Senior Data Scientist - Artificial Intelligence/Machine Learning (5-8 yrs)

Job Description :

Key Responsibilities :

Technical Leadership :

- Lead and mentor a team of data scientists, fostering a collaborative and innovative work environment.

- Define the technical vision and roadmap for AI solutions related to media and content.

- Provide guidance and support to team members on technical challenges and best practices.

AI Solution Development :

- Design and implement AI solutions for various media content formats (audio, images, video, text).

- Leverage expertise in NLP (Natural Language Processing), Computer Vision, and Deep Learning to achieve project goals.

- Stay up-to-date with the latest advancements in AI research and implement them into your work.

MLOps & Deployment :

- Apply MLOps principles for production-ready deployment of AI models, ensuring scalability and maintainability.

- Utilize tools like Docker for efficient model containerization (experience with Kubernetes is a plus).

- Monitor and optimize the performance of deployed AI models.

Collaboration & Communication :

- Collaborate effectively with cross-functional teams (engineering, product, marketing) to deliver impactful solutions.

- Clearly communicate technical concepts to both technical and non-technical audiences.

- Document and present technical findings and recommendations.

Required Skills :

- PhD in Computer Science, Artificial Intelligence, or a related field (or equivalent experience).

- 5-8 years of experience in designing and developing AI solutions.

- Proficiency in Python and relevant libraries for AI development (e., TensorFlow, PyTorch).

- Expertise in Natural Language Processing (NLP), Computer Vision, and Deep Learning techniques.

- Experience with MLOps practices and tools for model deployment (Docker is a plus, Kubernetes experience is advantageous).

- Strong communication, collaboration, and leadership skills.

A passion for innovation and a commitment to building impactful AI solutions.

Tech Stack :

- Python (TensorFlow, PyTorch, etc.)

- NLP libraries

- Computer Vision libraries

- Deep Learning frameworks

- Docker (Kubernetes a plus)