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About This Role
Locations: Atlanta \| Chicago \| Brooklyn
Who We Are
At Inverto North America, we’re shaping the future of procurement and supply chain, and we’re doing it with ambition, pace, and purpose. Backed by BCG and driven by our own entrepreneurial spirit, we work globally with market\-leading clients to deliver strategies that make businesses stronger.
Our people are at the heart of that impact. We’re experts in our field, and we don’t stand still. We grow our capabilities, expand our offering, and scale our global presence together. Our success opens new doors for everyone here, and we make sure that growth is shared. Over the last few years, we've made big investments in our ability to bring digital and AI\-based tools to our clients, including a center of excellence focused on the Digital, Data \& AI topic.
As we build and expand our existing team of Digital, Data \& AI experts, we’re looking for individuals who bring data, digital tools, and AI methods into real consulting projects that create measurable value in procurement and supply chain management. If you want to make a tangible difference, build lasting client relationships, and shape what comes next \- we’d love to have you with us.
What You'll Do
As a Senior Consultant, you won’t just gather insights \- you’ll turn them into action. You’ll actively work with clients to implement our digital and AI\-based solutions in real world contexts to help clients unlock value and shape their technological future.
From day one, you’ll collaborate closely with our team of procurement professionals, gain exposure to C\-level thinking, and take ownership of workstreams that matter. You’ll also help guide junior colleagues, sharing your knowledge and setting the pace for the team.
As part of a fast\-growing practice and an even faster\-growing center of excellence, you’ll have the space to shape your journey. Whether you’re looking to deepen your expertise, explore new industries, or take the next step in your consulting career, we’ll support you with tailored development and real responsibility.
You’ll grow, you’ll contribute, and you’ll do it alongside a team that wants to see you succeed.
As part of a high\-growth company, with accelerated opportunities you will be responsible for:* Pioneering digital and AI. You'll lead AI\-based, client\-facing workstreams and modules that enable clients to be at the cutting\-edge.
- Data\-driven project support. You’ll bring data, digital tools, and AI methods into real consulting projects \- supporting teams and clients with analyses, insights, and prototypes that create measurable value in procurement and supply chain management.
- Analytics with purpose. From cleansing and transforming raw data into structured insights to building intuitive dashboards and self\-service reports, you’ll make information accessible and actionable for project teams and clients.
- Smart automation. You’ll apply modern technologies such as Microsoft Power Platform, Azure, Python, and GenAI to streamline processes, whether that’s automating data extraction, building forecasting models, or experimenting with AI\-enabled solutions that make procurement smarter and faster.
- Innovation and learning. You’ll continuously explore how new technologies like LLMs, intelligent automation, and advanced analytics can be applied to procurement and supply chain challenges, sharing knowledge with colleagues and contributing to the growth of our digital, data \& AI community at Inverto.
What You'll Bring
- 4\+ years of professional experience in analytics, consulting, or data\-driven roles, including hands\-on work with core analysis and visualization tools (e.g., SQL, Power BI, Excel) as a foundation for developing more advanced solutions.
- Bachelor’s degree from an accredited university (Master’s preferred).
- Proficiency in Python for data transformation, automation, and building analytic or AI\-supported workflows. Experience working within cloud environments (Azure preferred) and/or the Microsoft Power Platform.
- Curiosity and practical experience with modern AI technologies, such as using large language models (LLMs), retrieval\-based systems, or workflow/agent orchestration frameworks. Examples may include OpenAI APIs, LangChain, LlamaIndex, vector databases, or similar tools \- but prior exposure to all is not required.
- Ability to translate complex business problems \- especially in procurement and supply chain \- into scalable analytics, automation, or AI\-enabled solutions.
- Strong analytical and problem\-solving skills, paired with creativity, pragmatism, and the ability to design solutions that balance technical innovation and real\-world feasibility.
- Consulting mindset and behaviors: independence, structured thinking, clear communication of insights, and the confidence to influence clients and stakeholders.
- Results\-oriented mindset with a high level of personal accountability.
- Willingness to travel to work with clients and Inverto teams. At times, this role will require significant travel to client sites. The amount of travel will depend on client needs and nature of projects.
- An authentic, entrepreneurial spirit that thrives through team collaboration.
Who You'll Work With
- Talented, highly driven colleagues with deep expertise in procurement, tech sourcing, and related fields.
- Entrepreneurial thinkers with a strong growth mindset and passion for procurement and supply chain.
- Teammates who bring energy, focus, and real\-world value\-creation experience.
- Authentic, collaborative people who elevate the team and support each other to succeed.
Additional info
YOU'LL BE BASED IN: This role is currently open in Chicago or Atlanta.
YOU'LL BE TRAVELING: Moderate travel is anticipated and will vary based on specific project locations.
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 base compensation for this role is $160,000 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 benefit 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
Across all AI roles, 14% (508 positions) offer remote work, while 3,180 require on-site attendance. Top AI hiring metros: New York (1,045 roles, $220,000 median); San Francisco (810 roles, $277,088 median); Los Angeles (397 roles, $215,000 median).
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
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