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quantiphi

Associate Architect - Machine Learning

Bengaluru · Staff/Principal

Older listing - lower visibility likelyVerified listingPosted 135d ago

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Skills required

22 listed
Retrieval-Augmented Generation (RAG)Decision Tree LearningArtificial Neural NetworksMachine LearningAWS SageMakerAmazon BedrockDeep LearningPrompt Engineering+14 more
Retrieval-Augmented Generation (RAG)Decision Tree LearningArtificial Neural NetworksMachine LearningAWS SageMaker

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Job description

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 : Associate Architect - Machine Learning (AWS)

Experience : 7 - 13 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!

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Applicants who checked fit first are 3.1× more likely to hear back

Your match scoreFree · sign in
86Overall
64Skills
97Experience

Your score for this role already exists

ASAI compared this JD against 41 signals - skills, seniority, domain, stack overlap etc. Add a resume and it unlocks in about 30 seconds.

Always free · no credit card · 1 tap with Google

Free · no signup

Get tomorrow's jobs before you have to search

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Why people use ASAI

Someone shared one job with you. ASAI keeps finding the rest.

  • Scored, not searched. Every role ranked against your actual profile.

  • Alerts as often as hourly. Reach new roles while the pile is still small.

  • Skill gaps, spelled out. See exactly which requirements you don't meet yet.

  • Verified jobs, only. Say no to ghost jobs. Your time deserves respect.

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