Lead R&D Engineer, AI Applications

Hologic•Marlborough, MA

1d•$128,200 - $200,500•Onsite

About The Position

The Lead Engineer, AI Applications leads the identification, evaluation, and integration of artificial intelligence and computer vision capabilities across Hologic's GYN Surgical capital platforms, including ultrasound-guided fibroid ablation, hysteroscopy consoles, and associated imaging and visualization systems. This role serves as the primary technical and strategic interface between internal R&D teams, external AI and imaging technology partners, and cross-functional stakeholders in Clinical, Regulatory, Quality, Marketing, and Business Development. The position is responsible for shaping the division's AI application roadmap, managing external vendor engagements from evaluation through productization, and ensuring AI-enabled features are developed in compliance with applicable regulatory and design control requirements.

Requirements

Bachelor's degree in Computer Science, Electrical Engineering, Biomedical Engineering, or a related technical field required
Minimum 8 years of engineering experience in medical devices, medical imaging, or a comparable FDA-regulated industry
Minimum 3 years of direct experience developing, evaluating, or integrating AI or computer vision technologies
Demonstrated experience managing external technology vendors or development partners through evaluation, contracting, and delivery
Experience working within a design controls environment and with FDA regulatory pathways (510(k), De Novo)
Experience presenting technical recommendations to senior leadership
Sufficient technical depth in machine learning and computer vision to critically assess vendor claims, model performance data, and validation reports
Strong cross-functional leadership and facilitation skills, with the ability to drive decisions across engineering, clinical, and business functions
Clear written and verbal communication, with the ability to adapt content for executive, clinical, and engineering audiences
Strategic thinking with the ability to balance technical feasibility, clinical value, regulatory burden, and business priorities
Negotiation skills and sound judgment in commercial and intellectual property discussions
Ability to operate independently in ambiguous environments and establish structure where needed

Nice To Haves

Master's degree or PhD preferred
Experience with ultrasound, endoscopy, or other intra-procedural imaging modalities
Direct involvement in a regulatory submission for an AI- or ML-enabled device feature
Experience with clinical data collection, annotation workflows, and dataset management
Familiarity with real-time or embedded imaging system architectures
Working knowledge of IEC 62304, ISO 14971, IEC 60601, and FDA Good Machine Learning Practice principles

Responsibilities

Identify, assess, and prioritize opportunities to apply AI and computer vision within GYN surgical procedures and capital equipment, in collaboration with software, systems, and clinical engineering teams
Translate clinical and workflow needs into well-defined technical problem statements with measurable success criteria
Lead technical evaluation of external AI, imaging, and data partners, including definition of evaluation criteria, comparative assessment, and formal recommendations to leadership
Manage ongoing vendor relationships, including proof-of-concept scoping, milestone tracking, deliverable review, and issue escalation
Partner with Business Development, Legal, and Procurement on statements of work, intellectual property terms, and data ownership and portability provisions
Facilitate cross-functional alignment on AI initiatives across R&D, Clinical, Regulatory Affairs, Quality, and Marketing
Prepare and deliver technical and strategic recommendations to divisional leadership and the Steering Committee
Collaborate with Regulatory Affairs to define submission strategy for AI-enabled features, including predicate identification, predetermined change control plans, and alignment with FDA guidance on AI/ML-enabled medical devices
Define requirements for training, validation, and test datasets, including data sourcing, annotation processes, and dataset governance
Ensure AI and ML components are integrated into existing design control, risk management (ISO 14971), software lifecycle (IEC 62304), and cybersecurity processes
Provide technical guidance and mentorship to engineering staff on AI and computer vision methods, evaluation practices, and industry developments
Monitor the external landscape of AI technologies, standards, and competitive products relevant to the division's product portfolio
Perform other duties as assigned