Director, AI & Machine Learning

Director AI & Machine Learning

ABOUT AMGEN

At Amgen if you feel like you are part of something bigger it is because you are. Our shared mission - to serve patients living with serious illnesses - drives all that we do.

Since 1980 we have helped pioneer the world of biotech in our fight against the worlds toughest diseases. With a focus on oncology inflammation general medicine and rare disease we reach millions of patients each year. As a member of the Amgen team you will help make a lasting impact on the lives of patients as we research manufacture and deliver innovative medicines.

Our culture is collaborative innovative and science based. Join us and transform the lives of patients while transforming your career.

ABOUT THE ROLE

Role Description

Lets do this. Lets change the world.

The Director AI & Machine Learning will play a key role in advancing Amgen Researchs AI capabilities by providing technical direction and engineering leadership across strategic initiatives. The role will help accelerate the development and adoption of AI solutions while building a strong reusable technical foundation that can support evolving priorities across the Research organization.

The leader will provide technical leadership and hands-on engineering expertise to advance scalable AI and machine learning capabilities across Amgen Research. This role will guide the design integration and evolution of AI-enabled solutions helping translate scientific and business needs into reliable scalable and maintainable technical capabilities.

The successful candidate combines strong AI/ML and software engineering expertise with technical leadership product thinking and scientific curiosity. You will partner across multidisciplinary teams to guide technical decisions establish engineering best practices evaluate emerging technologies and enable the effective adoption of AI capabilities across a broad portfolio of Research initiatives.

Roles & Responsibilities

• Set AI and ML strategy and roadmap. Develop and guide multi-department AI/ML strategy aligned to R&D clinical medical operations and commercial priorities. Shape and lead the R&D AI/ML roadmap with a focus on shared scientific data and models reusable AI capabilities and scalable end-to-end research workflows. Identify investment opportunities with clear scientific operational and business value.

• Lead advanced ML programs. Sponsor and direct the design validation and scale-up of ML generative AI foundation-model and agentic AI solutions from opportunity framing through production adoption.

• Establish production ML architecture. Drive platform choices modernization roadmaps reusable engineering patterns and quality standards that enable dependable model delivery at scale across multiple departments. Establish scalable architecture patterns that integrate scientific data tools predictive and generative models and AI agents into reusable end-to-end scientific workflows.

• Guide MLOps and data platform strategy. Prioritize investments in data quality lineage experimentation evaluation monitoring model registry release governance and lifecycle operations to reduce delivery time and improve compliance readiness.

• Champion responsible AI and model governance. Ensure AI/ML governance standards are implemented across the portfolio; balance innovation patient impact regulatory expectations security privacy and operational risk through practical controls and review forums.

• Build high-performing teams and capability. Recruit develop and retain strong ML engineering talent; guide senior professionals and create an inclusive culture of technical excellence scientific rigor continuous learning and accountable execution.

• Drive portfolio value and measurable outcomes. Set investment logic success measures and portfolio-level KPIs that demonstrate scientific operational and business impact. Measure the adoption and value of scientific AI capabilities through outcomes such as workflow completion time research productivity result quality user satisfaction and production adoption while managing value risk feasibility adoption cost and speed trade-offs.

• Build strategic alliances and influence decisions. Partner with scientists digital and technology leaders data/platform teams quality legal compliance privacy and information security to plan major changes and integrate AI/ML into real workflows.

• Communicate with executive clarity. Develop clear narratives roadmaps and recommendations that enable senior stakeholders to understand technical options assumptions risks and investment decisions.

We are all different yet we all use our unique contributions to serve patients. The professional we seek is a Director with these qualifications.

Basic Qualifications:

Doctorate degree and 4 years of Director AI & Machine Learning experience
OR
Masters degree and 8 years of Director AI & Machine Learning experience
OR
Bachelors degree and 10 years of Director AI & Machine Learning experience

In addition to meeting at least one of the above requirements you must have at least 4 years experience directly managing people and/or leadership experience leading teams projects programs or directing the allocation or resources. Your managerial experience may run concurrently with the required technical experience referenced above

• AI/ML technical leadership.Expert AI/ML engineering knowledge with a demonstrated record of setting technical and modeling strategy for scientific research applications. Proven ability to evaluate emerging AI/ML methods make consequential architecture and technology decisions and translate scientific needs into reusable scalable AI capabilities and production-grade research workflows.

