time off and sick leave
Continuing education stipends or conference allowances
Wellness programs and mental health support
Flexible work hours or hybrid/remote work options
Access to cutting-edge computing tools and research resources

5. Signing Bonuses & Relocation Assistance

For highly qualified candidates or those relocating from other cities, companies may offer signing bonuses ranging from $5,000 to $20,000 and relocation assistance to cover moving expenses and temporary housing.

Total Compensation Potential

When factoring in base salary, bonuses, equity, and perks, the total annual compensation for an Applied ML Engineer in Chicago can range from $130,000 to $220,000+, depending on the organization and individual qualifications. Positions at leading tech companies or AI-focused startups may offer even more competitive packages.

How to Apply

If you’re a skilled and motivated machine learning professional with a passion for solving complex problems through data-driven innovation, we encourage you to apply for the Applied Machine Learning Engineer role in Chicago, IL. This is your opportunity to join a forward-thinking team and contribute to the development of impactful AI and ML solutions in a fast-paced, technology-driven environment.

To apply, please submit your updated resume and a brief cover letter highlighting your experience in machine learning model development, data engineering, algorithm optimization, and ML deployment at scale. Emphasize your technical proficiencies (e.g., Python, TensorFlow, PyTorch, Scikit-learn), your hands-on experience working with large datasets, and your ability to collaborate across engineering and product teams.

This position offers a high-impact opportunity to build innovative solutions, drive measurable results, and grow your career in a dynamic company. Apply today to take the next step in your career as an Applied Machine Learning Engineer in Chicago, IL!

For more information or to explore similar opportunities, visit our Machine Learning Engineer Recruiters Page.

Job Category: Machine Learning Engineer

Job Type: Full Time

Job Location: Chicago

Applied ML Engineer job in Chicago, IL