Digital Product Engineer - Machine Learning & AI

Location

This position will be based in Lisle, Illinois with hybrid in-office and remote work flexibility.

ML Product Engineer

• Build, deploy and maintain production ML systems and solutions end-to-end (training > deployment > monitoring).
• Partner with data scientists to operationalize models for real‑world use.
• Take a hands‑on role in building and iterating solutions, turning ideas into working prototypes and production capabilities.

ML Ops & Reliability

• Define and implement ML Ops best practices, including Dev Ops and CI/CD, versioning and monitoring/telemetry.
• Deploy models as scalable, reliable solutions – part of APIs, headless services, APIs, or embedded capabilities.
• Monitor model performance, data quality, and drive retention strategies.

Product Collaboration

• Partner with engineering, architecture, UX, and data science teams to translate models and insights into usable, scalable product experiences.
• Help contribute to the product goals and vision, roadmap, and delivery plan for ML/AI‑driven capabilities by identifying key problems, decisions to improve, required data, and expected business outcomes.
• Work in multi‑disciplined product teams and with cross‑functional stakeholders internally and externally as needed.
• Actively support delivery by clarifying requirements, making trade‑offs, and unblocking progress across stakeholders.
• Contribute to a team culture that values curiosity, collaboration, pragmatism, and continuous learning.

Responsible AI & Trust

• Ensure solutions meet standards for security, reliability and maintainability.
• Ensure AI capabilities are practical, trusted, and responsibly deployed through appropriate guardrails, transparency, and human‑in‑the‑loop design.

• Bachelor's degree and at least 9 years of Information Technology or IT architecture experience.
• At least 2 years of lead experience.

OR

• Master's degree and at least 5 years of Information Technology or IT architecture experience.
• At least 2 years of lead experience.

OR

• At least 12 years of Information Technology or IT architecture experience.
• At least 2 years of lead experience.

• 2-3 years of experience building and deploying ML systems using cloud infrastructure, especially in product‑led, transformation environments (e.g., Azure ML, Compute, AKS, Azure Storage, Databricks, Key Vault, Palantir).
• 1-2 years of MLOps experience, including Dev Ops‑CI/CD for ML workflows, model and experiment versioning, monitoring models, performance and drift.
• 2-3+ years of progressively responsible delivering technical solutions in Product‑led teams, or similar role using an Agile/Scrum environment. Comfort with modern product practices, including MVP definition, experimentation, metrics, feedback loops, and iterative delivery.
• Qualified candidates, excluding current employees, must be legally authorized on an unrestricted basis (US Citizen, Legal Permanent Resident, Refugee or Asylee) to be employed in the United States. This position does not anticipate providing employment‑related work sponsorship.

• Passion for working to understand needs and challenges with a customer‑centric mindset. Prior experience and skills in gathering and analyzing Voice of Customer, rapid innovation and design‑thinking.
• Initiative, with the ability to work independently when needed, and pragmatic problem‑solving abilities. Experience following a strong analytic approach to evaluate complex choices, identify issues, and propose effective solutions and decisions.
• Excellent written and verbal communication skills for interacting with users, vendors, and other IT professionals. Ability to translate complex technical topics into easy‑to‑understand information with a strong attention to detail.
• Production‑grade Python and ML engineering experience.
• Working knowledge of common data engineering, ML /AI platforms and software solutions, including ChatGPT, Claude and Copilot, Databricks, Palantir AI‑Foundry, Lang Chain or similar LLM orchestration frameworks, and Kubernetes and/or similar container technologies.
• Experience deploying ML models as scalable APIs or Services.

This position offers…