Associate Process Manager

Job Description:

Job Title - Senior AI Resource - Generative AI / ML

Location – Mumbai / Pune / Gurgaon

Notice Period – Immediate Joiner / 30 days

Experience – 5+ Yrs

Key Responsibilities:

1. AI Model Development: Design and develop advanced AI/ML models, especially in generative AI, using state-of-the-art techniques and methodologies. Contribute to building scalable solutions aligned with best practices in software development.
2. Model Training & Tuning: Train, fine-tune, and optimize generative models to meet specific business and technical requirements, ensuring high-quality and effective results.
3. Model Deployment Support: Assist in deploying generative models into production, collaborating with engineers to ensure seamless integration with existing systems and workflows.
4. Performance Evaluation: Evaluate and benchmark the performance of generative models using appropriate testing methodologies. Continuously iterate on models for improvement.
5. Documentation: Create and maintain clear documentation for developed models, algorithms, and systems to ensure easy understanding and future updates by team members.
6. Research & Application: Keep abreast of the latest developments in generative AI and ML research. Apply emerging techniques and algorithms to current or upcoming projects.
7. Collaboration: Work closely with cross-functional teams (such as engineers, data scientists, and product managers) to align AI model outputs with business objectives, contributing to the successful completion of projects.
8. Mentorship: Provide support and guidance to junior AI engineers and data scientists. Help foster a culture of continuous learning and skill development within the team.

Qualifications:

1. Master’s degree in Computer Science, Machine Learning, or a related field (Ph.D. is a plus).
2. Proven experience (5+ years) in developing AI/ML models and solutions, with a strong focus on generative AI.
3. Proficiency in deep learning frameworks such as TensorFlow, PyTorch, or Keras.
4. Strong programming skills in Python and experience with data manipulation, cleaning, and preprocessing.
5. Experience with cloud platforms (e.g., AWS, Azure, GCP) and deployment tools.
6. Ability to independently execute projects while collaborating effectively within a team.
7. Practical experience in model evaluation, including measuring accuracy, efficiency, and scalability.
8. Familiarity with the entire machine learning lifecycle: data collection, training, deployment, and monitoring.
9. Ability to work under pressure to meet deadlines while maintaining a high standard of quality.
10. Strong communication skills and the ability to present technical concepts to both technical and non-technical stakeholders.