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Head of AI and ML Strategy

1 month ago

Bengaluru, Karnataka, India Saambavilabs Full time
Role Overview:

The Head of AI and ML Strategy & Implementation will be the driving force behind the company's AI and ML vision, strategy, and execution. This individual will shape the roadmap for AI/ML solutions, aligning them with the company's business objectives and ensuring they deliver impactful results in healthcare diagnostics. Acting as the company's AI/ML ambassador, this role requires a balance of technical expertise, strategic leadership, and strong interpersonal skills.

Key Responsibilities:

1. Strategic Leadership:

• Develop and own the AI/ML roadmap, aligning it with the company's long-term vision and business goals.

• Identify industry trends, technological advancements, and innovations in AI/ML that can be leveraged for healthcare diagnostics.

• Ensure the integration of AI/ML solutions aligns with regulatory, ethical, and compliance standards in healthcare.

2. Execution and Delivery:

• Oversee the development, deployment, and scaling of AI/ML models for key diagnostics applications.

• Ensure robust data pipelines, model performance, and real-world efficacy in healthcare scenarios.

• Establish quality benchmarks, testing protocols, and KPIs to measure the impact of AI/ML solutions.

3. Thought Leadership:

• Represent the company at conferences, industry events, and in publications as a leading voice in AI/ML-driven healthcare diagnostics.

• Build and maintain relationships with academic institutions, industry forums, and government bodies to stay at the forefront of innovation.

4. Team Leadership and Development:

• Build, mentor, and manage a team of AI/ML engineers, data scientists, and domain experts.

• Foster a culture of innovation, continuous learning, and ethical AI practices within the team.

• Collaborate with cross-functional teams, including product management, operations, and clinical specialists, to ensure seamless integration of AI/ML capabilities.

5. Stakeholder and Client Management:

• Engage with internal and external stakeholders, translating complex AI/ML concepts into actionable insights and recommendations.

• Build and maintain client trust by demonstrating the value and reliability of AI/ML solutions.

• Collaborate with hospital partners and other clients to tailor AI/ML solutions to their unique challenges.

6. Operational Oversight:

• Define data acquisition strategies, ensuring data quality, security, and privacy for AI/ML applications.

• Ensure cost-effective resource allocation for AI/ML projects while achieving maximum impact.

Key Qualifications:

Technical Expertise:

• Advanced degree (Ph.D. preferred) in Computer Science, AI/ML, Data Science, or a related field.

• Proven experience in designing and implementing AI/ML systems, preferably in healthcare or similar regulated industries.
• Expertise in machine learning frameworks (TensorFlow, PyTorch, etc.), cloud platforms, and large-scale data processing.

• Strong understanding of ethical AI, data privacy, and security considerations.

Leadership and Management:

• 10+ years of experience in leadership roles related to AI/ML, data science, or technology strategy.

• Demonstrated ability to lead and inspire multidisciplinary teams in a fast-paced environment.

• Track record of managing complex projects with multiple stakeholders and delivering results.

Interpersonal Skills:

• Exceptional communication skills, with the ability to simplify technical concepts for non-technical stakeholders.

• Proven ability to manage and influence diverse stakeholders, from internal teams to industry leaders and clients.

• Strong negotiation, problem-solving, and conflict resolution skills.

Thought Leadership:

• Recognized authority in AI/ML, with a portfolio of publications, patents, or contributions to industry standards.

• Experience as a speaker or panelist at industry conferences is highly desirable.

Personal Attributes:

• Visionary Thinker: Able to anticipate future AI/ML trends and position the company as a leader in the field.

• Ethical Leader: Strong commitment to building responsible AI that prioritizes patient safety and data integrity.

• Adaptable: Thrives in a startup environment, capable of handling ambiguity and shifting priorities.