Interested in this AI/ML Engineer role at Boston Consulting Group?
Apply Now →Skills & Technologies
About This Role
Locations: Atlanta \| Austin \| Boston \| Brooklyn \| Chicago \| Dallas \| Denver \| Detroit \| Durham \| Houston \| Miami \| Minneapolis \| Nashville \| New York \| Philadelphia \| Pittsburgh \| Summit \| Washington
Who We Are
Boston Consulting Group partners with leaders in business and society to tackle their most important challenges and capture their greatest opportunities. BCG was the pioneer in business strategy when it was founded in 1963\. Today, we help clients with total transformation\-inspiring complex change, enabling organizations to grow, building competitive advantage, and driving bottom\-line impact.
To succeed, organizations must blend digital and human capabilities. Our diverse, global teams bring deep industry and functional expertise and a range of perspectives to spark change. BCG delivers solutions through leading\-edge management consulting along with technology and design, corporate and digital ventures—and business purpose. We work in a uniquely collaborative model across the firm and throughout all levels of the client organization, generating results that allow our clients to thrive.
About BCG Platinion
BCG Platinion's presence spans across the globe, with offices in Asia, Europe, and South and North America. We achieve digital excellence for clients with sustained solutions to the most complex and time\-sensitive challenge. We guide clients into the future to push the status quo, overcome tech limitations, and enable our clients to go further in their digital journeys than what has ever been possible in the past. At BCG Platinion, we deliver business value through the innovative use of technology at a rapid pace. We roll up our sleeves to transform business, revolutionize approaches, satisfy customers, and change the game through Architecture, Cybersecurity, Digital Transformation, Enterprise Application and Risk functions. We balance vision with a pragmatic path to change transforming strategies into leading\-edge tech platforms, at scale.
What You'll Do
Lead AI Tech Architects at BCG Platinion are:
- Collaborative. They are interdisciplinary team players who seek alignment and establish relationships ranging from cross\-functional stakeholder groups to existing teams.
- Technical experts. They are critical thinkers and have extensive IT expertise that drives novel solutions routed in complexity.
- Comfortable with ambiguity. They know the path forward isn't always well\-defined. They are comfortable and confident working through the unknown.
- Change agents. They know how to make change happen across an organization. They can align and onboard teams to implement new processes and toolsets. They embrace complex challenges and guide an organization to optimize IT best practices.
- Agile advocates. They are well\-versed in agile methodologies and use their expertise to strategically tackle difficult challenges and implement change.
- Innovative. They are creative thinkers who apply their deep IT architecture expertise to envision novel design patterns for the next generation of technology solutions.
- Knowledgeable. They have a sophisticated understanding of IT Architecture, acting as a viable resource on teams as both a hands\-on practitioner and subject matter expert.
- Strategic partners. They work closely with senior client stakeholders, including C\-level executives, to build hypothesis\-driven solutions at the intersection of technology and business. They bridge the gap between IT and business functions, ensuring technology strategies are aligned with organizational goals to solve critical business challenges.
What You Are Good At
IT Architecture and Solution Design
- Designing solution, application, and data architecture.
- Developing feasibility studies, technical concepts, executing technical proofs of concept, and scaling software solutions.
- Performing technology assessments and implementing IT architectures.
- Analyzing complex IT application landscapes and status quo for IT architecture optimization.
- Reviewing technical architecture and code.
IT Optimization and Transformation
- Supporting IT functions during mergers and acquisitions, including the functional and technical transformation of an organization’s IT department.
- Restructuring IT processes and organization.
- Optimizing the application development processes.
Implementation Management and Support
- Designing work packages/modules in IT implementation projects.
- Evaluating products, SW packages, and solutions, including comparative studies across organizations’ systems (e.g., ERPs, HR systems, Data Analytics).
- Assessing quality assurance for IT implementation.
Communication and Collaboration
- Crafting compelling narratives, translating complex ideas for both technical and non\-technical audiences.
- Delivering impactful presentations, leading modules, presenting findings, and building consensus with clients.
- Building collaboration, mentoring teams, and sharing knowledge to drive collective success.
- Facilitating technical and strategic working sessions and workshops with both client and internal teams.
- Providing direction on key work items and feedback to other team members.
Team Management
- Manage junior team members by defining and organizing their "module", helping them structure their work and associated analyses.
- Mentor and coach junior team members by building mutual development agreements and manufacturing opportunities for them to grow and develop along explicitly defined objectives.
- Provide quality assurance oversight \- Review junior team members’ output for overall correctness, level of insight, clarity, etc.
- Promote an overall positive experience for junior staff.
