Architect - Machine Learning - GenAI

About the job

While technology is the heart of our business, a global and diverse culture is the heart of our success. We love our people and we take pride in catering them to a culture built on transparency, diversity, integrity, learning and growth.

If working in an environment that encourages you to innovate and excel, not just in professional but personal life, interests you- you would enjoy your career with Quantiphi!

Role : Architect - Machine Learning (AWS) Experience : 9 - 15 Years Location : Bangalore

Must have skills:

- 8+ years of relevant hands-on technical experience implementing, and developing cloud ML solutions on AWS.

- Hands-on experience on AWS Machine Learning services. Proven experience using AWS Sagemaker leveraging different types of data sources, Training jobs, real-time and batch Inference, and Processing Jobs.

- Good Experience developing applications using LLMs with Langchain.

- Must have experience using GenAI frameworks such as AWS Bedrock, OpenAI.

- Must have Hands-on experience fine-tuning large language models( LLM) and Generative AI (GAI), specifically LLama2.

- Must have Hands-on experience working with (Retrieval Augmented Generation) RAG architecture and experience using vector indexing such as Opensearch, Elasticsearch.

- Strong familiarity with higher-level trends in LLMs and open-source platforms.

- Should have experience with Deep Learning Concepts. Transformers, BERT, Attention models

- Prompt Engineering: Engineer prompts and optimizes few-shot techniques to enhance LLM's performance on specific tasks, e.g. personalized recommendations.

- Model Evaluation & Optimization: Evaluate LLM's zero-shot and few-shot capabilities, fine-tuning hyperparameters, ensuring task generalization, and exploring model interpretability for robust web app integration.

- Response Quality: Collaborate with ML and Integration engineers to leverage LLM's pre-trained potential, delivering contextually appropriate responses in a user-friendly web app.

- Thorough understanding of NLP techniques for text representation and modeling

- Able to effectively design software architecture as required

- Experience with at least one of the workflow orchestration tools, Airflow, StepFunctions, SageMaker Pipelines, Kubeflow etc.Knowledge of a variety of machine learning techniques (Supervised/unsupervised etc.) (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks

- Ability to create end to end solution architecture for model training, deployment and retraining using native AWS services such as Sagemaker, Lambda functions, etc.

- Ability to collaborate with cross-functional teams such as Developers, QA, Project Managers, and other stakeholders to understand their requirements and implement solutions.

Good to have skills:

- Experience of working for customers/workloads in the Edtech domain with use cases.

- Experience with software development   If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us !