Alnylam Pharmaceuticals
Senior Director, AI and Analytics
Alnylam Pharmaceuticals, Cambridge, Massachusetts, us, 02140
Overview
We are seeking a Senior Director, AI and Analytics with a passion for architecting solutions, building systems, and delivering real business impact through hands‑on contribution. As Senior Director, you will own the enterprise AI capability, leading a small, high‑caliber team while staying actively engaged in solving our most complex technical challenges. This role blends strategic leadership with meaningful hands‑on work, with approximately 10‑20% of your time dedicated to building, reviewing, and advancing production‑grade AI/ML systems. This is a role for a deeply technical leader who enjoys staying close to the work. You’ll thrive here if you’re excited to design and deploy modern ML solutions, collaborate closely with engineers, and regularly engage with Python and frameworks like PyTorch as part of your day‑to‑day leadership.
What You’ll Do \ Senior Director will own the enterprise AI capability, leading the enterprise AI strategy, designing alignment, and overseeing the AI strategy across R&D, clinical, manufacturing, and commercial. You’ll dedicate 10‑20% of your time to building, reviewing, and advancing production‑grade AI/ML systems, ensuring that the most complex technical challenges are solved. You’ll be a deeply technical leader who enjoys staying close to the work, designing and deploying modern ML solutions, collaborating closely with engineers, and regularly engaging with Python and frameworks like PyTorch as part of your day‑to‑day leadership.
AI Strategy & Technical Leadership
Define and execute enterprise AI strategy across R&D, clinical, manufacturing, and commercial
Architect end‑to‑end AI/ML solutions from ideation through production
Establish technical standards and governance for regulated environments
Lead evaluation of emerging AI technologies (LLMs, generative AI, foundation models)
Hands‑On Engineering
Architect and implement production ML systems using modern MLOps practices
Write production Python code for ML pipelines, model training, and inference
Build/deploy models using PyTorch, TensorFlow, scikit‑learn on AWS SageMaker or Databricks ML
Own the MLOps stack and tackle complex technical challenges directly
Team Leadership
Build and mentor 1‑3 highly skilled AI engineers
Foster experimentation, scientific rigor, and continuous learning
Recruit world‑class talent; lead from the front on hardest problems
Business Partnership
Partner with R&D, Clinical Ops, Manufacturing, and Commercial to translate challenges into AI solutions
Communicate AI concepts and trade‑offs to executive stakeholders
Drive adoption and measurable ROI across the organization
AI Education & Community
Lead AI education initiatives across the organization—democratizing AI knowledge at all levels
Regularly explore and demo new AI capabilities and technologies to keep the broader community engaged and skills sharp
Foster a culture of AI literacy and experimentation enterprise‑wide
Strategic Vendor Partnerships
Build and maintain indirect relationships with key AI platform partners including Google, Anthropic, Microsoft, and other leading vendors
Leverage vendor partnerships for early access to capabilities, technical support, and strategic roadmap alignment
Serve as primary technical liaison for AI vendor engagements and evaluations
Requirements
10+ years building production AI/ML systems; 5+ years in leadership
Deep ML expertise: supervised/unsupervised learning, deep learning, NLP, computer vision, time series, causal inference
Expert Python with PyTorch, TensorFlow, scikit‑learn, XGBoost
MLOps experience: MLflow, Kubeflow, SageMaker, Databricks ML
Strong software engineering: Git, CI/CD, Docker/Kubernetes, API development
LLM/generative AI experience (GPT, Claude, Llama)
Modern data platforms: Snowflake, Databricks, Airflow, dbt, Spark
AWS expertise preferred
Business & Leadership (Required)
5+ years in biotech, pharma, or data‑intensive industry applying AI at scale
AI domain knowledge in at least one area: drug discovery, clinical trials, manufacturing optimization, or commercial analytics
Experience in regulated environments
5+ years leading AI/ML teams with hands‑on technical mentorship
Track record translating business problems into ML solutions with measurable impact
Matrix organization experience; comfortable with influence over authority
At Alnylam, we commit to an inclusive recruitment process and equal employment opportunity. We are dedicated to building an environment where employees can feel that they belong, can bring their authentic selves to work, and achieve to their full potential. By empowering employees to embrace their unique differences at work, our business grows stronger with advanced and original thinking, allowing us to bring groundbreaking medicines to patients.
