Interested in this AI/ML Engineer role at Campana & Schott Business Services GmbH?
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About Us
Campana & Schott Inc. is the New York City-based innovation hub of the Campana & Schott Group, a privately held, 30+ year-old management and technology consulting firm with 600+ employees across Europe and the US.
We create tangible results for our clients by designing AI solutions and leading business transformations and change - spanning digital workplace, customer insights and analytics, and novel ways of working.
In the U.S., Campana & Schott focuses on healthcare and pharmaceuticals, combining digital and technology innovation with change management and transformation to create new momentum.
We are currently looking for an Associate Vice President - Data & AI to join our team in New York.
Our Values
Passion
We approach every single project with enthusiasm – we thrive on new challenges and taking the perspective of our clients and their people.
Diversity
We value the diversity of the people in our company – irrespective of nationality, family situation, sexual orientation, religion, or age. Our diversity benefits us all – we want to see things from your perspective!
Respect
We treat each other with respect and as equals – regardless of our age, position in the hierarchy, or role in the company. We’re all on first name terms and are always available for our colleagues.
Day in the Life
As an Associate Vice President at Campana & Schott U.S., you will lead our Data & AI practice and be the cornerstone of the strategic vision for AI-enabled Consulting. Your unparalleled expertise will guide our clients through complex business landscapes, fostering transformative growth and innovation.
Here are some of your key responsibilities:
Business Development: Lead the development of growth strategies for our Data & AI practice. Build new client relationships in the Life Science industry and position Campana & Schott as a trusted partner for agentic AI and analytics. Your ability to identify opportunities and forge connections will be instrumental.
Strategic Visionary: Develop a trusted partnership with new clients. Envision new ways of working by improving underlying business and operating models, processes, and enabling technology — including where AI agents and data products can create lasting value. Your thought leadership in the Data Science and Analytics space will drive innovative solutions.
Project Leadership: Steer interdisciplinary project teams to manage client initiatives end-to-end. From project planning to implementation, you'll oversee strategic AI, data, and analytics projects and entire portfolios.
Internal Impact: Engage in important internal initiatives. Collaborate with colleagues across established Campana & Schott hubs in Europe and shape our growing U.S. business, contributing to our collective success.
Organizational Leadership: Function as an inspiring leader for our team of data scientists, computer scientists, and consultants. Help develop and build our brand as a Life Sciences firm with strong agentic AI expertise and shape the future consulting organization from an AI-first perspective. Your influence will resonate both within our organization and with our clients.
What's in it for You
Join a dynamic team with a Start-Up atmosphere supported by strong roots of 30 years of successful business in Europe. If you are looking for a fast-paced working environment with exciting and innovative mandates around business transformation and if you are enjoying working closely with great colleagues and great clients, then this is a unique opportunity for you.
Professional & Personal
You can expect excellent project work and a trusting atmosphere with your colleagues, where you are challenged to contribute to impactful AI, data, and analytics engagements across the Life Sciences service spectrum of our NY-based team.
Live Collaboration
Mentoring from senior professionals and engagement in an active exchange of knowledge with over 600 consultants worldwide in forums and special expertise groups.
Compensation
The salary range for this position is $204,000 - $216,000 per year and total compensation for this role includes base salary, annual discretionary performance bonus, and a comprehensive benefits package described below. We expect total annualized compensation for New York City-based employees to be approximately the following:
- Base salary between $204,000 - $216,000 p.a.. Placement within this range will vary based on experience and skill level
- Annual discretionary performance bonus between 0-40%
In addition, we offer a comprehensive benefits package, including:
- 25 days of PTO p.a.
- 10 company paid holidays p.a.
- 5 days of professional development p.a.
- Option for employees to make personal contributions to a 401(k) plan, as well as 401(k) matching offered by Campana & Schott
- Attractive health benefits
- Annual company trip and regular team events
All qualified applicants will receive consideration for employment without regard to age, race, creed, color, national origin, ancestry, marital status, sex, affectional or sexual orientation.
Preferred Qualifications
- MBA, MSc, PhD or related degree from an accredited College or University.
- Minimum of 8 years of relevant work experience, ideally including recent management or technology consulting with hands-on exposure to AI, data science, or analytics delivery.
- Passion for Transformation: You thrive on business transformations, agentic AI, agile organizations, and international collaboration.
- AI & Data Expertise: Hands-on familiarity with modern AI/ML, LLMs, and agentic systems, and the realities of deploying them in enterprise environments (data integration, governance, security, MLOps).
- Leadership: Proven experience leading and developing technical teams of data scientists, ML engineers, or computer scientists, ideally with P&L or service-line accountability.
- Fluency in written and spoken English is mandatory.
- Strong communication skills and a team-oriented mentality.
- An analytical mindset, entrepreneurial spirit, and self-motivated working attitude.
- Flexibility and willingness to travel.
Do you have questions regarding your application?
Please contact us!
Please visit us on LinkedIn
Salary Context
This $204K-$216K range is above the median for AI/ML Engineer roles in our dataset (median: $175K across 1356 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 8,943 AI roles we're tracking, AI/ML Engineer positions make up 75% of the market. At Campana & Schott Business Services GmbH, 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 $212,000 based on 11,866 positions with disclosed compensation. Disclosed range: $204K to $216K.
Across all AI roles, the market median is $213,380. Top-quartile compensation starts at $264,148. The 90th percentile reaches $319,310. For comparison, the highest-paying categories include AI Safety ($253,100) and Research Engineer ($252,000). By seniority level: Entry: $110,408; Mid: $193,200; Senior: $228,700; Director: $272,250; VP: $235,000.
Campana & Schott Business Services GmbH AI Hiring
Campana & Schott Business Services GmbH has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in New York, NY, US. Compensation range: $216K - $216K.
Location Context
AI roles in New York pay a median of $221,000 across 2,878 tracked positions. That's 4% above the national 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 8,943 open positions tracked in our dataset. By seniority: 175 entry-level, 4,132 mid-level, 3,268 senior, and 1,368 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (521 positions). The remaining 8,351 roles require on-site or hybrid attendance.
The market median for AI roles is $213,380. Top-quartile compensation starts at $264,148. The 90th percentile reaches $319,310. Highest-paying categories: AI Safety ($253,100 median, 57 roles); Research Engineer ($252,000 median, 419 roles); AI Engineering Manager ($251,622 median, 51 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 8,943 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,739), AI Product Manager (403), AI Software Engineer (402). 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 (175) are outnumbered by mid-level (4,132) and senior (3,268) 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 1,368 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (521 positions), with 8,351 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 $213,380. Top-quartile roles start at $264,148, and the 90th percentile reaches $319,310. 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 $253,100 median, while Prompt Engineer roles sit at $141,440. 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 (1,422 postings), Aws (808 postings), Azure (638 postings), Rag (555 postings), Gcp (457 postings), Pytorch (433 postings), Claude (341 postings), Kubernetes (337 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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