Interested in this AI/ML Engineer role at Cumming Group?
Apply Now →About This Role
At Cumming Group, you will work on some of the world's most exciting projects in a dynamic environment where your success is measured by the impact you make. We are one of the fastest\-growing project and cost management consultancies in the United States, as reflected in our top 10 rankings in ENR. With over 60 offices globally, an extremely diverse project portfolio, and double\-digit year\-over\-year revenue growth, the opportunities to make your mark are limitless!
Essential Duties \& Responsibilities:
- Define product vision and prioritize initiatives across multiple applications.
- Oversee requirements for gathering, feature design, and release planning.
- Guide product owners and analysts to align deliverables with business outcomes.
- Engage with stakeholders at all levels to champion product usability and value.
- Coordinate with QA and development managers to ensure on\-time delivery.
Knowledge \& Skills Required:
- Strong leadership, communication, and strategic planning skills.
- Track record of delivering enterprise applications that improve field efficiency.
- Expert in Agile product development and construction software ecosystems.
- Familiarity with analytics and business intelligence tools.
- Nurture regional/global team member and client relationships.
- Identify resources to keep current and network externally.
- Mentor/develop key team members (within and outside the chain of command).
- Demonstrate solid managerial abilities.
- Excellent verbal and written communication.
Preferred Education and Experience:
- Bachelor’s or Master’s degree in Business, Engineering, or Construction.
- 8\+ years in product leadership roles, including managing product teams.
- PMP, SAFe, or CSPO certification.
- 3\-5 years’ experience in a leadership role with supervisory responsibility.
\#LI\-JB1
*Cumming Group is committed to providing Equal Employment Opportunity in its personnel policies and practices. It is Cumming Group’s policy to recruit, hire, train and promote Team Members and applicants for employment without regard to race, color, creed, religion, age, sex, marital status, registered domestic partner status, genetic information, sexual preference, sexual orientation, gender (including gender expression and gender identity), pregnancy (including childbirth or related medical conditions, including breastfeeding), military service, national origin, ancestry, citizenship, physical disability, mental disability, veteran status or any other protected classification under federal, state, or local law. All such decisions are based on (1\) individual merit, qualifications, and competence as they relate to the particular position, and (2\) promotion of the principle of equal employment opportunity.*
*All other terms and conditions of employment, such as compensation, benefits, transfers, layoff, return from layoff, training, education, and social and recreational programs, are administered without regard to the characteristics described above. To this end, Cumming Group complies with all provisions of Title VII of the Civil Rights Act of 1964 as amended, all of the rules, regulations and relevant orders of the Secretary of Labor, and all similar state and local laws.*
The salary range for this full\-time role is $146,400\.00\-$204,933\.36 per year. Ranges are determined based on the position, geography, client and industry experience and level, and represent a good faith effort to provide a fair and equitable salary. This range reflects base salary only, and not the total compensation package. Cumming Group reserves the right to pay more or less than the posted range, depending on a candidate’s experience, skills, and qualifications, including client requirements.
*In addition to base salary, Cumming Group offers a comprehensive benefits package including:*
- *Medical*
- *Dental Insurance*
- *Vision Insurance*
- *401(k)*
- *401(k) Matching*
- *Paid Time Off*
- *Paid Holidays*
- *Short and long\-term disability*
- *Employee Assistance Program*
Salary Context
This $146K-$204K range is below the median for AI/ML Engineer roles in our dataset (median: $180K across 1841 roles with salary data).
View full AI/ML Engineer salary data →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 Cumming 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 in Demand for This Role
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. This role's midpoint ($175K) sits 20% below the category median. Disclosed range: $146K to $204K.
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.
Cumming Group AI Hiring
Cumming Group has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in MA, US. Compensation range: $204K - $204K.
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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