- Serve as a role model by actively demonstrating and living BCG’s Culture and Values.
Innovation and Growth
- Driving innovation, uncovering novel ideas and transformative solutions.
- Fostering a growth mindset, continuously learning and applying new skills to grow your impact.
- Building relationships with key clients.
- Assisting with business development through writing proposals and scoping projects.
What You'll Bring
- Bachelor's degree in information technology, business administration, computer science, information systems, or system controls \& engineering or a related field (Master’s degree is a plus).
- 6\+ years of technology consulting or software engineering experience with more than 3\+ years in architecture discipline.
- Excellent communication and presentation skills, ability to act as a trusted advisor and influence clients and BCG case leadership teams.
- Outstanding ability to work creatively, autonomously, analytically, in a fast\-paced problem\-solving environment with a focus on customer and results.
- Superior technical knowledge, engineering rigor, and creative problem\-solving.
- Ability to explain complex technology topics to senior executives.
- Extensive technical expertise and knowledge along multiple of the following topics:
+ Cloud technologies, architectures, designing cloud workloads and optimizing cloud footprint (i.e., FinOps).
+ Integration methodologies, design patterns and associated tooling (API and Microservices architecture).
+ Structured and unstructured databases and usage patterns.
+ Data platform architecture and associated patterns (e.g. Data Lake, Data Warehouse, Lakehouse, etc.).
+ Data analytics, AI and GenAI architecture.
+ Application modernization, programming paradigms and approaches (e.g. object\-oriented).
+ Mainframe architecture.
+ Process automation approaches and tooling (e.g. DevOps, AIOps).
- An agile mindset that moves past blockers and a vision to iteratively migrate to the modern set of architecture capabilities with a lens of business benefits/value.
- Gen AI tool fluency (e.g., proven usage of GenAI such as ChatGPT, Claude) and validation of response.
- Willingness to travel to work with clients and BCG teams. At times, this role involves significant travel to client sites. The amount of travel will depend on client needs and nature of projects.
Additional info
What We Offer:
At BCG, we care about our people, and offer best in class benefits to support you personally and professionally including:
- An opportunity to work organically across disciplines and across BCG, we offer a unified and unrivaled opportunity that combines strategic thinking with hands\-on applications.
- A unique experience to work alongside a team of passionate and driven problem\-solvers with a mission to deliver innovative and valuable digital solutions in a supportive environment.
For U.S. Applicants:
The first year base compensation for this role is $190,000 in USD. In addition to your base salary, you will also be eligible for an annual discretionary performance bonus and BCG’s Profit Sharing and Retirement Fund (PSRF) contribution. BCG also provides a market leading benefits package described below.
At BCG, we are committed to offering a comprehensive benefit program that includes everything our employees and their families need to be well and live life to the fullest. We pay the full cost of medical, dental, and vision coverage for employees – and their eligible family members.\* That’s zero dollars in premiums taken from employee paychecks. All our plans provide best in class coverage:
- Zero\-dollar ($0\) health insurance premiums for BCG employees, spouses, and children.
- $10(USD) copays for trips to the doctor, urgent care visits and prescriptions for generic drugs.
- Dental coverage, including up to $5,000 (USD) in orthodontia benefits.
- Vision insurance with coverage for both glasses and contact lenses annually.
- Reimbursement for gym memberships and other fitness activities.
- Fully vested retirement contributions made annually, whether you contribute or not.
- Generous paid time off including vacation, holidays, and annual office closure between Christmas and New Years.
- Paid Parental Leave and other family benefits such as elective egg freezing, surrogacy, and adoption reimbursement.
- Employees, spouses, and children are covered at no cost. Employees share in the cost of domestic partner coverage.
To learn more about our employee benefits please check our Benefits page.
Boston Consulting Group is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, age, religion, sex, sexual orientation, gender identity / expression, national origin, disability, protected veteran status, or any other characteristic protected under national, provincial, or local law, where applicable, and those with criminal histories will be considered in a manner consistent with applicable state and local laws.
Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 3,708 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At Boston Consulting Group, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills Required
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $218,750 based on 3,817 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $230,000.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
Boston Consulting Group AI Hiring
Boston Consulting Group has 4 open AI roles right now. They're hiring across AI/ML Engineer. Positions span Summit, NJ, US, Brooklyn, NY, US, New York, NY, US.
Location Context
AI roles in New York pay a median of $220,000 across 1,045 tracked positions.
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (102) are outnumbered by mid-level (1,705) and senior (1,469) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $300,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
Get Weekly AI Career Intelligence
Salary data, skills demand, and market signals from 16,000+ AI job postings. Every Monday.