Role Overview :

As a Senior AI/ML Engineer based in Delhi, you will spearhead the design and deployment of sophisticated machine learning systems that drive our core product innovation. You will operate at the intersection of data engineering and advanced model development, collaborating closely with cross-functional product teams, data scientists, and business stakeholders to translate complex requirements into scalable AI solutions. Your work will directly influence business outcomes by optimizing decision-making processes and enhancing user experiences through intelligent, automated workflows, ensuring our platform remains at the cutting edge of industry standards.

Key Responsibilities :

- Architect and implement end-to-end machine learning pipelines using Python and Spark to process large-scale datasets, ensuring high performance and reliability for downstream applications.

- Develop and maintain robust data orchestration workflows using Airflow to streamline model training and inference cycles, reducing time-to-market for new features.

- Engineer advanced RAG (Retrieval-Augmented Generation) frameworks and vector search implementations on Azure to provide users with highly accurate, context-aware AI interactions.

- Optimize SQL-based data retrieval processes to improve the efficiency of feature engineering, directly impacting the latency and accuracy of production models.

- Partner with engineering leadership to define technical roadmaps, mentoring junior team members while establishing best practices for model monitoring and lifecycle management.

Required Skillset :

- Demonstrated expertise in building production-grade machine learning models using Python, with a deep understanding of the full ML lifecycle from experimentation to deployment.

- Proven ability to manage complex data ecosystems using Spark and SQL, ensuring data integrity and performance in distributed computing environments.

- Strong proficiency in cloud-native AI development on Azure, specifically in configuring vector databases and implementing RAG architectures to solve real-world information retrieval challenges.

- Exceptional communication skills, with the ability to articulate technical AI concepts to non-technical stakeholders and influence strategic decision-making.

- A collaborative mindset suited for a high-impact hybrid work environment in Delhi, balancing independent problem-solving with active participation in team-wide architectural reviews.

- A degree in Computer Science, Data Science, or a related quantitative field, complemented by 6-12 years of hands-on experience in delivering scalable AI/ML solutions.