Interested in this AI/ML Engineer role at Merck?
Apply Now →Skills & Technologies
About This Role
Job Description
The Associate Director, AI Activation & Data Science is a member of the AI Activation team within Digital Human Health (DHH), supporting the Specialty, Pharma & Infectious Diseases business units. This role is designed for a highly technical AI leader with deep, hands-on expertise in building and deploying AI solutions, including generative AI, large language models (LLMs), and agentic systems, who is eager to apply that expertise to pharmaceutical commercial challenges. Working in close partnership with brand, marketing, Market Engagement (ME), and commercial analytics colleagues, this leader ensures AI solutions are grounded in real business needs. The Associate Director leads the technical design and delivery of strategic AI programs, defines scalable AI architectures and guardrails, and moves AI use cases from prototype to production with measurable business value, while upholding responsible AI, compliance, and governance standards.
Primary Job Function and Key Responsibilities:
AI solution architecture and delivery:
- Own the technical design and end-to-end delivery of DHH-wide strategic AI initiatives from ideation and prototyping through deployment and adoption.
- Design and build generative AI and agentic solutions, including LLM applications, retrieval-augmented generation (RAG), multi-agent workflows, tool and API integrations, and simulation or scenario-planning capabilities.
- Define scalable AI architectures, reusable components, and delivery guardrails so that AI use cases can be operationalized and democratized across ME teams.
- Establish rigorous evaluation approaches for AI solutions, covering accuracy, groundedness, reliability, latency, cost, and safety, and monitor performance in production.
- Lead MLOps/LLMOps practices, including versioning, CI/CD, monitoring, and model lifecycle management, in partnership with IT and platform teams.
- Stay current on the rapidly evolving AI landscape (models, frameworks, and tools) and assess which internal and external capabilities should be adopted.
AI enablement partnership and governance:
- Run targeted AI pilots in prioritized areas of business impact (e.g., field and customer engagement tools, targeting support, forecast validation, barrier analysis, causal inference), rapidly prototyping and validating value with business partners.
- Partner closely with brand, ME, and commercial analytics teams to understand business needs and translate them into technical requirements and solution designs.
- Activate and guide external delivery partners and vendors, setting technical standards and reviewing solution quality.
- Apply a structured prioritization approach to triage AI requests, and guide teams toward approved enterprise AI tools and platforms.
- Champion responsible AI practices, ensuring solutions meet data privacy, security, model validation, and enterprise governance standards.
- Mentor team members and build technical AI capability across the business, establishing best practices for prompt engineering, agent design, and AI development.
Required Experience & Skills:
- 5+ years of experience in AI/ML engineering, applied data science, or a related technical field, including at least 2 years of hands-on experience building generative AI or LLM-based solutions. Prior pharmaceutical or healthcare industry experience is required.
- Deep expertise in LLMs and generative AI, including RAG, embeddings and vector databases, agent frameworks (e.g., LangChain, LangGraph, Semantic Kernel), prompt engineering, and fine-tuning.
- Proven track record of taking AI solutions from prototype to production at enterprise scale, including solution architecture, APIs, cloud services for building AI and agents (e.g., Google Cloud Vertex AI, Amazon Bedrock), and MLOps/LLMOps.
- Experience designing evaluation frameworks and guardrails for AI systems, grounded in responsible AI principles and governance.
- Advanced Python and SQL skills, experience with Databricks or similar platforms, and strong software engineering practices (e.g., Git, testing, CI/CD), backed by a solid foundation in machine learning and statistics.
- Explains complex AI concepts in plain business language to non-technical stakeholders and senior leaders, with a product mindset focused on user needs, adoption, and measurable business value.
- Aligns brand, ME, IT, and cross-functional stakeholders on priorities, and manages scope by redirecting out-of-scope requests while maintaining strong relationships.
- People and/or matrix leadership experience, including leading cross-functional teams, global collaborators, and external delivery partners and vendors.
- Strong organizational and project management skills; resilient and adaptable in ambiguity and a fast-moving AI landscape.
Qualifications:
- Master's degree or PhD in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a related technical discipline is required.
Required Skills:
Business Case Development, Business Case Development, Business Intelligence (BI), Business Needs, Competency Development, Computer Science, Continuous Development, Database Design, Data Engineering, Data Modeling, Data Science, Data Visualization, Design for Maintainability, Machine Learning (ML), Prioritization, Product Management Strategy, Product Requirements, Prototyping, Python (Programming Language), Scalable Architectures, Software Development, Solution Architecture, Solutions Delivery, Stakeholder Relationship Management, Standards Compliance {+ 3 more}
Preferred Skills:
Current Employees apply HERE
Current Contingent Workers apply HERE
US and Puerto Rico Residents Only:
Our company is committed to inclusion, ensuring that candidates can engage in a hiring process that exhibits their true capabilities. Please click here if you need an accommodation during the application or hiring process.
