Senior Machine Learning Engineer

Developing and maintaining Machine Learning (ML) models used in our computer

vision based diagnostic tool

End-to-End Machine Learning Application delivery which includes Planning, Design,

Development, Testing, and Delivery of Application(s)

Developing open-source, cloud enabled, microservice based, scalable platforms that

provide amazing consumer experience, whilst building cutting-edge technology that

provides device protection with a unique value proposition

Implementing requirements of the API layer like security, custom analytics, throttling,

caching, logging, request, and response modifications etc. using the API management

platform

Implementing API monitoring and system support for production application services

client facing environments

Ensuring timely development of POC's and prototypes prioritizing quick time to

market with MVP features

Applying Agile techniques to deliver key features quickly to ensure stories are

delivered in incremental manner e.g., breaking down the stories in the right sizes,

scheduling them, encourage sustainable workloads etc.

Continuously research new technical capability and solutions for adoption

You will require the following qualifications and skills

Master's Degree or PhD in the fields of Computer Science, Statistics, or an equivalent with a

minimum of 5 years of experience in data science and ML Ops Engineering

Should have worked with at least one GenAI project

Familiarity with Gen AI foundation models and Amazon Bedrock

Should have expertise in Deep Learning & Reinforcement Learning techniques

Should have experience in building statistical models using the above-mentioned techniques

Should possess ability to build & deploy the models and interpret the results to business users

Should have experience working with NLP models and building related applications such as

chatbot, text-classifications, etc

Should have experience working with big data tools Hadoop, Hive, Spark.

Proficiency in Python, good understanding of OOPs is a must.

Worked with at least one mainstream machine learning framework such as Tensor Flow, py

Torch, Lang chain

Experience working with Cloud platforms (Azure, AWS, GCP)

Should have ability to write complex SQL & stored procedures

Should have experience in working with API's - deploying models, extracting data.

Should have good communication skills and ability to interact with customers

Good grasp of Microservices based Architecture

Previous hands-on experience in training and developing ML models is preferred

Exposure to computer-vision based technologies and MLOps solutions from

AWS/GCP is a major plus (AWS SageMaker, AWS Lambda, GCP Vertex, Kubeflow

etc.). AWS is preferred.

Experience building applications using services provided by AWS such as S3, SQS,

SNS and Kinesis

Familiar with CI/CD tooling. CircleCI is preferred.

Exposure to Infrastructure as code (IaC) tooling such as Terraform or CloudFormation

is an advantage

Knowledge in web services especially in REST API and tools such as Postman

Working experience in a Linux based environment

Knowledge in source code repository and branching models in Git and usage of tools

such as GitHub, GitLab, BitBucket etc