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What You’ll Do \ Senior Director will own the enterprise AI capability, leading the enterprise AI strategy, designing alignment, and overseeing the AI strategy across R&D, clinical, manufacturing, and commercial. You’ll dedicate 10‑20% of your time to building, reviewing, and advancing production‑grade AI/ML systems, ensuring that the most complex technical challenges are solved. You’ll be a deeply technical leader who enjoys staying close to the work, designing and deploying modern ML solutions, collaborating closely with engineers, and regularly engaging with Python and frameworks like PyTorch as part of your day‑to‑day leadership.
AI Strategy & Technical Leadership
Define and execute enterprise AI strategy across R&D, clinical, manufacturing, and commercial
Architect end‑to‑end AI/ML solutions from ideation through production
Establish technical standards and governance for regulated environments
Lead evaluation of emerging AI technologies (LLMs, generative AI, foundation models)
Hands‑On Engineering
Architect and implement production ML systems using modern MLOps practices
Write production Python code for ML pipelines, model training, and inference
Build/deploy models using PyTorch, TensorFlow, scikit‑learn on AWS SageMaker or Databricks ML
Own the MLOps stack and tackle complex technical challenges directly
Team Leadership
Build and mentor 1‑3 highly skilled AI engineers
Foster experimentation, scientific rigor, and continuous learning
Recruit world‑class talent; lead from the front on hardest problems
Business Partnership
Partner with R&D, Clinical Ops, Manufacturing, and Commercial to translate challenges into AI solutions
Communicate AI concepts and trade‑offs to executive stakeholders
Drive adoption and measurable ROI across the organization
AI Education & Community
Lead AI education initiatives across the organization—democratizing AI knowledge at all levels
Regularly explore and demo new AI capabilities and technologies to keep the broader community engaged and skills sharp
Foster a culture of AI literacy and experimentation enterprise‑wide
Strategic Vendor Partnerships
Build and maintain indirect relationships with key AI platform partners including Google, Anthropic, Microsoft, and other leading vendors
Leverage vendor partnerships for early access to capabilities, technical support, and strategic roadmap alignment
Serve as primary technical liaison for AI vendor engagements and evaluations
Requirements
10+ years building production AI/ML systems; 5+ years in leadership
Deep ML expertise: supervised/unsupervised learning, deep learning, NLP, computer vision, time series, causal inference
Expert Python with PyTorch, TensorFlow, scikit‑learn, XGBoost
MLOps experience: MLflow, Kubeflow, SageMaker, Databricks ML
Strong software engineering: Git, CI/CD, Docker/Kubernetes, API development
LLM/generative AI experience (GPT, Claude, Llama)
Modern data platforms: Snowflake, Databricks, Airflow, dbt, Spark
AWS expertise preferred
Business & Leadership (Required)
5+ years in biotech, pharma, or data‑intensive industry applying AI at scale
AI domain knowledge in at least one area: drug discovery, clinical trials, manufacturing optimization, or commercial analytics
Experience in regulated environments
5+ years leading AI/ML teams with hands‑on technical mentorship
Track record translating business problems into ML solutions with measurable impact
Matrix organization experience; comfortable with influence over authority
At Alnylam, we commit to an inclusive recruitment process and equal employment opportunity. We are dedicated to building an environment where employees can feel that they belong, can bring their authentic selves to work, and achieve to their full potential. By empowering employees to embrace their unique differences at work, our business grows stronger with advanced and original thinking, allowing us to bring groundbreaking medicines to patients.
#J-18808-Ljbffr