Senior Software Engineer ? ML Ops

It is an American technology company most known for its postage meters and other mailing equipment and services, and with expansions into e-commerce, software, and other technologies. Was founded in 1920.

As a Senior Software Engineer – ML Ops, you will be part of our Commerce Cloud Data And Analytics 
team which is the core Big Data Team for across BU’s within the company and is responsible for hosting 
and managing TBs of Data and providing Analytical and Data Science Solutions and deploying Data Science 
Models in production.

Must to have :

• Software engineering experience in l Python/Scala/Java or similar programming languages to 
contribute to a Python code base.
• Scripting experience on Shell , AWS CLI etc.
• Experience architecting, building and deploying scalable data / Data science applications into 
AWS cloud using ECS, ECR,EKS, Elasticbeanstalk, Lambda, API Gateway, Sagemaker, DynamoDB, 
and S3
• Ansible , Terraform frameworks .
• Docker , Kubernetes (EKS)
• Operational knowledge of setting up and Managing Notebook Environments – Jupyter/Zeppelin
• Experience designing internet-scale public APIs.
• Operational Experience on setting up & maintaining Big Data Ecosysytem on AWS EMR & AWS 
Datapipeline  
• Experience working with Docker, CI/CD pipelines using GitlabCI & Jenkins , and familiarity with 
infrastructure as code principles.
• Hands on experience working on Production Solutions with understanding on Scalability, 
Reliability, Uptime, Cost Optimization of a solution.
• Participate in design review sessions and ensure all solutions are aligned to pre-defined 
architectural specifications
• Work with distributed teams to design and develop frameworks, solution accelerators, proofs of 
concept, and external customer facing products
• Evaluate and incorporate new technologies into new and existing frameworks and solutions as 
applicable
• Collaborate with and mentor members of the team and other coworker
• Experience, knowledge, and/or training with the Agile/Scrum methodology
• Ability to collaborate effectively and work as part of a team
• Strong attention to details
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Good to have :

• Project management and Stakeholder management experience
• Automation of ETL Jobs and orchestration using scripts, pipelines, workflows.
• AWS data streaming and big data technologies such as Amazon Kinesis, Managed Kafka, Amazon 
Simple Queue Service (Amazon SQS), Amazon Simple Notification Service (Amazon SNS)
Qualification & work experience
• UG - B.Tech/B.E. OR PG – M.S. / M.Tech from REC or any other reputed institute
• 1+ years of Experience on AWS Sagemaker
• 1+ years' experience in an AWS(EMR data Pipeline) development environment with experience 
working with hands on experience designing and implementing solutions.
• 1+ year experience on Ansible/Terraform 
• 1+ year experience on Docker/Kubernete.