Engineering Manager - Machine Learning

For our client, we are seeking a Engineering Manager - Machine Learning to join the team of a leader in the Pharmaceuticals & Biotech space. This role will lead work at the intersection of data, AI-enabled capabilities, and scalable technology delivery. You will work across engineering, product, operations, and business stakeholders to translate complex requirements into practical technology solutions. The position offers the opportunity to influence architecture, execution quality, and the technology capabilities that enable long-term growth within a life sciences environment.

Location: Remote - US based candidates only, no visa sponsorship available

Compensation: $210,070 – $282,851 annually

Responsibilities

• Build and scale machine learning infrastructure for drug discovery
• Collaborate with cross-functional teams to identify infrastructure needs
• Act as a mentor and coach to foster growth and learning
• Promote a model-driven culture that supports rapid experimentation
• Optimize performance of GPU clusters and model deployment systems
• Establish MLOps standards across the organization
  
  

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Qualifications

• 5-7 years in technical roles focusing on infrastructure and MLOps
• Proven leadership experience in hands-on technical management
• Strong understanding of distributed systems and orchestration techniques
• Expertise in ML infrastructure technologies, GPU optimization, and model deployment
• Passionate about continuous learning and mentoring others in technical areas
• Familiarity with tools like Python, Docker, Kubernetes, and cloud platforms is beneficial
  
  

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Benefits

• Full remote work flexibility
• Collaborative working environment with technical leaders
• Opportunities for mentorship and professional growth
• Accessible and committed leadership
• Comprehensive benefits package including bonuses and equity opportunities
  
  

Our client is an equal opportunity employer. We encourage you to apply even if you don’t meet every qualification—your background could be exactly what this team needs.