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About This Role
Job Description
Be a part of the legacy: Postdoctoral Research Fellow Program
Our Research Laboratories’ Postdoctoral Research Fellow Program aims to be a best\-in\-industry program for industrial postdoctoral researchers, designed to provide you with an academic focus in a commercial environment. With the resources, reach, and expertise of a large pharmaceutical company, postdoctoral researchers will be positioned to excel in an institution committed to breakthrough innovation in research and discovery.
Position Overview:
This position is in the vaccine modeling team of the Health Economic and Decision Sciences (HEDS) department withing Biostatistics and Research Decision Sciences (BARDS) at our Research Laboratories. BARDS HEDS provides strategic and analytic modeling expertise to measure and quantify the value of our company's products.
As part of an agile team, the fellow will develop and support a seamless mechanism of coordination and collaboration in a dynamic area of interdisciplinary research. Collaboration with modeling scientists, data scientists, IT partners, subject matter experts and strategically leveraging generative AI to automate model extraction and facilitate rapid, intelligent adaptation across diverse settings, this project will profoundly enhance model transparency, dramatically accelerate deployment, and improve consistency in global health decision\-making. This innovative approach promises to transform the efficiency and impact of health economic evaluations in infectious disease preparedness and response.
At BARDS, we value diversity and inclusion in our working environment where employees are enabled to develop and contribute.
Responsibilities include but are not limited to:
Reporting under a Senior Director within the Vaccines team within HEDS, the fellow is expected to:
- Build a robust corpus of health economic infectious disease models using AI\-assisted systematic review techniques,
- Utilize advanced LLMs to precisely extract infectious disease model type, structure (states, transitions), and parameters (costs, utilities, probabilities),
- Implement an intelligent AI reasoning layer to evaluate consistency, completeness, and scientific validity across extracted models,
- Employ generative AI to propose new model structures, dynamically guided by disease\-specific needs and prior evidence,
- Apply the developed pipeline to critical case studies (e.g., RSV vaccine modeling) and rigorously compare AI\-generated models with existing approaches,
- Develop excellent working relationships within partner across our Research Laboratories; ensure effective cross\-functional collaboration across teams,
- Collaborate externally and solicit input from appropriate stakeholders and adopt latest techniques from relevant published literature, and
- Disseminate key research findings/methodology via scientific presentations at congresses and publications in scientific journals.
Education Minimum Requirement:
Candidates should currently hold a PhD OR will receive a PhD by start of employment in Computer Science, Mathematics, Statistics, or a closely\-related quantitative field.
Required Experience and Skills:
- Previous experience with large language models (LLMs), natural language processing (NLP), or machine learning,
- Strong programming skills in Python and/or C\+\+, with experience in model fitting, simulation, and data extraction workflows,
- Previous experience working on interdisciplinary research projects and/or working within interdisciplinary teams,
- Ability to gather, organize, and synthesize complex information in order to draw conclusions and make recommendations,
- Strong creative problem solving skills,
- Strong interpersonal, networking, presentation, and communication skills, and
- Ability to communicate effectively in English in both verbal and written formats.
Preferred Experience and Skills:
- Experience in prompt engineering, fine\-tuning, or evaluating large language models, and
- Previous experience of health economic modeling and cost\-effectiveness analysis for infectious disease.
postdoctoralopportunities
Under New York City, Colorado State, Washington State, and California State law, the Company is required to provide a reasonable estimate of the salary range for this job. Final determinations with respect to salary will take into account a number of factors, which may include, but not be limited to the primary work location and the chosen candidate’s relevant skills, experience, and education.
Expected salary range:
$75,000\.00\-$86,000\.00
Available benefits include bonus eligibility, health care and other insurance benefits (for employee and family), retirement benefits, paid holidays, vacation, and sick days. For Washington State Jobs, a summary of benefits is listed here.
Required Skills:
Adaptability, Adaptability, Analytical Chemistry, Cell Culture Techniques, Computational Biology, Computer Science, Data Analysis, Generative AI, Global Health, Health Economics, Immunoassays, Infectious Disease, Information Technology Consulting, Interdisciplinary Research, In Vivo Mouse Models, Large Language Models (LLMs), Mathematical Biology, Molecular Biology, Natural Language Processing (NLP), Programming Languages, Prompt Engineering, Report Writing, Scientific Presentations, Scientific Writing, siRNA Knockdown {\+ 1 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:
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
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:
DomesticVISA Sponsorship:
YesTravel Requirements:
10%Flexible Work Arrangements:
HybridShift:
Not IndicatedValid Driving License:
NoHazardous Material(s):
n/aJob Posting End Date:
06/27/2026* 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:R402279
Salary Context
This $75K-$86K range is in the lower quartile 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. Entry-level AI roles across all categories have a median of $97,880. This role's midpoint ($80K) sits 56% below the category median. Disclosed range: $75K to $86K.
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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