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About This Role
The Role
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Moderna is seeking a Senior AI Engineer in Cambridge, MA/ Warsaw, Poland to provide deep technical leadership for the design, implementation, and operation of AI software platforms and Cloud\-based deployment patterns for Supply Chain and enterprise Digital. This is a senior individual contributor role that sets architecture, codes critical components, establishes engineering standards, and mentors engineers while partnering closely with product and business leaders.
You will own end\-to\-end application architecture and delivery strategy for AI and data products: lakehouse patterns, Unity Catalog governance, CI/CD and release automation, MLflow model lifecycle, feature/data product packaging, model serving, vector search, observability, cost/performance optimization, and validated releases for GxP use cases. The role requires demonstrated experience shipping scalable AI/ML/GenAI systems, APIs, and data applications in enterprise environments.
Here's What You’ll Do
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- Define the technical strategy and reference architecture for AI software delivery, GenAI applications, agentic workflows, ML services, and cloud\-based data/AI platforms.
- Lead end\-to\-end Cloud deployment standards across development, test, validation, and production environments, including workspace architecture, Delta Lake/Lakehouse design, Unity Catalog, Workflows/Jobs, MLflow, model serving, deployment automation, observability, and access governance.
- Build and review critical software components, APIs, orchestration patterns, model\-serving interfaces, reusable libraries, and platform accelerators that enable teams to move AI prototypes into production reliably.
- Establish engineering practices for AI/ML/LLMOps, including automated testing, CI/CD, infrastructure\-as\-code, release management, model and prompt versioning, evaluation, monitoring, incident response, and rollback.
- Guide integration of SAP and enterprise data sources into trusted data products, feature pipelines, semantic layers, and decision\-support services for Supply Chain, Quality, Manufacturing, Finance, and Digital stakeholders.
- Partner with product owners, architects, cybersecurity, quality, validation, and infrastructure teams to ensure solutions meet business outcomes, security expectations, GxP requirements, and enterprise architecture standards.
- Coach and mentor engineers across regions, raise the quality of design reviews and code reviews, and help build a practical AI/Data/Automation Center of Excellence with reusable standards and assets.
- Improve platform reliability, performance, cost efficiency, data quality, and developer experience through metrics, architectural guardrails, operational playbooks, and continuous feedback from users and support teams.
Here’s What You’ll Need (Basic Qualifications)
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- Bachelor's or Master's degree in Computer Science, AI, Data Science, Engineering, Applied Mathematics, Physics, or a related technical field; equivalent deep technical experience will be considered.
- 7\+ years of software, data, or AI engineering experience, including 4\+ years delivering production ML, GenAI, analytics, automation, or data\-intensive systems.
- Expert proficiency with Python and SQL, strong software architecture fundamentals, and experience with at least one additional language such as Java, Scala, or TypeScript.
- Hands\-on frontend engineering experience with TypeScript/JavaScript and a modern framework such as React, Angular, Vue, or Svelte, including reusable components, state management, forms, charts, browser fundamentals, accessibility, and responsive design.
- Hands\-on backend engineering experience designing production APIs and services using Python, Node.js, Java, Scala, or comparable technologies, including REST/GraphQL patterns, service boundaries, authentication, authorization, testing, observability, and production debugging.
- Demonstrated experience architecting and operating LLM/GenAI systems, including RAG, agents/tool use, embeddings/vector search, model and prompt evaluation, guardrails, monitoring, and human\-in\-the\-loop controls.
- Strong background in cloud architecture on AWS, Azure, or GCP, including IAM, networking, secrets management, CI/CD, infrastructure\-as\-code, and production support models.
- Experience designing secure, compliant, auditable systems in regulated environments, with practical understanding of GxP, data integrity, validation documentation, and change control.
Here’s What You’ll Bring to the Table (Preferred Qualifications)
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- Experience in life sciences, pharmaceutical manufacturing, supply chain, quality, or another regulated operational domain.
- Experience with SAP\-centric supply chain data and integration patterns, including SAP ECC/S/4HANA, IBP, MM, PP, QM, SD, EWM/WM, MDG, BTP, or related analytics enablement.
- Advanced experience with Databricks Asset Bundles, Terraform or infrastructure\-as\-code, Databricks SQL, Feature Engineering/Feature Store, Vector Search, model monitoring, and lakehouse governance patterns.
- Applied expertise in forecasting, optimization, simulation, anomaly detection, scheduling, inventory, logistics, or decision intelligence methods.
Track record of mentoring senior engineers, shaping engineering communities of practice, and influencing technical direction across global teams.
