Lead Machine Learning Engineer
4 weeks ago
Job Description
About the Role
We are looking for an engineer with strong experience in building, deploying, and scaling chatbot solutions on AWS. The role involves working closely with product and engineering teams to design conversational AI systems that are secure, scalable, and integrated with enterprise applications.
Key Responsibilities
Design, develop, and deploy chatbot solutions leveraging AWS services (Lambda, API Gateway, DynamoDB, S3, etc.).
Integrate chatbots with enterprise applications (CRM, HRMS, custom apps, etc.).
Build NLP workflows, conversation flows, and handle fallback/error strategies.
Implement monitoring, logging, and analytics to track chatbot performance.
Ensure security, scalability, and high availability of deployed solutions.
Collaborate with product managers, UX designers, and data scientists to improve conversational experiences.
Optimize costs and performance of chatbot workloads on AWS.
Required Skills
Strong hands-on experience with AWS services (Lambda, S3, DynamoDB, CloudWatch, API Gateway, IAM).
Machine Learning and Artificial Intelligence
Proficiency in at least one programming language (Python, Node.Js, or Java).
Experience with NLP / conversational AI frameworks (Rasa, Dialogflow, or similar).
Knowledge of API integrations (REST, GraphQL, Webhooks).
Understanding of CI/CD pipelines (CodePipeline, GitHub Actions, Jenkins).
Familiarity with cloud security best practices and IAM policies.
Knowledge of FastAPI, Flask or other API development frameworks
AI Agents knowledge
Nice to Have
Experience with Generative AI (Amazon Bedrock, OpenAI APIs, Anthropic Claude, etc.).
Familiarity with front-end integration (React, Angular, mobile apps, WhatsApp/Slack/Teams bots).
Exposure to MLOps or deploying custom NLP models.
Knowledge of analytics platforms for chatbot performance (Amazon Kendra, QuickSight, or third-party).
Years Of Experience
7 to 12 Years
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