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