
Machine Learning Engineer
4 weeks ago
Overview
Design and implement AI/ML models to automate business processes and enhance user experiences. Lead and support the integration of AI into CRM systems (Freshworks) and related platforms. Build and maintain conversational AI/chatbots for customer service and internal support. Collaborate closely with product managers, developers, and operations teams to align AI capabilities with business objectives. Evaluate and recommend third-party AI tools and APIs where applicable. Contribute to architecture decisions for AI features, data flows, and platform integration. Stay current on emerging AI trends and apply learnings to future
Responsibilities- Design and implement AI/ML models to automate business processes and enhance user experiences.
- Lead and support the integration of AI into CRM systems (Freshworks) and related platforms.
- Build and maintain conversational AI/chatbots for customer service and internal support.
- Collaborate closely with product managers, developers, and operations teams to align AI capabilities with business objectives.
- Evaluate and recommend third-party AI tools and APIs where applicable.
- Contribute to architecture decisions for AI features, data flows, and platform integration.
- Stay current on emerging AI trends and apply learnings to future
- Education: Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, Information Technology or related field.
- Experience: Minimum of 2-3 years of professional experience in AI/ML development or AI platform integration.
- Proficient in:
- AI/ML frameworks such as TensorFlow and PyTorch
- Python or JavaScript (for model deployment and automation)
- Natural Language Processing (NLP), chatbot frameworks (Dialogflow, HuggingFace Models)
- Working with APIs and integrating AI into web, CRM platforms, and Cron.
- Knowledge in using AI workflows automation like N8N
- Strong Knowledge in AI Fine tuning methods
- CRM systems (Freshworks preferred)
- CI/CD and DevOps tools
- Agile methodologies and sprint planning
- Cloud services (e.g., AWS, GCP)
- Data handling and security best practices
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