- Location
- Bengaluru, KA, IN · Pune, MH, IN · Gurgaon, HR, IN
- Department
- IT
- Closing date
- Today
- Source
- iCIMS
Description
Role Description
ZS’s India Capability & Expertise Center (CEC) houses more than 60% of ZS people across three offices in New Delhi, Pune and Bengaluru. Our teams work with colleagues across North America, Europe and East Asia to create and deliver real world solutions to the clients who drive our business. The CEC maintains standards of analytical, operational and technological excellence across our capability groups. Together, our collective knowledge enables each ZS team to deliver superior results to our clients.
ZS's Scaled AI practice is part of ZS's rich and advanced AI ecosystem, in the Architecture & Engineering Expertise Center, focused on creating continuous business value for clients using a range of innovative machine learning, deep learning, and engineering capabilities.
Being part of Scaled AI practice allows you to collaborate with data scientists to create state-of-the-art AI models, create and use cutting-edge ML platforms, create and deploy advanced ML pipelines and manage the complete ML lifecycle.
What You’ll Do
- Design and implement technical features leveraging best practices for technology stack being used
- Collaborate with client-facing teams to understand solution context and contribute to technical requirement gathering and analysis
- Work with technical architects on the team to validate design and implementation approach
- Write production-ready code that is easily testable, understood by other developers, and accounts for edge cases and errors
- Ensure the highest quality of deliverables by following architecture/design guidelines, coding best practices, periodic design/code reviews
- Write unit tests as well as higher-level tests to handle expected edge cases and errors gracefully, as well as happy paths
- Uses bug tracking, code review, version control, and other tools to organize and deliver work
- Participate in scrum calls and agile ceremonies, and effectively communicate work progress, issues, and dependencies
- Consistently contribute in researching & evaluating the latest technologies through rapid learning, conducting proofs-of-concept and creating prototype solutions
- Support the project architect in designing modules/component of the overall project/product architecture
- Breaks down large features into estimable tasks lead estimation and can defend them with clients
- Implement complex features with limited guidance from the engineering lead. For example service or application-wide change
- Systematically debug code issues/bugs using stack traces, logs, monitoring tools, and other resources
- Performs code/script reviews of senior engineers in the team
- Mentor and groom technical talent within the team
What You’ll Bring
- At least 5-7 relevant hands-on experience in deploying and productionizing ML models at scale
- Experience in scaling GenAI or similar applications to accommodate a high number of users, large data size, and reduce response time.
- Strong knowledge in developing RAG-based pipelines using frameworks like LangChain & LlamaIndex
- Experience in creating GenAI applications such as answering engines, extraction components, and content authoring.
- Expertise in Designing, configuring, and using ML Engineering platforms like Sagemaker, MLFlow, Kubeflow, or other platforms
- Big data - Hive, Spark, Hadoop, queuing system like Apache Kafka/Rabbit MQ/AWS Kinesis
- Ability to quickly adapt to new technology and be innovative in creating solutions
- Ability to independently run POCs on new technologies and document findings to share
- Strong in at least one of the Programming languages - PySpark, Python or Java, Scala, etc. and Programming basics - Data Structures
- Hands-on experience in building metadata-driven, reusable design patterns for data pipeline, orchestration, ingestion patterns (batch, real-time)
- Experience in designing and implementation of solution on distributed computing and cloud services platform (but not limited to) - AWS, Azure, GCP
- Hands-on experience building CI/CD pipelines and awareness of practices for application monitoring
- Fluency in English
- Client-first mentality
- Intense work ethic
- Collaborative spirit and problem-solving approach