Description :

About the Role :

We are seeking a highly skilled and visionary Lead AI/ML Engineer to lead the design, development, and deployment of scalable machine learning and artificial intelligence solutions.

The ideal candidate will combine strong hands-on technical expertise with leadership capabilities to mentor teams, define ML architecture, and drive innovation across data-driven initiatives.

This role involves close collaboration with data scientists, data engineers, product managers, and business stakeholders to translate complex business challenges into impactful AI/ML solutions that deliver measurable outcomes.

Key Responsibilities :

- Lead the end-to-end development lifecycle of machine learning models from problem definition, data exploration, feature engineering, and model training to evaluation and deployment.

- Build and productionize ML models for classification, regression, forecasting, NLP, computer vision, or recommendation systems, depending on project needs.

- Work with large and complex datasets using distributed data processing frameworks such as Spark, Databricks, or Ray.

- Implement feature stores, data pipelines, and model registries to enable reusability and governance of ML assets.

- Collaborate with data engineers to ensure data quality, availability, and reliability for model training and inference.

- Design scalable ML system architectures for cloud and hybrid environments using tools such as AWS Sagemaker, Azure ML, or Google Vertex AI.

- Develop automated MLOps pipelines for model versioning, CI/CD, monitoring, and retraining.

- Deploy and monitor models in production using containerization (Docker) and orchestration tools (Kubernetes, Kubeflow, MLflow).

- Optimize models for latency, throughput, and cost efficiency in real-time or batch inference settings.

- Ensure compliance, reproducibility, and governance across all ML workflows.

- Stay current with the latest AI/ML research, tools, and frameworks, applying relevant innovations to real-world business problems.

- Identify opportunities to leverage AI for process automation, customer personalization, risk mitigation, and predictive analytics.

- Contribute to AI roadmap definition, including technology selection, architecture standards, and best practices.

- Evaluate open-source and commercial AI tools, recommending the right solutions for various business use cases.

- Mentor and guide a team of data scientists and ML engineers, fostering a culture of experimentation and learning.

- Review code, architectures, and model performance to ensure quality and consistency.

- Collaborate with cross-functional teams including product managers, engineers, and business analysts to align technical solutions with business objectives.

- Present AI/ML strategies, insights, and outcomes to technical and executive stakeholders.

Preferred Experience :

- Proven track record of delivering AI/ML solutions in production at scale.

- Strong background in data science, applied mathematics, or software engineering.

- Hands-on experience with large language models (LLMs), generative AI, or multimodal models is a plus.

- Familiarity with A/B testing, feature stores, and data drift monitoring.

- Exposure to data lakehouse architectures and cloud-native data pipelines.

- Experience in Agile/Scrum environments and end-to-end project delivery