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.

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.

• 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

• 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

• 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

• Establish robust data contracts and monitoring practices
• Build evaluation frameworks including dashboards, regression testing, and slice analysis
• Continuously improve model quality while preventing regressions

• 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

• 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 environments
  
  Strong 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)

• 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

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