ML Staff Engineer - LLM & Production Systems

WHO YOU’LL WORK WITH

You’ll join our Enterprise Technology organization, partnering closely with engineering, product, and data teams to build the next generation of AI- and machine learning-powered solutions across Bain. Working in a highly collaborative environment, you’ll help define the technical direction of ML platforms that enable scalable, reliable, and impactful solutions for internal users and client-facing products.

WHERE YOU’LL FIT WITHIN THE TEAM

As a Staff Engineer, Machine Learning, you’ll play a critical role in defining the architecture, engineering standards, and operational excellence of Bain’s machine learning ecosystem. You'll partner with cross-functional teams to build scalable ML and LLM-powered systems, establish engineering best practices, and translate complex business challenges into robust technical solutions. This role is ideal for someone who enjoys solving complex engineering problems, influencing technical strategy, and mentoring other engineers while remaining hands-on with modern AI technologies.

WHAT YOU’LL DO

Architect & Build ML Systems Design and evolve scalable machine learning pipelines supporting analytics, Q&A, and insight generation across products Select and implement appropriate ML and LLM architectures based on quality, latency, scalability, and cost considerations Design resilient systems capable of handling evolving datasets while continuously improving model performance Deploy & Operate Production ML Platforms Lead production deployment of LLM-powered systems using both open-source models and commercial APIs Define service level objectives (SLOs) and ensure system reliability, scalability, and operational efficiency Develop deployment strategies and optimize inference workloads through capacity planning Own ML Platforms End-to-End Lead the design, implementation, and long-term operation of business-critical ML systems Define operational KPIs and engineering standards Lead root cause analysis and postmortems while driving continuous improvements Translate complex business needs into scalable engineering solutions Improve Data Quality & Model Performance Establish robust data contracts and monitoring practices Build evaluation frameworks including dashboards, regression testing, and slice analysis Continuously improve model quality while preventing regressions Advance MLOps & Engineering Excellence Define lifecycle management for data, models, and prompts Establish CI/CD standards and deployment best practices for ML systems Improve observability, governance, and production monitoring Mentor engineers and elevate technical standards across teams

ABOUT YOU

Required Qualifications Bachelor's degree in Computer Science, Engineering, Data Science, or a related field, or equivalent practical experience 6+ years of experience in software engineering, machine learning engineering, or related technical roles Experience designing and operating production-grade ML systems at scale Experience deploying machine learning or LLM-powered applications into production environmentsStrong proficiency in Python, SQL, and production software development Experience designing scalable ML pipelines, inference systems, and retrieval architectures Experience implementing CI/CD practices and MLOps frameworks Deep understanding of NLP, transformer architectures, retrieval systems, fine-tuning, and structured extraction Experience building cloud-based ML infrastructure Strong analytical, communication, and problem‑solving skills Proven ability to mentor engineers and influence technical direction Advanced English proficiency (written and spoken) Preferred Qualifications Advanced degree in Computer Science, Machine Learning, or a related technical discipline Experience owning machine learning platforms supporting multiple teams or products Experience operating LLM-powered systems with measurable business impact Experience establishing engineering standards across ML organizations Experience designing large-scale entity resolution or data integration systems

WORKING MODEL

This role follows a hybrid model, requiring in‑office presence at least one day per week at our Chicago office .

U.S. COMPENSATION INFORMATION

Compensation for this role includes base salary, annual discretionary performance bonus, 401(k) plan with an annual employer contribution based on years of service and Bain’s best in class benefits package. Some local governments in the United States require a good‑faith, reasonable salary range to be included in job postings for open roles. The estimated annualized compensation for this role is as follows: In Chicago, IL, the good‑faith, reasonable annualized full‑time salary range for this role is between 141k and 169k; placement within this range will vary based on several factors including, but not limited to experience, education, licensure/certifications, training, and skill level. Annual discretionary performance bonus This role may also be eligible for other elements of discretionary compensation 4.5% 401(k) company contribution, which increases after 3 years of service and is 100% vested upon start date Bain & Company's comprehensive benefits and wellness program is designed to help employees achieve personal independence, protection, and stability in the areas most important to them and their families. Bain pays 100% individual employee premiums for medical, dental, and vision programs, offering one of the most comprehensive medical plans for employees without impacting your paycheck Generous paid time off, including parental leave, sick leave, and paid holidays Fully vested 401(k) company contribution Paid Life and Long‑Term Disability insurance Annual fitness reimbursements #J-18808-Ljbffr Bain & Company