Ai / Ml Engineer
Revin KrishiPalakkad, Kerala, India16 hours ago
Job descriptionIntegrate and operate vector databases (Pinecone, Weaviate, Milvus) for semantic search over manuals, research papers, extension notes, sensor logs, and historical field records. Build embeddings-based retrieval systems for large-scale agronomic content (extension content, protocols, yield records, hyperlocal sensor time-series annotations). Expose ML capabilities via scalable APIs and services with backend engineers. Optimize and deploy models on AWS / GCP / Azure and / or edge / cloud hybrid architectures appropriate for field connectivity constraints. Work with agronomists and field teams to align model outputs with realistic farming recommendations and compliance (e.g., safe pesticide use). Instrument pipelines with monitoring, feedback loops, and data labeling workflows from field observations. Python expert : production-grade ML pipelines, reproducible experiments, and code quality. NLP practitioner : strong grasp of embeddings, tokenization, fine-tuning, transformer architectures. Applied AI builder : hands-on experience with LangChain, LangGraph, and Hugging Face ecosystem. Data & infra aware : experience with SQL / NoSQL and vector DBs (Pinecone, Weaviate, Milvus). Cloud experience : deploying ML services on AWS / GCP / Azure; knowledge of containerization, CI / CD. Comfortable translating domain knowledge (agronomy) into model inputs / labels and evaluation metrics. Prior work in agritech , environmental sensing, or decision-support systems for farming. Experience building chatbots or conversational assistants for low-connectivity or low-literacy users (multilingual support a plus). Familiarity with retrieval-augmented generation (RAG) at scale and model optimization (quantization, pruning, Distil / LoRA). Experience integrating time-series sensor data with textual knowledge bases (fusion models, multimodal retrieval). Bachelor’s or Master’s degree in Computer Science, AI / ML, Data Science, or related field. Strong Python programming skills and experience shipping ML in production. Demonstrable experience with LangChain / LangGraph and Hugging Face models. Working knowledge of vector DBs, embeddings, and cloud deployments. Work on real, high-impact AI for agriculture that reaches farmers and improves livelihoods. Collaborate with researchers and engineers at the intersection of AI and agri-science. Opportunity to lead innovation in agri-intelligence and scale solutions nationally. Be part of a fast-growing IIT-incubated startup with strong domain focus.
About the Job!!
You will be our : AI / ML Developer – NLP & Generative AI (Agri-Intelligence)
You will be based at : Palakkad, Kerala
Who We Are
At Revin Krishi , we’re redefining agriculture with data-driven intelligence and precision-farming solutions. Emerging from IIT Palakkad, we empower farmers with cutting-edge technology that improves productivity, sustainability, and profitability. Our products — Revin Eco (intelligent in-field monitoring) and Revin Livo (farm insights & decision platform) — are transforming farm decision-making. If you want to use AI to make real impact in agriculture and enjoy working in a high-growth, purpose-driven startup, join us!
Website : Your Role at Revin
We’re looking for an innovative, hands-on AI / ML Developer with strong expertise in NLP, RAG pipelines, LangGraph / LangChain, and vector databases — but focused on agri-intelligence use cases. You’ll build conversational & retrieval systems that help agronomists and farmers interpret sensor data, generate actionable insights, diagnose crop issues, recommend interventions, and automate agronomic knowledge workflows.
You’ll work closely with backend engineers, data scientists, agronomists, and product teams to design scalable ML pipelines and production services for hyperlocal agronomic intelligence.
What You’ll Do at Revin Core AI / ML Development
- Design and implement RAG-based pipelines and knowledge retrieval systems tailored to agronomy, pest / disease diagnosis, nutrient recommendations, and field advisory.
- Develop conversational AI agents that provide farmer-friendly guidance (in local languages where needed) — for example, diagnosing pest symptoms from farmer inputs, recommending management actions, and explaining reasoning.
- Fine-tune Hugging Face transformer models for agri-specific tasks : classification, named-entity extraction (crop / pest / chemical), summarization of field reports, and question answering over agronomic knowledge bases.
Data & Vector Intelligence
Collaboration & Deployment
Requirements — Who You Are
Preferred
Qualifications
Why Join Revin?
How to Apply
If you’re ready to design the future of agriculture with AI, send your updated resume and portfolio to :
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Engineer • Palakkad, Kerala, India
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