Lead Machine Learning Engineer

We are seeking a highly skilled Machine Learning Lead to drive the development and deployment of advanced machine learning solutions across our products and platforms. This role demands a balance of technical excellence, project leadership, and a deep understanding of business goals. You will lead a team of ML engineers and data scientists, collaborating cross-functionally with product, engineering, and business stakeholders to deliver impactful AI-driven outcomes.

• Lead End-to-End ML Projects: Own the full lifecycle of ML solutions from problem scoping, data exploration, model development, deployment, and post-deployment monitoring.
• Own the Gen AI Strategy: Define and drive the technical vision and execution strategy for Gen AI use cases across the organization.
• Architect Scalable Solutions: Design robust ML systems and pipelines that integrate seamlessly into production environments.
• Team Leadership: Mentor and guide a team of ML engineers and data scientists, fostering a culture of technical excellence, innovation, and continuous learning.
• Modeling & Research: Stay up to date with the latest advancements in ML/AI and guide experimentation with novel algorithms (e.g., deep learning, NLP, GenAI, reinforcement learning).
• Build RAG & Prompt Engineering Pipelines: Design scalable architectures for RAG, vector search, prompt tuning, and prompt chaining with tools like LangChain, LlamaIndex, and FAISS.
• Stakeholder Collaboration: Work closely with product managers, engineers, and domain experts to translate business problems into technical solutions.
• Operationalize ML: Partner with MLOps/DevOps teams to deploy, monitor, and maintain ML models in production, ensuring reliability and scalability.

• Bachelor’s or Master’s degree in Computer Science, Machine Learning, Data Science, or related field (PhD is a plus).
• 8+ years of hands-on experience in machine learning, with at least 1–2 years in a leadership or mentorship role.
• Proficiency in Python and ML libraries such as scikit-learn, TensorFlow, PyTorch, HuggingFace Transformers, etc.
• Strong understanding of statistics, optimization, and model evaluation techniques.
• Experience with cloud platforms (AWS, GCP, or Azure) and tools like Docker, Kubernetes, MLflow, or Kubeflow.
• Proficiency in Python and Gen AI frameworks such as LangChain, Crew AI, or similar.
• Proven track record of deploying ML models into production at scale.
• Excellent communication and leadership skills.

• Background in domain-specific ML (e.g., healthcare, fintech, manufacturing).
• Familiarity with data engineering tools like Apache Spark, Airflow.
• Prior experience in startup or fast-paced environments.

Skills to Have : Artificial Intelligence, Natural Language Processing, machine learning, Deep Learning, Scikit-Learn, Python, Pytorch, Tensorflow, data science, Huggingface, Transformers, Langchain, Crew AI, Aws Cloud, Gcp Cloud, Azure Cloud.