[Hiring] Associate Director, AI/ML Engineering @Calyx

Role Description

As Associate Director, AI/ML Engineering, you'll lead the development and integration of cutting-edge artificial intelligence and machine learning (AI/ML) solutions into our Imaging platform for clinical trials. Your role will be central to driving the digital transformation of our platform—enhancing data-driven decision-making, accelerating trial execution, and improving outcomes. You'll lead a multidisciplinary team of engineers and scientists, shaping and executing an ambitious AI/ML strategy aligned with our R&D roadmap. You'll be responsible for defining technical architecture, establishing best practices, and championing AI/ML capabilities across the organization.

An accomplished professional, you'll play an instrumental role in managing talent, fostering innovation, and cultivating a culture of technical excellence and collaboration.

Key Responsibilities

• Strategic and Organizational leadership
  • Sets the strategic direction and supports the strategic roadmap for AI/ML adoption and innovation within the organization.
  • Contributes to governance frameworks and recommended protocols for responsible, ethical, and sustainable development and use of AI.
  • Contributes to the development of organizational capabilities, policies, standards, and guidelines in AI.
  • Collaborates with senior stakeholders to identify high-impact opportunities for AI and drives their implementation.
  • Follows research and industry trends and integrates them into organizational practices.
  • Works closely with senior leaders within R&D to align engineering goals with broader organizational objectives.
  • Serves as a key thought partner to senior leadership, providing regular updates on AI/ML initiatives, progress, risks, and opportunities.
• Talent growth and People Leadership
  • Builds a team that drives innovation, aligns with Company culture and values, and delivers business priorities.
  • Develops a comprehensive talent strategy that includes recruitment, retention, onboarding, and career development.
  • Leads, mentors, and manages a high-performing team of engineers, fostering an environment that encourages learning, collaboration, and innovation.
  • Focuses on nurturing future leaders and provides growth opportunities through coaching, training, and mentorship.
• Cross functional collaborations
  • Serves as an AI/ML evangelist across the organization, promoting awareness and understanding of the capabilities and value of AI/ML technologies.
  • Partners with scientists, domain experts, software engineers, and product teams to define requirements.
  • Supports Product Manager to translate business requirements into technical AI solutions.
  • Communicates complex technical concepts to technical and non-technical stakeholders.
• Technical leadership & Mentorship
  • Oversees the end-to-end lifecycle of AI/ML projects, from concept and design through to deployment and optimization.
  • Provides strategic technical direction for AI/ML initiatives, ensuring alignment with broader R&D and platform transformation goals.
  • Provides technical leadership and mentorship, guiding engineers in implementing scalable, secure, robust, and high-performing AI/ML systems for clinical trials applications.
  • Leads code and model reviews, ensuring high standards of quality, performance, and documentation.
  • Fosters a collaborative and inclusive team culture that encourages innovation, continuous learning, and knowledge sharing.
  • Ensures adoption of ML-Ops best practices, including model versioning, testing, deployment, and monitoring.
  • Supports the team in identifying the state-of-the-art AI technique and the needed data sets to solve the business problem.
• Innovation & Research application
  • Stays current with AI/ML research advances and evaluates their practical applications.
  • Identifies opportunities to improve existing systems with new techniques.
  • Contributes to the company’s intellectual property through innovative solutions.
  • Publishes and presents work at conferences.

Qualifications

• Excellent understanding of machine learning algorithms, neural networks, and statistical analysis.
• Strong numerical/statistical background including image processing.
• Strong source code management skills with git.
• Strong programming skills in languages such as Python and/or C++.
• Demonstrable ability to challenge work, such as identifying and adding new custom features with improved timelines.
• Knowledge of MLOps tools and practices for continuous integration/deployment of ML models.
• Excellent interpersonal, verbal, and written communication skills.
• A flexible attitude with respect to work assignments and new learning.
• A self-starter and able to work under own initiative.
• Ability to plan own work to meet given objectives and processes.
• Ability to handle production support work.
• Ability to manage multiple and varied tasks and prioritize workload with attention to detail.
• Shows initiative and self-confidence, is adaptable and able to manage changing and evolving priorities.
• Ability to work methodically in a fast-paced, time-sensitive environment.
• Demonstrable ability to apply critical thinking to problems and tasks.
• Proactively participates in skills improvement training.
• Ability to coach and mentor others to succeed enhancing individual and professional development.
• Ability to manage a globally distributed and multi-disciplined team.
• Strong problem-solving skills and analytical thinking ability.
• Leadership potential, attention to detail, and passion for innovation.
• Maintains an up-to-date awareness of trends, tools, technology, techniques, and processes that affect technology within the Life sciences domain.

Experience and Certifications

• Proven experience in developing and deploying AI/ML solutions in real-world applications with demonstrable experience of productizing AI/ML models.
• Proven experience in leading and developing AI/ML teams.
• Expertise in Machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn.
• Strong experience with cloud platforms (AWS, Azure, or GCP) and containerization technologies.
• Strong background in data structures, algorithms, and software engineering principles.
• Strong experience with medical imaging modalities (such as CT, MRI, PET, or SPECT) and DICOM standard.
• Experience with feature stores and ML data pipelines.

Education

• Ph.D. or Master’s degree in a relevant field (such as Mathematics, Computer Science, Data Science, Software Engineering, Biomedical Engineering, etc.).
• English: Fluent.

Benefits

• 25 days’ holiday (with the option to buy more)
• Health Cash Plan
• Optional private health, dental insurance, and health screens
• Cycle to work scheme
• Generous pension scheme with up to 10% employer contribution
• Life assurance
• Season ticket loan