About the Role
As an AI/ML Computational Science Manager within the AI team, you will be instrumental in developing cutting-edge AI solutions. This role involves building innovative assets by leveraging the latest technologies and advanced AI techniques, specifically focusing on Machine Learning, Deep Learning, NLP, and GenAI-based methods. You will be responsible for creating products and solutions that enhance business processes and provide a competitive edge. The position requires adherence to world-class frameworks and standard development practices, with an emphasis on designing generic and scalable solutions.
What would you do?
- Drive the development of cutting-edge AI solutions using Machine Learning, Deep Learning, NLP, and GenAI-based techniques.
- Build innovative assets that impact the efficiency of business processes and differentiate the company.
- Leverage world-class frameworks, employ standard development practices, and design generic products/solutions.
- As an AI Lead, drive innovation through patenting, creating new assets, and enhancing existing ones.
- Analyze and solve moderate to complex problems using AI.
- Identify and build end-to-end AI assets including industrialization of assets.
- Drive innovation via patents and publications.
- Manage, mentor, and guide teams.
- Articulate leadership goals and drive the team to reach their vision.
- Follow best practices of AI asset development, including CI/CD, model monitoring, and responsible AI principles.
What are we looking for?
- 10 – 13 years of experience in relevant fields.
- Proficiency in Data Analytics, especially with Unstructured Data.
- Expertise in Natural Language Processing (NLP), Machine Learning, and Deep Learning.
- Experience with Large Language Models (LLMs), both Cloud and Open Source.
- Strong programming skills in Python.
- Ability to perform under pressure and establish strong client relationships.
- Skills in managing multiple stakeholders and understanding business challenges to drive business impact.
- Understanding of design patterns and exposure to designing large product architectures.
- Familiarity with Agile process / Sprint Planning / Product Management.
- Proficiency in DevOps and MLOps tools (e.g., MLflow, DVC, Kubeflow, SageMaker Pipelines).
- Experience with Cloud Technologies (AWS, Azure, GCP – including SageMaker, Vertex AI, Azure ML).
- Good understanding of SQL and NoSQL databases.
- Strong capabilities in Strategic Planning.
- Passion for staying current with emerging technologies in AI and ML (e.g., LangChain, LlamaIndex, vector databases like Pinecone/FAISS, Hugging Face Transformers, Prompt Engineering, ONNX, FastAPI, Docker, Kubernetes, TensorFlow Serving, TorchServe, Arize AI, WhyLabs).
- Any Graduation.