What are the responsibilities and job description for the Head of Machine Learning position at Metric Bio?
Head of Machine Learning /Senior Director Level
Location Preference: Based in Cambridge, MA or near the RTP/NC
Remote Option: The position could be remote for the right candidate.
A biotechnology platform advancing nature-positive agriculture by leveraging breakthroughs in human health and digital innovation. It develops biological solutions that enhance crop health, helping farmers increase yields while adopting more sustainable, natural practices.
Sector Focus:
- Nature-positive agriculture
- Bioengineering for crop health
- Integration of computational biology and ML in protein and peptide design
Core Responsibilities:
Strategic Leadership:
- Define long-term vision for computational/AI-driven biological design
- Lead cross-functional team (AI/ML, bioinformatics, structural biology)
- Foster scientific rigor, innovation, and rapid iteration culture
Scientific & Technical Execution:
- Drive protein/peptide design using advanced ML (deep learning, generative models, protein language models)
- Develop predictive/generative models for function and developability
- Integrate ML with wet-lab processes for DBTL acceleration
- Contribute to Biodesign IP portfolio development
Collaboration & Communication:
- Work closely with bioprocess, formulation, analytical, and regulatory teams
- Communicate insights and strategy to stakeholders and at scientific forums
- Align scientific direction with business and platform priorities
Program Oversight:
- Lead multiple computational discovery programs
- Manage project timelines, technical prioritization, and resource planning
Ideal Candidate Profile:
- PhD or equivalent in computational biology, ML, bioengineering, or related field
- 10 years in ML application to complex domains; 5 years in leadership
- Expertise in protein/peptide design via AI/ML
- Skilled in Python, scalable cloud environments (preferably AWS), and MLOps
- Proven team builder with biotech experience
***Ideal Talent Fit***
Target Backgrounds & Skill Sets:
- Computational biologists with a strong machine learning foundation
- AI researchers with domain experience in protein engineering or synthetic biology
- Experienced biotech leaders in bioinformatics or molecular modeling
- Technical leaders with proven MLOps and software engineering practices in cloud environments
- PhD-level scientists adept in cross-functional team management and translational science
This role is suited for individuals at the intersection of life sciences and machine learning, with a mission-driven mindset and the capability to innovate at the frontier of biological design.
