About Miimansa
Miimansa is a health tech startup at the forefront of AI and machine learning applications in life sciences and healthcare. We digitise clinical workflows with the help of modern AI tooling, to achieve improved clinical and financial outcomes for drug developers, patients, providers & payers.
Role Overview
We are seeking a hands-on and visionary Engineering Manager to lead the end-to-end product engineering lifecycle. This role combines leadership, technical excellence, strategic thinking, and people management to build impactful technology solutions in the healthcare and life sciences domain.
Key Responsibilities
- Technical Oversight: Provide hands-on leadership in AI/ML system design and deployment, working closely with individual contributors to guide solution architecture, data pipelines, algorithm selection, and model development. Embrace a collaborative, in-the-trenches approach to ensure the quality, reliability, security, and scalability of AI systems in production environments.
- Project Planning & Execution: Take ownership of defining project scope, objectives, and deliverables, while actively engaging with team members to align day-to-day execution with strategic goals. Lead detailed planning, timeline management, and resource allocation with a focus on team synergy, enabling world-class delivery standards within time and budget constraints.
- Innovation & Problem-Solving: Foster a mindset of innovation through active collaboration and by supplementing individual team strengths. Tackle challenges alongside contributors, translating complexity into practical, high-impact solutions. Champion continuous improvement and technical excellence in every phase of AI/ML development.
Required Qualifications
- Bachelor’s/Master’s/Ph.D. in Computer Science, Machine Learning, Engineering, or a related technical field.
- Proven hands-on experience in AI/ML system development, including designing, building, and deploying models at scale.
- Strong foundational knowledge of data engineering, machine learning algorithms, and cloud-native architectures.
- Demonstrated ability to lead from within the team, actively contributing to technical problem-solving and supporting team members at an individual level.
- Deep understanding of ML Ops, CI/CD practices, versioning, and monitoring AI systems in production.
- Experience managing complex projects with cross-functional teams, delivering against aggressive timelines without compromising on quality.
- Strong interpersonal and leadership skills with the ability to balance strategic vision with execution detail.
- A track record of fostering innovation, mentoring talent, and elevating team performance through technical and emotional intelligence.
Preferred Qualifications
- Experience in healthcare IT or clinical research informatics.
- Familiarity with healthcare data standards (e.g., HL7, FHIR).
- Knowledge of AI/ML applications in healthcare.
- Understanding of regulatory requirements in healthcare software development.