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Pay \& Benefits
At Moderna, we believe that when you feel your best, you can do your best work. That’s why our benefits and well\-being resources are designed to support you—at work, at home, and everywhere in between.
- Competitive healthcare, plus voluntary benefit programs to support your unique needs
- A holistic approach to well\-being, with access to fitness, mindfulness, and mental health support
- Family planning benefits, including fertility, adoption, and surrogacy support
- Generous paid time off, including vacation, volunteer days, sabbatical, global recharge days, and a discretionary year\-end shutdown
- Savings and investments to help you plan for the future
- Location\-specific perks and extras
The salary range for this role is $145,900\.00 \- $234,200\.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 individual’s position within the salary range will be based on several factors including, but not limited to, specific competencies, relevant education, qualifications, certifications, experience, skills, performance, and business or organizational needs.\&\#xa;\&\#xa;The successful candidate may be eligible for an annual discretionary bonus, other incentive compensation, or equity award, subject to company plan eligibility criteria and individual performance.
About Moderna
Since our founding in 2010, we have aspired to build the leading mRNA technology platform, the infrastructure to reimagine how medicines are created and delivered, and a world\-class team. We believe in giving our people a platform to change medicine and an opportunity to change the world.
By living our mission, values, and mindsets every day, our people are the driving force behind our scientific progress and our culture. Together, we are creating a culture of belonging and building an organization that cares deeply for our patients, our employees, the environment, and our communities.
We are proud to have been recognized as a Science Magazine Top Biopharma Employer, a Fast Company Best Workplace for Innovators, and a Great Place to Work in the U.S.
If you want to make a difference and join a team that is changing the future of medicine, we invite you to visit modernatx.com/careers to learn more about our current opportunities.
Our Working Model
As we build our company, we have always believed an in\-person culture is critical to our success. Moderna champions the significant benefits of in\-office collaboration by embracing a 70/30 work model. This 70% in\-office structure helps to foster a culture rich in innovation, teamwork, and direct mentorship. Join us in shaping a world where every interaction is an opportunity to learn, contribute, and make a meaningful impact.
Moderna is a smoke\-free, alcohol\-free, and drug\-free work environment.
Equal Opportunities
Moderna is committed to equal employment opportunity and non\-discrimination for all employees and qualified applicants without regard to a person's race, color, sex, gender identity or expression, age, religion, national origin, ancestry or citizenship, ethnicity, disability, military or protected veteran status, genetic information, sexual orientation, marital or familial status, or any other personal characteristic protected under applicable law. Moderna is a place where everyone can grow. If you meet the Basic Qualifications for the role and you would be excited to contribute to our mission every day, please apply!
Moderna is an E\-Verify Employer in the United States. We consider qualified applicants regardless of criminal histories, consistent with legal requirements.
Accommodations
We’re focused on attracting, retaining, developing, and advancing our employees. By cultivating a workplace that values diverse experiences, backgrounds, and ideas, we create an environment where every employee can contribute their best.
Moderna is committed to offering reasonable accommodations to qualified job applicants with disabilities. Any applicant requiring an accommodation in connection with the hiring process and/or to perform the essential functions of the position for which the applicant has applied should contact the Accommodations team at [email protected] .
Export Control Notice\&\#xa;This position may involve access to technology or data that is subject to U.S. export control laws, including the Export Administration Regulations (EAR). As such, employment is contingent upon the applicant’s ability to access export\-controlled information in accordance with U.S. law. Due to the nature of the work and regulatory requirements, only individuals who qualify as U.S. persons (citizens, permanent residents, asylees, or refugees) are eligible for this position. For this role Moderna is unable to sponsor non\-U.S. persons to apply for an export control license.\&\#xa;\#LI\-KH1
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Salary Context
This $145K-$234K range is above the median for AI/ML Engineer roles in our dataset (median: $180K across 1841 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 3,708 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At Moderna, 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 $218,750 based on 3,817 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $230,000. This role's midpoint ($190K) sits 13% below the category median. Disclosed range: $145K to $234K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
Moderna AI Hiring
Moderna has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Cambridge, MA, US. Compensation range: $234K - $234K.
Location Context
Across all AI roles, 14% (508 positions) offer remote work, while 3,180 require on-site attendance. Top AI hiring metros: New York (1,045 roles, $220,000 median); San Francisco (810 roles, $277,088 median); Los Angeles (397 roles, $215,000 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 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 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 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). 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 (102) are outnumbered by mid-level (1,705) and senior (1,469) 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 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 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 $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. 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 $300,000 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 (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 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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