• Production systems and architecture. Deep hands-on understanding of software engineering and production AI/ML system design including scalable APIs and pipelines cloud platforms model serving evaluation observability and maintainable system architecture that support reusable scientific capabilities and workflows..

• Data MLOps and lifecycle operations. Experience directing reusable data and MLOps capabilities including lineage reproducibility validation monitoring drift detection CI/CD incident response auditability and model retirement.

• Responsible AI in a regulated environment. Ability to implement fit-for-purpose governance validation evidence model documentation risk controls access safeguards and review mechanisms for sensitive or regulated AI/ML applications.

• People and organizational leadership. Demonstrated success building and leading high-performing technical teams developing senior professionals informing resource allocation and guiding advanced programs through major change.

• Strategic stakeholder management. Strong record of building alliances across scientific business and technology functions; partnering with scientists and research workflow owners to translate complex scientific needs into scalable AI/ML solutions; influencing decisions without formal authority; and communicating complex ML strategy to leadership audiences.

• Generative AI and systems thinking. Experience setting strategy for foundation models and enterprise AI adoption balancing innovation compliance platform reuse operating risk workforce enablement and scientific or business value.

Education and Professional Certifications

• Education. Doctorate degree with 10-12 years of relevant experience in computer science machine learning artificial intelligence computational science data science engineering or a related field; OR Bachelors degree with 12-14 years of relevant experience.

• Technical depth. Demonstrated experience with Python and modern ML/deep-learning frameworks (for example PyTorch TensorFlow JAX) along with cloud and data platforms used to deploy AI/ML solutions at scale.

• Certifications. Relevant cloud AI/ML or MLOps certifications (for example AWS Azure Google Cloud Databricks) are a plus.

PREFERRED QUALIFICATIONS

• Agentic AI architectures. Experience designing evaluating and governing agentic AI architectures including tool use orchestration planning memory guardrails human oversight and production monitoring.

• Scientific background. Academic or professional background in chemistry biology biochemistry biophysics computational biology bioinformatics or a related life-science discipline.

• Scientific AI and foundation models. Experience with AI/ML enabled approaches for biological and molecular research including protein structure prediction Protein Language Models (PLMs) biological foundation models molecular design or related computational biology and chemistry applications is a plus.

• Biopharma and regulated domains. Experience applying AI/ML in pharma biotech healthcare or another highly regulated industry including an understanding of privacy consent data provenance quality and compliance expectations.

• Enterprise platform experience. Experience partnering with cloud data engineering security and platform teams to build reusable AI/ML capabilities using Azure Databricks Snowflake or comparable technology ecosystems.

• Scientific and executive communication. Ability to turn technical evidence into concise decision-ready narratives for scientific leaders business leaders and senior executives.

As we work to develop treatments that take care of others we also work to care for your professional and personal growth and well-being. From our competitive benefits to our collaborative culture well support your journey every step of the way.

The expected annual salary range for this role in the U.S. (excluding Puerto Rico) is posted. Actual salary will vary based on several factors including but not limited to relevant skills experience and qualifications.

In addition to the base salary Amgen offers a Total Rewards Plan based on eligibility comprising of health and welfare plans for staff and eligible dependents financial plans with opportunities to save towards retirement or other goals work/life balance and career development opportunities that may include:

• A comprehensive employee benefits package including a Retirement and Savings Plan with generous company contributions group medical dental and vision coverage life and disability insurance and flexible spending accounts
• A discretionary annual bonus program or for field sales representatives a sales-based incentive plan
• Stock-based long-term incentives
• Award-winning time-off plans
• Flexible work models where possible. Refer to the Work Location Type in the job posting to see if this applies.

In any materials you submit you may redact or remove age-identifying information such as age date of birth or dates of school attendance or graduation. You will not be penalized for redacting or removing this information.

Amgen does not have an application deadline for this position; we will continue accepting applications until we receive a sufficient number or select a candidate for the position.

Sponsorship for this role is not guaranteed.

As an organization dedicated to improving the quality of life for people around the world Amgen fosters an inclusive environment of diverse ethical committed and highly accomplished people who respect each other and live the Amgen values to continue advancing science to serve patients. Together we compete in the fight against serious disease.

Amgen is an Equal Opportunity employer and will consider all qualified applicants for employment without regard to race color religion sex sexual orientation gender identity national origin protected veteran status disability status or any other basis protected by applicable law.

We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process to perform essential job functions and to receive other benefits and privileges of employment. Please contact us to request accommodation.

Salary Range