Shape the future of AI by designing and developing cutting-edge ML solutions for diverse industries like BFSI, EnU, Life Sciences, and Manufacturing. This role involves translating complex business needs into scalable AI architectures and driving the complete ML project lifecycle.

You will be instrumental in evaluating and selecting optimal ML algorithms and frameworks, ensuring high performance, scalability, and interpretability. Continuous innovation is key, with opportunities to research emerging ML techniques and contribute to organizational growth.

This position also emphasizes strong collaboration, requiring you to mentor junior team members and effectively communicate technical insights to stakeholders and leadership.

Architect and build robust AI/ML solutions tailored for industries such as BFSI, Energy & Utilities, Life Sciences, and Manufacturing. Collaborate with cross-functional teams to define requirements and translate them into scalable machine learning architectures. Lead the full ML project lifecycle, from data exploration and model development to deployment and ongoing monitoring. Select appropriate ML algorithms, frameworks, and tools to optimize model performance and scalability. Research and integrate emerging ML techniques to drive innovation and continuous improvement. Define and implement data governance, model versioning, and deployment strategies for compliance and ethical AI use. Mentor junior developers and data scientists, fostering a collaborative team environment. Communicate technical solutions and project progress clearly to stakeholders, translating complex concepts into business terms.

A Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or a related discipline is required.

Possess at least 4 years of experience in AI/ML development, with a strong background in solution design, model creation, and deployment.

Demonstrate proven success in building ML solutions across multiple industry verticals, particularly BFSI, EnU, Life Sciences, and Manufacturing.

Exhibit strong programming skills in Python or R, coupled with hands-on experience using ML libraries such as Scikit-learn, XGBoost, TensorFlow, or PyTorch.

Maintain a solid understanding of supervised, unsupervised, and reinforcement learning algorithms.

Have practical experience with cloud platforms like AWS, Azure, or GCP, and their respective ML services (e.g., SageMaker, Azure ML, Vertex AI).

Showcase excellent analytical and problem-solving capabilities, thriving in fast-paced environments.

Possess outstanding communication skills, adept at conveying technical concepts to non-technical audiences.