ML​/AI Integration and Enablement Specialist

Company Description

Founded through Flagship Pioneering’s venture creation engine, Terrana Biosciences is a cutting‑edge agricultural biotechnology company developing innovative RNA‑based products to address global agricultural challenges. We are committed to advancing sustainable farming solutions through precision technologies that ensure environmental safety and regulatory compliance.

The ML/AI Integration and Enablement Specialist is responsible for driving innovation and execution at the intersection of science, ML/AI, and software. The role requires technical expertise, strategic thinking, and leadership to develop, implement, and oversee cutting‑edge software, ML, and AI systems that accelerate discovery and development within Terrana’s scientific teams. The specialist will serve as a bridge between technical specialists and research groups, translating complex needs into scalable solutions, mentoring team members, fostering collaboration, and working closely with leadership.

• Develop a deep understanding of the science domain to identify opportunities where ML, AI, software, and data systems can significantly enhance team performance and scientific outcomes.
• Develop and execute a comprehensive ML, AI and software integration strategy, identifying key challenges and defining measurable objectives for technology‑driven improvements.
• Design, develop, deploy, and integrate ML, AI, and software tools and systems to automate and optimize the R&D pipeline and operations, transforming them into high‑throughput platforms.
• Promote AI fluency and data‑driven decision‑making across the company through the selection and deployment of key tools and associated technical mentorship.

• Master’s or Ph.D. in Computer Science, Bioinformatics, Computational Biology, or related field (or equivalent experience).
• 2+ years of experience in ML/AI software development, preferably in a biotech or life sciences environment.
• Proficiency in Python or similar programming languages for developing scalable software solutions.
• Hands‑on experience with machine learning frameworks (e.g., Tensor Flow, PyTorch, Scikit‑learn) and data engineering pipelines.
• Strong understanding of data structures, software architecture, and algorithmic optimization.
• Familiarity with cloud computing, MLOps, and deployment environments such as AWS, GCP, or Azure.
• Experience developing and maintaining APIs, databases, and automated data pipelines for scientific applications.
• Knowledge of bioinformatics tools, computational biology data formats, and workflows (FASTA/FASTQ, BLAST, RNA‑Seq, etc.).
• Proven track record of leading interdisciplinary projects involving research teams.
• Excellent communication skills and ability to convey complex technical concepts to non‑technical audiences.
• Strong organizational skills with the ability to manage multiple projects and priorities effectively.

Cambridge, MA or Durham, NC