AI/ML Developer Level II

About the Role

We are seeking an experienced AI/ML Developer Level II to join our Innovation & Software Solutions team. In this role, you will be responsible for designing, developing, deploying, and optimizing enterprise-grade conversational AI solutions using the RASA framework, Python, and Google Cloud Platform (GCP). Working closely with cross-functional teams, you will build scalable, production-ready virtual assistants and intelligent automation solutions while driving continuous improvements in machine learning models, NLP performance, and MLOps practices. This is an excellent opportunity for a proactive developer who is passionate about conversational AI, cloud technologies, and delivering innovative AI-powered solutions at scale.

Responsibilities:

• Design, develop, and maintain enterprise-grade conversational AI solutions using RASA Open Source and RASA Pro/X.
• Develop complex dialogue flows, NLU pipelines, custom actions, stories, and rules.
• Train, evaluate, fine-tune, and optimize NLP models to improve chatbot performance, intent recognition, entity extraction, and user experience.
• Build clean, scalable, and maintainable backend services and APIs using Python.
• Deploy, monitor, and manage AI applications on Google Cloud Platform (GKE, Cloud Run, Compute Engine, Pub/Sub, Vertex AI, Dialogflow, Cloud Speech-to-Text, and Text-to-Speech).
• Integrate conversational AI solutions with enterprise systems and third-party services.
• Contribute to CI/CD pipelines, automated testing, model versioning, and MLOps best practices.
• Analyze conversational data using BigQuery and leverage Cloud Storage for managing training datasets and model artifacts.
• Collaborate within an Agile development environment and mentor junior team members when needed.

Qualifications:

• Bachelor's degree in Computer Science, Software Engineering, Data Science, or a related discipline, or equivalent practical experience.
• Strong hands-on experience with Python and software engineering best practices.
• Proven experience developing conversational AI solutions using RASA.
• Hands-on experience with Google Cloud Platform (GCP) services.
• Strong understanding of Natural Language Processing (NLP) concepts, including intent classification, entity recognition, dialogue management, and context handling.
• Experience working with machine learning frameworks such as spaCy, scikit-learn, or Transformers.
• Proficiency with Git and collaborative software development workflows.
• Excellent analytical, problem-solving, and communication skills.

Preferred Skills:

• Experience with Docker and Kubernetes.
• Knowledge of Terraform or other Infrastructure-as-Code tools.
• Experience implementing CI/CD pipelines and MLOps workflows.
• Google Cloud certifications, particularly Professional Machine Learning Engineer, are highly desirable.