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 : Senior Machine Learning Engineer
Experience : 3-5 Years
Location : Bangalore (Hybrid)
Role & Responsibilities
- Experimenting with range of models, evaluating model performance and model selection.
- Performing data cleaning, feature engineering, selection and evaluation.
- Implementing the data and model training pipelines on cloud using AWS services such as sagemaker, lambda functions, etc.
- Documentation for Model architecture and solutions
- Collaboration with cross-functional teams, including platform engineers, Machine learning engineers, software developers and business stakeholders, to ensure data solutions meet business needs.
- Adhering to project timelines
- Communicate with non-technical stakeholders to understand their data requirements and convey the benefits of data solutions, including migration strategies
Must Have Skills
- Machine Learning Engineer with 3–4 years of experience, based in Bangalore, with a requirement to work from the client’s office 2 days a week.
- Good exposure on Python (Pandas, Numpy, Matplotlib, Advance Python Syntax’s etc)
- Hands on experience on OpenAI Framework, required to develop AI applications.
- Handson experience in developing the RAG pipeline, LLM Gen AI models and Prompt Engineering.
- Handover experience on creating the MCP’s (Model Context Protocol).
- Exposure on Agentic frameworks like langGraph and langchain.
- Exposure to the Agentic framework (like AWS Bedrock Agentcore) is mandatory.
- Exposure on below AWS Services - Amazon SageMaker Studio, Amazon Elastic Container Registry, Amazon API Gateway, Amazon DynamoDB, Amazon Managed Streaming for Apache Kafka, AWS Elastic Beanstalk, AWS Glue, AWS Lambda, Amazon Elastic Container Service, Kubernetes.
- Hands-on GenAI Model Providers (example : OpenAI models, Anthropic models and Gemini Models).
- ML Algos : Bagging and Boosting algorithms
Good To Have Skills
- AWS Bedrock Models
- Redshift and SQL
- ML Algos : Bagging and Boosting algorithms
- Knowledge of Data Pipelines (GlueJobs)
If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!
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