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About This Role
Job Description
We aspire to be the premier research\-intensive biopharmaceutical company. We're at the forefront of research to deliver innovative health solutions that advance the prevention and treatment of diseases in people and animals. Join our team and contribute to our mission of using the power of leading\-edge science to save and improve lives around the world.
Responsibilities
- Oversee and coordinate clinical database activities across multiple clinical programs, including review of eCRFs, edit check specifications, and database development
- Ensure adherence to clinical database standards, SOPs, and process guidelines
- Plan and manage timelines for database deliverables; identify and escalate risks appropriately
- Interface with study teams and stakeholders to integrate requirements into deliverables
- Align with CDS leadership to ensure consistency of technical strategies and execution
- Lead and participate in improvement initiatives, including task forces, automations, and exploration of emerging digital capabilities (e.g., advanced analytics, AI\-enabled tools)
- Contribute strategies and innovative solutions to enhance processes and increase productivity, including the appropriate use of automation and data\-driven approaches
- Support testing and evaluation of new systems, tools, and capabilities
- Coordinate and contribute to CDS technical initiatives that improve efficiency and scalability
- Serve as subject matter expert (SME) in clinical database and EDC activities, including database development and data integration
- Increase functional effectiveness by supporting efforts to simplify and standardize processes, including identifying opportunities for automation and improved data workflows
- Provide technical guidance, best practices, and knowledge sharing across the team and broader organization
- Provide oversight and guidance to Clinical Database Developers
- Support recruitment, onboarding, mentoring, and technical development of team members
- Contribute to performance management input and capability development planning
- Lead or contribute to functional and cross\-functional meetings
- Communicate clinical database processes, requirements, and risks effectively to stakeholders and vendors
- Support alignment, decision\-making, and continuous improvement efforts
Qualifications
*Required*
- Bachelor’s degree in Computer Science or related discipline (or equivalent experience)
- Minimum of 5 years of experience in pharmaceutical clinical research / data management
- Experience in clinical database development, EDC systems, and data management processes
- Strong understanding of clinical database design, eCRFs, edit checks, and data collection frameworks
- Knowledge of EDC and data management systems
- Familiarity with clinical data standards, regulatory requirements, and GxP/ICH guidelines
- Understanding of end\-to\-end clinical data lifecycle and data cleaning processes
- Strong stakeholder management and cross\-functional collaboration skills
- Effective communication and ability to translate technical concepts clearly
- Strong organizational, prioritization, and multi\-project management skills
- Ability to work independently and manage competing priorities
- High attention to detail and commitment to quality and compliance
*Preferred*
- Experience in technology implementation and/or system evaluation
- Exposure to automation tools, data workflows, and process optimization approaches
- Demonstrated awareness of emerging digital capabilities, including automation and AI, and their potential application within clinical data management
- Ability to identify opportunities to improve processes using data\-driven and automation approaches, while ensuring compliance within regulated environments
Required Skills:
Adaptability, Adaptability, Artificial Intelligence (AI), Automation, Clinical Database Programming, Clinical Data Management, Clinical Data Standards, Clinical Development, Clinical Trials Operations, Data Analysis, Data Engineering, Data Quality Assurance, Data Reporting, Data Validation, Detail\-Oriented, Drug Discovery Process, Escalation Management, FDA Regulations, Good Clinical Data Management Practice (GCDMP), Good Clinical Practice (GCP), Integration Architecture, Interpersonal Relationships, Mentoring Staff, Project Management Tools, Release Management {\+ 4 more}Preferred Skills:
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:
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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 salary range for this role is
$142,400\.00 \- $224,100\.00
This is the lowest to highest salary we in good faith believe we would pay for this role at the time of this 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.
You can apply for this role through https://jobs.merck.com/us/en (or via the Workday Jobs Hub if you are a current employee). The application deadline for this position is stated on this posting.
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:
RegularRelocation:
No relocationVISA Sponsorship:
NoTravel Requirements:
10%Flexible Work Arrangements:
HybridShift:
Not IndicatedValid Driving License:
NoHazardous Material(s):
n/aJob Posting End Date:
06/20/2026* 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:R399669
Salary Context
This $142K-$224K range is above the median for AI/ML Engineer roles in our dataset (median: $180K across 1937 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 3,823 AI roles we're tracking, AI/ML Engineer positions make up 69% 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 $181,170 based on 12,692 positions with disclosed compensation. Director-level AI roles across all categories have a median of $247,800. Disclosed range: $142K to $224K.
Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($275,000) and AI Safety ($274,200). By seniority level: Entry: $97,880; Mid: $165,000; Senior: $227,400; Director: $247,800; VP: $250,000.
Merck AI Hiring
Merck has 3 open AI roles right now. They're hiring across AI/ML Engineer. Positions span West Point, PA, US, Rahway, NJ, US. Compensation range: $86K - $224K.
Location Context
Across all AI roles, 15% (590 positions) offer remote work, while 3,217 require on-site attendance. Top AI hiring metros: New York (2,643 roles, $211,000 median); San Francisco (2,168 roles, $253,000 median); Los Angeles (1,792 roles, $191,580 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 3,823 open positions tracked in our dataset. By seniority: 112 entry-level, 1,798 mid-level, 1,516 senior, and 397 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (590 positions). The remaining 3,217 roles require on-site or hybrid attendance.
The market median for AI roles is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($275,000 median, 41 roles); AI Safety ($274,200 median, 55 roles); Research Engineer ($260,000 median, 434 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 3,823 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,629), Data Scientist (322), AI Software Engineer (279). 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 (112) are outnumbered by mid-level (1,798) and senior (1,516) 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 397 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (590 positions), with 3,217 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 $200,100. Top-quartile roles start at $253,500, 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 $275,000 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 (1,979 postings), Aws (1,190 postings), Azure (899 postings), Rag (839 postings), Gcp (726 postings), Pytorch (595 postings), Prompt Engineering (595 postings), Claude (540 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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