Description : Applied AI/ML Lead

Experience : 10 - 15 Years

Location : Pune, India

Education : Bachelors degree in Computer Science Engineering or a related technical field

Role Summary :

We are seeking a visionary Applied AI/ML Lead to bridge the gap between AI research and production-grade business applications. In this senior leadership role, you will act as a "Technical AI Architect," responsible for designing and deploying scalable models that drive customer personalization, predictive analytics, and real-world business value.

You will lead a high-performance team to turn complex algorithms into robust features - such as recommendation engines and scoring systems - integrated into real-time data environments. The ideal candidate is an expert in the AWS ecosystem (SageMaker), possesses deep knowledge of AIOps, and is eager to pioneer LLM and RAG implementations to enhance customer-facing experiences.

Responsibilities :

- AI Model Orchestration : Lead the end-to-end development, testing, and deployment of AI/ML models specifically designed for customer personalization and business process optimization.

- Production Integration : Collaborate with Data Analytics and DevOps teams to ensure AI models are seamlessly integrated into production environments using AWS SageMaker or similar cloud services.

- Algorithmic Design : Design and oversee AI-based solutions leveraging advanced clustering, segmentation, and lead scoring techniques to drive targeted business outcomes.

- Feature Development : Manage the roadmap for AI/ML-based features, including real-time recommendation engines and predictive analytics suites.

- Data Readiness Governance : Partner with Data Engineering to build robust data pipelines, ensuring high data quality and low-latency integration with systems like Kafka.

- AIOps & Performance Tracking : Implement AIOps best practices to monitor model drift and performance, focusing on reducing Mean Time to Resolution (MTTR) for model-related incidents.

- Technical Mentorship : Mentor and guide a growing team of AI/ML engineers, fostering a culture of continuous learning and adherence to clean coding standards in Python.

- Modern AI Exploration : Stay at the forefront of AI advancements, integrating Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) into the product ecosystem where applicable.

- Workflow Automation : Drive the automation of ML workflows using tools like Airflow to ensure efficient model retraining and deployment cycles.

- Stakeholder Influence : Work closely with business leaders to align AI strategies with overarching company goals and customer experience improvements.

Technical Requirements :

- AI/ML Leadership : 10+ years of total experience in AI/ML, with 3+ years in a technical leadership or oversight capacity.

- Framework Mastery : Expert-level proficiency in TensorFlow, PyTorch, and scikit-learn.

- Cloud Infrastructure : Hands-on experience with AWS AI/ML tools (SageMaker, Rekognition, or equivalent).

- Programming & Data : Advanced Python skills and deep knowledge of real-time data systems (e.g., Kafka).

- Deployment Skills : Proven track record of moving models from Jupyter notebooks to scalable production environments.

Preferred Skills :

- GenAI Exposure : Practical experience with LLMs, Vector Databases, and RAG models.

- Data Management : Familiarity with MinIO or S3 for managing massive AI datasets.

- Orchestration : Experience with Airflow for managing complex ML DAGs.

- AIOps : Experience with model monitoring, logging, and automated retraining triggers.

Core Competencies :

- Applied Strategy : Ability to translate abstract AI research into tangible features that solve specific business problems.

- Decisive Leadership : Capability to manage a team under tight deadlines while maintaining high engineering standards.

- Scalable Thinking : Focus on building "Robust AI" that can handle high-volume, real-time customer traffic.

- Effective Communication : Ability to articulate the ROI of AI initiatives to both technical teams and non-technical stakeholders.