Time since we first saw it
Day 119
Up longer than most. Similar jobs usually come down between day 6 and day 69.
From 4,296 similar postings that came down. Coming down is not always a hire.
Architect - Machine Learning - GenAI
IN KA Bengaluru
Open 3 months, first seen by us 119 days ago- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting
What you’ll work on
Full postingCreate end-to-end solution architecture for model training, deployment and retraining on AWS
Fine-tune hyperparameters and evaluate LLM zero-shot and few-shot performance
Engineer prompts and few-shot techniques to improve LLM task performance
Collaborate with ML and integration engineers on LLM responses in a web app
Design software architecture and work with cross-functional teams on solutions
From the employer’s posting
Ability to create end to end solution architecture for model training, deployment and retraining using native AWS services such as Sagemaker, Lambda functions, etc.
Model Evaluation & Optimization: Evaluate LLM's zero-shot and few-shot capabilities, fine-tuning hyperparameters
Prompt Engineering: Engineer prompts and optimizes few-shot techniques to enhance LLM's performance on specific tasks
Collaborate with ML and Integration engineers to leverage LLM's pre-trained potential, delivering contextually appropriate responses in a user-friendly web app.
Able to effectively design software architecture as required
Posting record
Report an errorOpen 3 monthsWe first saw this posting 119 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
- Status in our records
- Live
- First seen by us
- Jul 8, 2026119 days ago
- Recorded sightings
- 168
- Last seen by us
- Nov 4, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Quantiphi is hiring
30 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- ML Engineer hiring has slowed
- Takes jobs down at a usual pace
- 3% of open jobs were reposted
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- AWS
- Elasticsearch
- SageMaker
- Airflow
Where the posting names them
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 : 12 - 15 Years
Must have skills: - 12+ 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.
- 12+ 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.
- 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.
- 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.
- 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.
- 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.
Your next step
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About the role
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
US government figures for computer and information research scientists
- Median yearly pay, May 2025
- $140,300
- Expected change, 2025 to 2035
- 21.8% more jobsagainst 3.5% for all jobs
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
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 : Architect - Machine Learning (AWS)
Experience : 12 - 15 Years
Location : Bangalore
Must have skills:
12+ 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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IN KA Bengaluru
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