– Part of Data Science team to develop high impact, scalable and sustainable ML solutions
– Collaborate with Senior Data Scientists and product managers to understand customer
needs and co-own the deployment and maintenance of key ML models
– Work closely with Data Scientists on text and image data using the leading ML techniques
in GenAI / OCR / Image processing
– Develop end to end pipeline and further enhancement of solutions for scale and stability
– Build quality checks, unit tests and diagnostic reports for code and output quality
monitoring using python, SQL and yaml
– Conduct modeling experiments and report automation
– Scheduling, automating and stabilizing the current AWS pipeline using jenkins, Step
Function, Lambda, Runtime, Sagemaker
– Develop in-house capability to deploy custom models on Sagemaker endpoints taking
care of platform and library compatibility
– Explore GCP capabilities to deploy projects – Code Versioning, end points, GCS, Bigquery
and automation / scheduling
Preferred Qualifications :
– Curiosity to learn Advanced ML, Data Science + ML Ops ; looking to build a career and
expertise in Data Science
– 1-2 years working experience as a Data Engineer / ML Engineer / Data Analyst
– Hands-on experience with Python and SQL is must
– Understanding of data modeling, data access, data storage, and optimization techniques – Experience working with cloud-based technologies and development processes
– An ideal candidate would be expected to have basic familiarity of GCP and AWS
Infrastructure. Advanced knowledge of ML Ops related tools like Sagemaker, ECR, Step
Functions, Vertex AI is preferred
– Ability to quickly understand the tech pipeline / project infrastructure; engage deeply with
Team members; Delivery quickly on new development or optimization related action items
– Quick action oriented approach preferred over brainstorming on very long term ideas
