Consultant - Architecture & Engineering /ML

WhatYoullDo

• 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

WhatYoullBring

• At least 5+ 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