As an Equal Employment Opportunity Employer, we provide equal opportunities to all employees and applicants for employment and prohibit discrimination on the basis of race, color, age, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability status, or other applicable legally protected characteristics. As a federal contractor, we comply with all affirmative action requirements for protected veterans and individuals with disabilities. For more information about personal rights under the U.S. Equal Opportunity Employment laws, visit:
EEOC Know Your Rights
EEOC GINA Supplement
We are proud to be a company that embraces the value of bringing together, talented, and committed people with diverse experiences, perspectives, skills and backgrounds. The fastest way to breakthrough innovation is when people with diverse ideas, broad experiences, backgrounds, and skills come together in an inclusive environment. We encourage our colleagues to respectfully challenge one another’s thinking and approach problems collectively.
Learn more about your rights, including under California, Colorado and other US State Acts
The primary location for this posting is:
USA - New Jersey - Rahway
Where required by law, the compensation range for this role is provided below.
The salary range for the primary location of this role is:
$156,900.00 - $247,000.00
This range reflects the Company's reasonable expectation of the base salary applicable to this role at the time of posting. An employee’s position within the salary range will be based on several factors including, but not limited to relevant education, qualifications, certifications, experience, skills, geographic location, government requirements, and business or organizational needs. The successful candidate will be eligible for annual bonus and long-term incentive, if applicable.
We offer a comprehensive package of benefits. Available benefits include medical, dental, vision healthcare and other insurance benefits (for employee and family), retirement benefits, including 401(k), paid holidays, vacation, and compassionate and sick days. More information about benefits is available at https://jobs.merck.com/us/en/compensation-and-benefits.
Additional location(s): Please note the salary range above applies to the Primary Location of the position. Where a role has other listed locations, different compensation guidelines may apply. You may find the salary ranges for additional locations below. If the salary range is not listed for the location you are applying to, our Talent Acquisition team will provide further information to you relevant to your location.
Additional location(s) Compensation Information:
San Francisco Residents Only: We will consider qualified applicants with arrest and conviction records for employment in compliance with the San Francisco Fair Chance Ordinance
Los Angeles Residents Only: We will consider for employment all qualified applicants, including those with criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance
Search Firm Representatives Please Read Carefully
Merck & Co., Inc., Rahway, NJ, USA, also known as Merck Sharp & Dohme LLC, Rahway, NJ, USA, does not accept unsolicited assistance from search firms for employment opportunities. All CVs / resumes submitted by search firms to any employee at our company without a valid written search agreement in place for this position will be deemed the sole property of our company. No fee will be paid in the event a candidate is hired by our company as a result of an agency referral where no pre-existing agreement is in place. Where agency agreements are in place, introductions are position specific. Please, no phone calls or emails.
Employee Status:
Regular
Relocation:
VISA Sponsorship:
Travel Requirements:
Flexible Work Arrangements:
Hybrid
Shift:
Valid Driving License:
Hazardous Material(s):
Job Posting End Date:
11/4/2026*A job posting is effective until 11:59:59PM on the day BEFORE the listed job posting end date. Please ensure you apply to a job posting no later than the day BEFORE the job posting end date.
Requisition ID: R423510
Salary Context
This $156K-$247K range is above the median for AI/ML Engineer roles in our dataset (median: $178K across 2239 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 11,520 AI roles we're tracking, AI/ML Engineer positions make up 76% of the market. At Merck, 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 $212,040 based on 13,780 positions with disclosed compensation. Director-level AI roles across all categories have a median of $272,250. This role's midpoint ($201K) sits 5% below the category median. Disclosed range: $156K to $247K.
Across all AI roles, the market median is $213,480. Top-quartile compensation starts at $264,000. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($266,050) and AI Engineering Manager ($253,461). By seniority level: Entry: $112,320; Mid: $193,200; Senior: $230,000; Director: $272,250; VP: $235,830.
Merck AI Hiring
Merck has 8 open AI roles right now. They're hiring across AI/ML Engineer. Based in Rahway, NJ, US. Compensation range: $247K - $444K.
Location Context
Across all AI roles, 6% (708 positions) offer remote work, while 10,737 require on-site attendance. Top AI hiring metros: New York (3,257 roles, $221,000 median); San Francisco (2,766 roles, $260,550 median); Los Angeles (1,580 roles, $210,000 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 11,520 open positions tracked in our dataset. By seniority: 140 entry-level, 5,630 mid-level, 4,176 senior, and 1,574 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (708 positions). The remaining 10,737 roles require on-site or hybrid attendance.
The market median for AI roles is $213,480. Top-quartile compensation starts at $264,000. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($266,050 median, 70 roles); AI Engineering Manager ($253,461 median, 58 roles); Research Engineer ($252,000 median, 476 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 11,520 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (8,769), AI Software Engineer (586), AI Product Manager (511). 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 (140) are outnumbered by mid-level (5,630) and senior (4,176) 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 1,574 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (708 positions), with 10,737 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 $213,480. Top-quartile roles start at $264,000, and the 90th percentile reaches $318,400. 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 $266,050 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 (2,267 postings), Aws (1,178 postings), Azure (972 postings), Rag (924 postings), Gcp (715 postings), Pytorch (586 postings), Claude (572 postings), Kubernetes (559 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.