Interested in this AI/ML Engineer role at Rhythm Pharmaceuticals?
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About This Role
Company Overview
Rhythm is a global, commercial-stage biopharmaceutical company committed to transforming the lives of patients and their families living with rare neuroendocrine diseases. We develop medicines for previously untreatable or undertreated diseases and provide meaningful support for healthcare providers and patients and their families. We recognize the courage it takes for patients and their caregivers to begin their journey of advocacy to find the answers they need. Their courage inspires us to challenge convention, ask bold questions and seek answers for them. Every day, we strive for excellence through our willingness to adapt, learn, and our tenacity to overcome barriers, together.
Opportunity Overview
Reporting to the Senior VP, Head of Information Technology and Data Security, this position is responsible for our AI strategy, innovation and value creation in the enterprise. The role is focused on driving AI transformation, improving enterprise AI literacy, creating AI strategies and evolving AI capabilities, overall data strategies and transformation, implementing appropriate operating models, and implementing governance practices that reduce risk and increase business value.
Responsibilities and Duties:
- Establishes an AI and data strategy and organization that aligns with the company’s overarching enterprise vision, including goal setting and measuring AI initiatives.
- Work closely with all functional and regional leaders to understand our business and shape our artificial intelligence strategy to accelerate AI-driven innovation and transformation. This includes groups such as the Executive Leadership Team, AI Working Committee and the Senior Management Team.
- Work closely with all functional and regional leaders to understand and shape our data analytics strategy especially in areas where no data analytics capability currently exists.
- Fosters collaboration and bridges departmental gaps to develop cross-organizational and functional alignment in accordance with the enterprise AI vision. Establishes an internal and external AI ecosystem, building working relationships with vendors, partners and other external stakeholders.
- Defines the operating model and delivery capabilities for AI initiatives, overseeing the development and execution of advanced AI products and solutions, ensuring their scalable and seamless integration across the organization.
- Create a consistent innovation pipeline and foster an innovation culture, identifying opportunities that grow business opportunities, capabilities and solutions in the scope defined.
- Oversees the AI technology stack and makes recommendations for cross functional technology tools and platforms.
- Manages the AI portfolio and budget for AI initiatives, overseeing the allocation of resources for AI.
- Evolve AI policies and governance programs to address AI’s regulatory and compliance requirements.
- Fosters and cultivates AI literacy across the enterprise, leading transformation efforts and developing change management programs.
- Empower data analytics at an enterprise level, enabling Rhythm leadership further visibility and insights when assessing company performance
- Acts as thought leader and subject matter expert on emerging AI & Analytics trends and technologies.
- Be able to work in a ‘hands on’ capacity as needed and appropriate
Qualifications and Skills:
- 10+ years’ experience working in information technology business application functions
- 5+ years’ experience as of active IT Business Partner for business functional areas – experience in Life Sciences is a plus
- 5+ years’ experience of data analytics in information-intensive industries or digitally advanced enterprises; Life Sciences experiences are a plus.
- 3+ years of AI experience in information-intensive industries or digitally advanced enterprises; Life Sciences experiences are a plus
- Experience fostering enterprise change and leading technology-led transformation programs.
- Experience working in collaboration with Senior Leadership levels
- Ability to work independently and have strong ability to influence outcomes
- Strong vendor management skills; experience and knowledge of available vendors in the IT space
- Strong experience in customer communications to ensure alignment of priorities and activities
- Experience in people management is required in managing vendors/contractors and potentially employees as Rhythm grows.
- Broad, state-of-the-art technology awareness that can be applied creatively to business problems and opportunities
- Expertise in investigating, negotiating and selecting outside services and technology
*This role is based out of our corporate office in Boston, Massachusetts. Rhythm operates in a hybrid-work model. Candidates applying must be willing and able to be in the Boston office in coordination with their department and business needs.**This role may involve some travel.*
*The expected salary range for this position is $182,000-$275,000. Actual pay will be determined based on experience, level, qualifications, geographic location, and other job-related factors permitted by law. A discretionary annual bonus may be available based on individual and company performance. This role may be eligible for benefits and other compensation such as restricted stock units.*
*More about Rhythm*
*We are a dynamic and growing global team spanning more than a dozen countries. At Rhythm we are dedicated to transforming the lives of patients living with rare neuroendocrine diseases by rapidly advancing care and precision medicines that address the root cause.* *Our team is passionate about expanding access to reach more patients and developing novel therapies for other rare neuroendocrine diseases, including congenital hyperinsulinism.*
*At Rhythm our core values are:*
- *We are committed to advancing scientific understanding to improve patients’ lives*
- *We are inspired to tackle tough challenges and have the courage to ask bold questions*
- *We are eager to learn and adapt*
- *We believe collaboration and ownership are foundational for our success*
- *We value the unique contribution each individual brings to furthering our mission*
*Rhythm is an equal employment opportunity employer and does not discriminate against any applicant because of race, creed, color, age, national origin, ancestry, religion, gender, sexual orientation, disability, genetic information, veteran status, military status, application for military service, or any other class protected by state or federal law.*
*Headquartered in Boston, Rhythm is proud to have been named one of the* *Top Places to Work* *in Massachusetts.*
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Salary Context
This $182K-$275K range is above the 75th percentile for AI/ML Engineer roles in our dataset (median: $170K across 217 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 37,339 AI roles we're tracking, AI/ML Engineer positions make up 91% of the market. At Rhythm Pharmaceuticals, 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 $154,000 based on 8,743 positions with disclosed compensation. Director-level AI roles across all categories have a median of $230,600. This role's midpoint ($228K) sits 48% above the category median. Disclosed range: $182K to $275K.
Across all AI roles, the market median is $190,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $300,688. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Safety ($274,200). By seniority level: Entry: $85,000; Mid: $147,000; Senior: $225,000; Director: $230,600; VP: $248,357.
Rhythm Pharmaceuticals AI Hiring
Rhythm Pharmaceuticals has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Boston, MA, US. Compensation range: $275K - $275K.
Location Context
AI roles in Boston pay a median of $210,300 across 352 tracked positions. That's 11% 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 37,339 open positions tracked in our dataset. By seniority: 3,672 entry-level, 23,272 mid-level, 7,048 senior, and 3,347 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (2,732 positions). The remaining 34,484 roles require on-site or hybrid attendance.
The market median for AI roles is $190,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $300,688. Highest-paying categories: AI Engineering Manager ($293,500 median, 21 roles); AI Safety ($274,200 median, 24 roles); Research Engineer ($260,000 median, 264 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 37,339 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (33,926), AI Software Engineer (823), AI Product Manager (805). 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 (3,672) are outnumbered by mid-level (23,272) and senior (7,048) 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 3,347 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 7% of all AI roles (2,732 positions), with 34,484 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 $190,000. Top-quartile roles start at $244,000, and the 90th percentile reaches $300,688. 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 $145,600. 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: Rag (23,721 postings), Aws (12,486 postings), Rust (10,785 postings), Python (5,564 postings), Azure (3,616 postings), Gcp (3,032 postings), Prompt Engineering (2,112 postings), Kubernetes (1,713 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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