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AI/ML Engineer
1 month ago
We help start-ups grow. Through offshore development services, design solutions, talent acquisition and investor readiness services.
About the role
We are seeking a seeking an AI/ML Engineer with expertise in large language models (LLMs), prompt engineering, and API integration to help build and optimize our conversational AI systems. If you have a passion for cutting-edge technology, a strong background in AI/ML, and experience working with conversational agents, we would love to hear from you
Role Title: AI/ML Engineer (AI Agents)
Location: Trivandrum/ Remote
Experience: 5-7 Years
Contract: 6 Months (Extentable)
Educational Qualification: Bachelor / Master’s degree in CS/ME/IT
Roles & Responsibilities
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LLM Development & Prompt Engineering:
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Work with Gemini 2.0 or similar large language models to fine-tune and optimize conversational AI agents.
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Design, test, and refine prompts to enhance agent performance, ensuring the right tone, personality, and clarity in user interactions.
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Leverage LangGraph for orchestrating LLM calls and managing conversational state to create a seamless AI agent experience.
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API Integration:
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Utilize the Instagram Graph API to access and interact with user profiles, comments, direct messages (DMs), and other relevant data.
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Manage API authentication, handle rate limits, and ensure graceful error handling in interactions with the Instagram API.
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Knowledge Graph & Data Management:
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Design and manage user profiles and interaction data models for efficient storage and retrieval.
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Develop a knowledge graph to store user relationships and interactions (with experience in Neo4j a plus).
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Implement best practices for data modeling to optimize retrieval and management of user data.
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AI/ML Frameworks & Cloud Computing:
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Apply strong Python programming skills to implement AI models and integrations.
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Deploy and manage AI models on Google Cloud Platform (GCP), particularly with Vertex AI.
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Utilize Google Cloud Storage (Firestore or BigQuery) for storing and managing conversational data.
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Testing & Evaluation:
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Design and execute comprehensive tests to evaluate AI agent performance, accuracy, and ability to handle diverse scenarios.
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Monitor and track AI metrics such as user satisfaction, task completion rate, and response time to ensure optimal performance.
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Software Engineering Best Practices:
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Collaborate in code versioning using Git.
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Write clear, concise, and maintainable code documentation to support development teams.
You are close if you have
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Experience with large language models (e.g., Gemini 2.0) and prompt engineering techniques.
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Hands-on experience with LangGraph for conversational AI orchestration.
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In-depth knowledge of Instagram Graph API, including API authentication, rate limits, and error handling.
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Strong understanding of knowledge graphs and data modeling, with familiarity with Neo4j (preferred).
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Proficient in Python programming and AI/ML frameworks.
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Familiarity with Google Cloud Platform (GCP), especially Vertex AI, Firestore, and BigQuery.
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Experience in testing and evaluating conversational AI performance.
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Knowledge of Git for version control and code collaboration.
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Ability to write clear and concise code documentation.
Nice to Have
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Basic understanding of Natural Language Processing (NLP) concepts.
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Experience with other conversational AI frameworks like Dialogflow or Rasa.
