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About This Role
Why Valtech? We’re advisors, visionaries, creative and techies. We embrace all things digital. We talk to each other. We have fun. We love our clients. We’re looking ahead • We are global
Why Valtech? We’re the experience innovation company \- a trusted partner to the world’s most recognized brands. To our people we offer growth opportunities, a values\-driven culture, international careers and the chance to shape the future of experience.
The opportunity
At Valtech, you’ll find an environment designed for continuous learning, meaningful impact, and professional growth. Whether you're pioneering new digital solutions, challenging conventional thinking or building the next generation of customer experiences, your work will help transform industries.
We are proud of:
- The work we do and the innovation we drive
- Our values of share, care and dare
- Our borderless, global framework, which enables seamless collaboration
The role
We are looking for an experienced AI Engineer to lead the implementation of Azure AI Foundry within an established Microsoft Fabric environment. This role focuses on designing, deploying, and operationalizing enterprise AI capabilities that integrate seamlessly with our existing data platform, governance model, and analytics infrastructure.
You will work closely with data engineering, architecture, security, and business stakeholders to build scalable AI solutions using the Microsoft ecosystem.
This position is onsite in New York City, 5 days per week.
Role responsibilities
- Design and implement AI solutions using Microsoft Azure AI Foundry within an existing Microsoft Fabric architecture
- Integrate AI services with Fabric components including:
- + Data Factory
- + OneLake
- + Power BI
- + Lakehouse and Warehouse environments
- + Real\-Time Analytics
- Build and operationalize generative AI and machine learning workflows
- Configure and manage:
- + Azure AI Services
- + Azure OpenAI
- + Model deployment pipelines
- + Prompt orchestration and evaluation
- Establish secure connectivity between Azure AI Foundry and enterprise data sources
- Implement governance, RBAC, security, compliance, and cost management controls
- Develop reusable AI pipelines, APIs, and automation frameworks
- Collaborate with platform teams to ensure scalability, observability, and production readiness
- Support CI/CD and Infrastructure\-as\-Code deployment patterns
- Provide technical leadership and documentation for AI platform adoption
Must have qualifications
To be considered for this role, you must meet the following essential qualifications:
- 5\+ years of experience in cloud engineering, AI engineering, or data platform architecture
- Strong hands\-on experience with:
- + Microsoft Fabric
- + Azure AI Foundry
- + Azure OpenAI
- + Azure Machine Learning
- + Azure Data Services
- Experience integrating AI workloads into enterprise analytics platforms
- Proficiency in Python and/or C\#
- Experience with REST APIs, SDKs, and AI orchestration frameworks
- Knowledge of:
- + Vector databases
- + Retrieval\-Augmented Generation (RAG)
- + Prompt engineering
- + Model evaluation and monitoring
- Familiarity with DevOps practices including GitHub Actions or Azure DevOps
- Strong understanding of enterprise security and governance
Nice to have qualifications
- Microsoft Azure certifications
- Experience with:
- + Semantic models in Fabric
- + Copilot integrations
- Experience working in regulated or enterprise\-scale environments
- Consulting or stakeholder\-facing delivery experience
If you do not meet all the listed qualifications or have gaps in your experience, we still encourage you to apply. At Valtech, we recognize that talent comes in many forms, and we value diverse perspectives and a willingness to learn.
The benefits
This is a full\-time position based in New York City. The offered salary range is $160,000\-220,000 annually, depending on experience and location.
Beyond a competitive compensation package, we offer:
- Flexibility, with remote and hybrid work options (country\-dependent)
- Career advancement, with international mobility and professional development programs
- Learning and development, with access to cutting\-edge tools, training and industry experts
- Medical, dental, and vision insurance for you and your family, plus employer contributions to Health Savings Accounts
Our benefits are tailored to each location. Your Talent Partner will provide full details during the hiring process.
Your application process
Once you apply, our Talent Acquisition team will review your application. If your skills and experience align with the role, we’ll reach out for next steps. Your CV should cover key information on relevant experiences and expertise. We do not require information such as age, gender, marital status, or a headshot in your application. We review all candidates based on skills, experience, and potential.
- ️ Beware of recruitment fraud: Only engage with official Valtech email addresses.
We are committed to inclusion and accessibility. If you need reasonable accommodations during the interview process, please either indicate it in your application or let your Talent Partner know.
About Valtech
Valtech is the experience innovation company that exists to unlock a better way to experience the world. By blending crafts, categories, and cultures, we help brands unlock new value in an increasingly digital world.
At the intersection of data, AI, creativity, and technology, we drive transformation for leading organizations, including L’Oréal, Mars, Audi, P\&G, Volkswagen Dolby, and more.
At Valtech, we don’t just talk about transformation. We make it happen. Our people are the heart of our success, and we foster a workplace where everyone has the support to thrive, grow and innovate.
Are you ready to create what’s next? Join us.
For applicants in California, please see Valtech's CPRA Privacy Notice here.
Salary Context
This $160K-$220K range is above the median for AI/ML Engineer roles in our dataset (median: $181K across 1996 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 3,824 AI roles we're tracking, AI/ML Engineer positions make up 71% of the market. At Valtech 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 $178,940 based on 11,900 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($190K) sits 6% above the category median. Disclosed range: $160K to $220K.
Across all AI roles, the market median is $200,000. Top-quartile compensation starts at $253,000. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Safety ($274,200). By seniority level: Entry: $97,380; Mid: $160,000; Senior: $227,400; Director: $243,000; VP: $250,000.
Valtech Group AI Hiring
Valtech Group has 4 open AI roles right now. They're hiring across AI/ML Engineer, AI Agent Developer. Based in New York, NY, US. Compensation range: $220K - $228K.
Location Context
AI roles in New York pay a median of $210,000 across 2,448 tracked positions. That's 5% 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 3,824 open positions tracked in our dataset. By seniority: 119 entry-level, 1,813 mid-level, 1,472 senior, and 420 leadership roles (Director, VP, C-Level). Remote roles make up 16% of the market (613 positions). The remaining 3,187 roles require on-site or hybrid attendance.
The market median for AI roles is $200,000. Top-quartile compensation starts at $253,000. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($293,500 median, 31 roles); AI Safety ($274,200 median, 51 roles); Research Engineer ($260,000 median, 401 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 3,824 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,702), Data Scientist (281), AI Software Engineer (258). 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 (119) are outnumbered by mid-level (1,813) and senior (1,472) 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 420 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 16% of all AI roles (613 positions), with 3,187 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 $200,000. Top-quartile roles start at $253,000, and the 90th percentile reaches $307,500. 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 Engineering Manager roles lead at $293,500 median, while Prompt Engineer roles sit at $142,800. 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 (1,968 postings), Aws (1,203 postings), Azure (882 postings), Rag (877 postings), Gcp (735 postings), Prompt Engineering (587 postings), Pytorch (586 postings), Claude (554 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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