ML Staff Engineer - LLM & Production Systems

General Information Job Title ML Staff Engineer – LLM & Production Systems Job ID 107242 Work Areas Technology & Engineering Employment Type Permanent Full-Time Location(s) Boston, Chicago, Dallas, New York Description & Requirements WHAT MAKES US A GREAT PLACE TO WORKWe are proud to be consistently recognized as one of the world’s best places to work. We are currently the top ranked consulting firm on Glassdoor’s Best Places to Work list and have earned the #1 overall spot a record seven times. Extraordinary teams are at the heart of our business strategy, but these don’t happen by chance. They require intentional focus on bringing together a broad set of backgrounds, cultures, experiences, perspectives, and skills in a supportive and inclusive work environment. We hire people with exceptional talent and create an environment in which every individual can thrive professionally and personally.WHO YOU’LL WORK WITHYou’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 TEAMAs 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 DOArchitect & Build ML SystemsDesign and evolve scalable machine learning pipelines supporting analytics, Q&A, and insight generation across productsSelect and implement appropriate ML and LLM architectures based on quality, latency, scalability, and cost considerationsDesign resilient systems capable of handling evolving datasets while continuously improving model performanceDeploy & Operate Production ML PlatformsLead production deployment of LLM-powered systems using both open-source models and commercial APIsDefine service level objectives (SLOs) and ensure system reliability, scalability, and operational efficiencyDevelop deployment strategies and optimize inference workloads through capacity planningOwn ML Platforms End-to-EndLead the design, implementation, and long-term operation of business-critical ML systemsDefine operational KPIs and engineering standardsLead root cause analysis and postmortems while driving continuous improvementsTranslate complex business needs into scalable engineering solutionsImprove Data Quality & Model PerformanceEstablish robust data contracts and monitoring practicesBuild evaluation frameworks including dashboards, regression testing, and slice analysisContinuously improve model quality while preventing regressionsAdvance MLOps & Engineering ExcellenceDefine lifecycle management for data, models, and promptsEstablish CI/CD standards and deployment best practices for ML systemsImprove observability, governance, and production monitoringMentor engineers and elevate technical standards across teamsABOUT YOURequired QualificationsBachelor's degree in Computer Science, Engineering, Data Science, or a related field, or equivalent practical experience6+ years of experience in software engineering, machine learning engineering, or related technical rolesExperience designing and operating production-grade ML systems at scaleExperience deploying machine learning or LLM-powered applications into production environmentsStrong proficiency in Python, SQL, and production software developmentExperience designing scalable ML pipelines, inference systems, and retrieval architecturesExperience implementing CI/CD practices and MLOps frameworksDeep understanding of NLP, transformer architectures, retrieval systems, fine-tuning, and structured extractionExperience building cloud-based ML infrastructureStrong analytical, communication, and problem-solving skillsProven ability to mentor engineers and influence technical directionAdvanced English proficiency (written and spoken)Preferred QualificationsAdvanced degree in Computer Science, Machine Learning, or a related technical disciplineExperience owning machine learning platforms supporting multiple teams or productsExperience operating LLM-powered systems with measurable business impactExperience establishing engineering standards across ML organizationsExperience designing large-scale entity resolution or data integration systemsWORKING MODELThis role follows a hybrid model, requiring in-office presence at least one day per week at our Chicago, NYC, Dallas or Boston office.U.S. COMPENSATION INFORMATIONCompensation 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.In NYC, NY, the good-faith, reasonable annualized full-time salary range for this role is between 160k and 192k; placement within this range will vary based on several factors including, but not limited to experience, education, licensure/certifications, training, and skill level.In Boston, MA, the good-faith, reasonable annualized full-time salary range for this role is between 147k and 176k; placement within this range will vary based on several factors including, but not limited to experience, education, licensure/certifications, training, and skill level.In Dallas, TX, the good-faith, reasonable annualized full-time salary range for this role is between 134.5k and 161.5k; 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 bonusThis role may also be eligible for other elements of discretionary compensation4.5% 401(k) company contribution, which increases after 3 years of service and is 100% vested upon start dateBain & 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 paycheckGenerous paid time off, including parental leave, sick leave, and paid holidaysFully vested 401(k) company contributionPaid Life and Long-Term Disability insurance Go back