
10,000+ employees
Founded 1980
🏥 Healthcare
🧬 Biotechnology
💊 Pharmaceuticals
💰 $28.5G Post-IPO Debt on 2022-12
Healthcare • Biotechnology • Pharmaceuticals
Amgen is a global leader in biotechnology, focusing on the development and commercialization of innovative medicines made from living cells. The company aims to treat serious illnesses, often targeting diseases with limited therapeutic options. Amgen emphasizes scientific innovation and is committed to ethical research, patient safety, and environmental sustainability. It actively engages in clinical trials and is known for its contributions to the fields of cancer treatment and obesity management among others.
🔥 3 minutes ago
🇺🇸 United States – Remote
💵 $242.5k - $328.1k / year
⏰ Full Time
🔴 Lead
🤖 Machine Learning Engineer
🦅 H1B Visa Sponsor
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10,000+ employees
Founded 1980
🏥 Healthcare
🧬 Biotechnology
💊 Pharmaceuticals
💰 $28.5G Post-IPO Debt on 2022-12
Healthcare • Biotechnology • Pharmaceuticals
Amgen is a global leader in biotechnology, focusing on the development and commercialization of innovative medicines made from living cells. The company aims to treat serious illnesses, often targeting diseases with limited therapeutic options. Amgen emphasizes scientific innovation and is committed to ethical research, patient safety, and environmental sustainability. It actively engages in clinical trials and is known for its contributions to the fields of cancer treatment and obesity management among others.
• Set AI and ML strategy and roadmap across R&D, clinical, medical, operations, and commercial priorities • Lead advanced ML, generative AI, foundation-model, and agentic AI programs from opportunity framing through production adoption • Establish production ML architecture, platform choices, modernization roadmaps, reusable engineering patterns, and quality standards • Guide MLOps and data platform strategy, including data quality, lineage, experimentation, evaluation, monitoring, model registry, release governance, and lifecycle operations • Champion responsible AI and model governance across the portfolio • Recruit, develop, and retain ML engineering talent and build a culture of technical excellence • Define investment logic, success measures, and portfolio-level KPIs • Measure adoption and value of scientific AI capabilities • Partner with scientists, technology leaders, data/platform teams, quality, legal, compliance, privacy, and information security • Develop clear technical narratives, roadmaps, recommendations, and investment decisions for senior stakeholders
• Doctorate degree and 4 years of Director, AI & Machine Learning experience, OR Master’s degree and 8 years of such experience, OR Bachelor’s degree and 10 years of such experience • At least 4 years of direct people management and/or leadership experience leading teams, projects, programs, or resource allocation • Expert AI/ML engineering knowledge and technical strategy experience for scientific research applications • Deep hands-on experience with software engineering and production AI/ML system design • Experience with scalable APIs, pipelines, cloud platforms, model serving, evaluation, observability, and maintainable architecture • Experience directing data and MLOps capabilities, including lineage, reproducibility, validation, monitoring, drift detection, CI/CD, incident response, auditability, and model retirement • Ability to implement responsible AI governance, validation evidence, model documentation, risk controls, access safeguards, and review mechanisms • Demonstrated success building and leading high-performing technical teams • Strong stakeholder management and cross-functional alliance-building experience • Experience setting strategy for foundation models and enterprise AI adoption • Demonstrated experience with Python and modern ML/deep-learning frameworks such as PyTorch, TensorFlow, or JAX • Experience with cloud and data platforms used to deploy AI/ML solutions at scale
• Retirement and Savings Plan with generous company contributions • Group medical, dental and vision coverage • Life and disability insurance • Flexible spending accounts • Discretionary annual bonus program • Stock-based long-term incentives • Award-winning time-off plans • Flexible work models where possible • Career development opportunities • Work/life balance support
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