Machine Learning Engineer - Python

Responsibilities :

- Design robust AI/ML solutions that align with business objectives and user needs.

- Lead the development of Generative AI models and applications, including conversational agents, chatbots, and personalized user experiences.

- Collaborate with cross-functional teams to integrate AI capabilities into Groww's products and services.

- Stay at the forefront of AI advancements and identify opportunities to leverage emerging technologies.

- Ensure the scalability, performance, and security of AI/ML systems in production.

- Guide and mentor ML engineering teams in best practices for AI/ML development.

- Define AI strategies and roadmaps, balancing short-term impact with long-term innovation.

- Drive the evaluation and selection of tools, platforms, and frameworks for AI projects.

- Work closely with data scientists, product managers, and other stakeholders to translate business problems into AI solutions.

Requirements :

- 8 to 10 years of core machine learning experience, including building and deploying ML models in production.

- Strong expertise in Generative AI, natural language processing (NLP), and conversational AI technologies.

- Proven experience in designing and implementing AI-powered chatbots, virtual agents, or similar applications.

- Proficiency in Python and common ML libraries/frameworks (e. g., TensorFlow, PyTorch, Hugging Face, etc.).

- Hands-on experience with cloud platforms (AWS, GCP, or Azure) and scalable architectures for AI workloads.

- Strong understanding of data pipelines, feature engineering, and MLOps practices.

- Excellent problem-solving skills and a deep understanding of machine learning algorithms.

- Experience in driving AI strategy and delivering measurable business impact.

- Strong communication and stakeholder management skills.

Preferred Qualifications :

- Master's degree in Computer Science, Machine Learning, or related field.

- Experience with reinforcement learning, recommendation systems, or personalization techniques.

- Contributions to open-source projects or research in the AI/ML domain.