Senior Associate AI ML Engineer

Your Team Responsibilities

• Architect, build, and maintain scalable AI/ML and GenAI solutions for enterprise applications.
• Actively contribute to AI strategy and roadmap in collaboration with leadership and product teams.
• Ensure robustness, reliability, and optimization of production-grade data pipelines and ML systems.
• Drive end-to-end AI/ML lifecycle from ideation to deployment and monitoring.

Your Key Responsibilities

We are looking for a seasoned AI/ML engineer with a deep passion for data and innovation, a proactive mindset, and strong ownership of solutions. You will play a pivotal role in shaping our generative AI initiatives, delivering impactful and scalable intelligence across business verticals within Sustainability and Climate Org.

• Lead the design and implementation of machine learning, deep learning, and GenAI systems.
• Collaborate across engineering, product, domain experts, and senior leadership to identify and solve high-impact problems with AI.
• Architect clean, maintainable, and efficient ML and data pipelines using modern frameworks and cloud services.
• Develop and deploy AI models into production environments, ensuring resilience, scalability, and low latency.
• Stay ahead of the curve in GenAI advancements and infuse them into real-world use cases.
• Champion best practices in model training, evaluation, interpretability, and governance.
• Guide and mentor junior team members, fostering innovation and excellence.

Your skills and experience that will help you excel

• Strong programming skills in Python, with hands-on experience in ML libraries like TensorFlow, PyTorch, HuggingFace Transformers, Scikit-learn, etc.
• Proven expertise in building and deploying AI/ML systems at scale (batch or real-time).
• Practical experience with GenAI techniques including LLMs, fine-tuning, RAG, embeddings, prompt engineering, etc.
• Solid understanding of MLOps best practices and familiarity with tools like MLflow, Airflow, Kubeflow, and Docker/Kubernetes.
• Deep knowledge of data structures, algorithms, and software engineering principles.
• Strong grasp of data modeling, feature engineering, and large-scale data processing with Spark or similar technologies.
• Experience with cloud platforms (AWS, Azure, GCP) and their respective AI toolkits.
• Excellent communication skills and ability to translate technical concepts to non-technical stakeholders.
• Comfortable working in fast-paced environments and navigating ambiguity.
• Self-motivated and driven by impact, with a strong sense of ownership and initiative.

• Experience with multimodal AI (text, vision, audio).
• Publications, open-source contributions, or patents in AI or ML.