Do you want to work on complex and pressing challenges—the kind that bring together curious, ambitious, and determined leaders who strive to become better every day? If this sounds like you, you’ve come to the right place.

YOUR IMPACT

You will deal with Product and Services architecture and you will work at the intersection of other pods that deal with Data Engineering, Data Integration, Application Development and Data Science.
You should be able to deploy ML, NLP and other similar solutions in a production environment at scale.
You will be given ownership across the entire Software Engineering and Ops Lifecycle with a strong emphasis on Machine Learning Engineering to deploy models, and training, inference and validation pipelines into production.
In the process, you will be supported and encouraged to become a Technology Architect.
You will work with Data Engineers, Developers, Analysts and Product Owners to build scalable, reliable, and impactful services.
You will be creating and maintaining stable, performant services (real-time, streaming, batch and scheduled) and applications that will deal with prescriptive analytics pre-dominantly which will help in driving firm decisions on the basis of large data-sets within the firm.
You will design, implement, deploy into the cloud, and integrate state-of-the-art machine learning services at scale in production into critical firm workflows that need to be availed for stakeholders and users to serve the following use-cases - recruitment, trainings for firm members, team composition, staffing, satisfaction of your colleagues, etc.
You will build self-serve tools and services that will be leveraged by Product Owners and non-tech colleagues to analyze and to distill unstructured text data into actionable insights. For example, you will deploy solutions that analyze unstructured text like resumes, job descriptions, surveys, and other firm documents to help with use-cases in recruiting, staffing, etc.
You will architect scalable and performant solutions for the firm’s use-cases; provision and support Platforms, Tools, and Services necessary to drive Advanced Analytics, BI initiatives, and AI/ML opportunities in the People Technology space; conduct Discoveries and in-depth analysis of Cloud Services and SaaS platforms to determine the optimal tech stack for the team.
You will develop NLP, ML Ops, and other capabilities for data scientists across the firm to use; aid Development teams with activities related to Architecture diagrams, Cloud Infrastructure setup and Security.

YOUR QUALIFICATIONS AND SKILLS

• 3 + years experience developing production oriented systems in Python is required. Experience with R preferred
• Applied understanding of Natural Language processing techniques and Gen AI (e.g. language transformers / Large Language Models, text embeddings, and topic modeling), Statistical methods (e.g. linear and logistic regression), Machine Learning methods and optimization (e.g. boosted trees and deep neural networks), and graph algorithms with efficacy metrics
• Prior experience with Infrastructure as Code (IaC) using solutions like Cloud Formation, Terraform or similar tools; developing CI/CD automation (primarily using GitHub actions, ArgoCD)
• Hands on experience working with AWS services such as the ones related to Networking (VPC, Load Balancers), Compute (ECS, EKS, EC2), Storage (S3), Serverless (Lambda), API Gateway, Data Science services (Sagemaker), etc.
• Bachelor’s degree preferred in computer science or related field

Please refer the Job description for details