Job Summary:

This role will lead the technical execution of the Company’s AI initiatives, bridging advanced algorithm research with scalable engineering solutions. This role will be vital in developing and maintaining a robust AI development framework, establishing production-grade MLOps capabilities, and collaborating closely with data scientists, infrastructure specialists, and algorithm teams to ensure effective AI solution deployments.

Main Responsibilities:

• Lead end-to-end ML solutions development and delivery, including data ingestion, feature engineering, training, validation, deployment, and monitoring.

• Architect a highly available, secure, scalable cloud/on-prem hybrid ML infrastructure.

• Engage directly with ML scientists, contribute to algorithm development, and act as the team’s bridge/glue between science and engineering.

• Partner closely with algorithm scientists, translating innovative concepts into reliable, production-ready software.

• Implement robust CI/CD workflows for ML models, including testing, rollout, rollback strategies, and compliance governance.

• Ensure strict compliance with regulatory and privacy standards such as HIPAA, GDPR, and Software as a Medical Device (SaMD) guidelines.

• Evaluate and pilot emerging technologies, including large language models, multimodal machine learning techniques, and advanced hardware accelerators.

• Mentor and guide ML engineers and data scientists, establish coding standards, and conduct detailed design and architectural reviews.

Required Qualifications:

• Bachelors Degree (± 16 years) in Computer Science, Engineering Mathematics, or related field

• Minimum 10 years with 10+ years of experience, Master’s Degree with 7+ years of related experience, or Ph.D. with 2+ years of related experience

• Experience in building and deploying Machine Learning solutions using various ML algorithms and hands-on experience with Python programming

• Experience in building IT use cases / solutions especially around AI/ML cognitive services and platforms, Model product ionization, and CICD Automation.

• Excellent understanding of Machine Learning techniques and proficiency in feature analysis, algorithm selection and model hyperparameter tuning

• Experience of senior executive/leadership engagement

• Exposure to various aspects of architecture practices and frameworks: business, application, data, security, infrastructure and governance

• Experience with NLP/NLG, AI Conversational Agents & Other Generative AI, and Software development lifecycles

• Experience with Azure OpenAI, Azure Databricks, CloudDBs,

• Experience in reviewing and selecting Technical and Applications Architectures solutions

• Certifications and specializations in AI/ML, LLMs and Cloud platforms

• Excellent oral, written and presentation communication skills

• Preferred team leadership experience and demonstrated mentorship capabilities

Preferred Qualifications:

• PhD in Computer Science, Data Science, Data Engineering, or related field

• Medical Device experience

• Experience working in an FDA-regulated business (e.g. validated software related to medical, pharmaceutical, or life sciences products) is preferred.

• Solid understanding of the design thinking process, as well as a passion and know-how for influencing design strategy.

• Experience with microservices architecture and distributed systems.

• Publications, patents, or notable contributions to open-source projects.

• Experience with FDA 510(k) submissions and clinical-grade ML product development.

• Background in signal processing, computer vision, or multimodal learning.

• Familiarity with data security best practices, data anonymization, synthetic data generation, and federated learning.