Senior Cloud Architect

2 weeks ago

Bangalore, India Watson Search Partner Full time

About the Team :

Our team is responsible for ensuring that our organization's Data Scientists can effectively train and deploy classic ML models, Large Language Models (LLMs), and Large Image Models (LIMs) at scale. This is a highly exciting and rapidly evolving domain within Data Science.

As of July-2024, our team has successfully enabled Data Scientists to go live with multiple use cases using in-house open-source fine-tuned models. This includes Azure OpenAI ChatGPT 3.5, GPT 4, and GPT 4.o, as well as Google Gemini 1.5 Pro and Flash models.

Your Responsibilities :

1. As a technical expert, you will provide direction and oversight on software development methodologies, technologies, and best practices.

2. You will be responsible for driving technology and good practices in engineering in your respective team.

3. You will actively participate in development along with team members for at least 75% of your time, creating modules and systems that reflect the best practices.

4. You will be responsible for scaling, performance, and quality for the team.

5. You will set up best practices to help the team achieve the above and constantly think about improving technology usage.

6. You will experiment with new and relevant technologies and tools, and drive adoption while measuring yourself on the impact you can create.

7. You will implement long-term technology vision for your team.

8. You will be responsible for the architecture of your platform, ensuring it is aligned with the long-term requirements and the platform vision.

9. You will actively participate in technology forums and represent the company in internal and external forums.

10. You will create architectures and designs for new solutions around existing and new problem spaces in the organization.

11. You will drive technology and tool choices for your team and be responsible for them.

Your Qualifications :

1. You must have a Bachelor's degree in Computer Science or a related field.

2. You must have taken courses on Machine Learning/Deep Learning/MLOps or possess a Master's degree in Data Science or a related field.

3. You must have demonstrable industry or academic experience with the Machine Learning/Deep Learning domain. A GitHub repository showcasing your portfolio of work on ML/DL points is a plus if you have experience with distributed data processing, common ML algorithms, Deep Learning, familiarity with NLP or computer vision domains, usage of GPUs in ML lifecycle, exposure to CUDA programming, experience with Google Cloud Platform or any other public cloud, and working knowledge of Kubernetes or any container orchestration technology/framework.

What You Will Do :

1. As a Machine Learning leader, you will play a crucial role in the development and implementation of cutting-edge artificial intelligence products.

2. You will lead a team of technical professionals, providing guidance, mentorship, and support to ensure successful project delivery.

3. Your responsibilities will involve designing and constructing platform tools for deploying sophisticated machine learning models, as well as refining and updating existing systems.

4. You will build platform solutions to drive greater productivity for Data Scientists in the organization.

5. You will build tools to support adoption and quick productization of Data Science solutions.

6. You will build on recent advancements in the area of Generative AI, LLMs.

7. You will build frameworks to support distributed training, large model training within the company on Hybrid compute.

8. You will develop services on top of Computer Vision and Natural Language capabilities developed by Data Scientists.

9. You will develop a self-serve platform to allow Data Scientists to manage training, retraining, deployment, scheduling, monitoring, and improvement of ML models.

10. You will work on problems such as Data Version Controller, Experiment Tracking, Data Labeling, Active Learning, training large language models, building a cluster of GPUs optimized for inferring and training needs, both.

11. You will explore and conduct PoC using open-source frameworks, Azure, and GCP offerings on Data Science.

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