Jr. AI Engineer

Key Responsibilities AI Model Development and Testing Assist in designing, developing, and testing machine learning and Generative AI models for applications like crop yield prediction, soil health analysis, and pest detection. Contribute to RAG pipeline development and integrate AI with real-world agricultural datasets. Build and fine-tune transformer-based models like BERT, GPT, and LLaMA for NLP-driven farmer advisory tools. Collaborate with Sr. AI engineers to optimize models for accuracy and scalability. Technology Deployment and Support Support the deployment of AI tools and platforms in rural agricultural settings, ensuring usability for farmers and field practitioners. Assist in developing LangChain-powered systems with Vector Database integration for efficient information retrieval. Provide technical support for pilot projects and proof-of-concept initiatives. Collaboration and Data Integration Work closely with interdisciplinary teams, including agricultural scientists, data analysts, and field staff, to align AI solutions with real-world needs. Integrate external data sources (e.g., weather data, market trends) into AI models to enhance decision-making for farmers. Participate in team discussions to identify high-impact use cases for AI in agriculture. Documentation and Reporting Document model development processes, datasets, and deployment outcomes for internal records and publications. Contribute to technical reports, case studies, or presentations for stakeholders, including government bodies and research institutes. Assist in preparing training materials for farmers or field staff on AI tool usage. Learning and Skill Development Stay updated on advancements in AI/ML, particularly in agri-tech applications, through training and mentorship. Participate in capacity-building initiatives, such as workshops or hackathons, to enhance technical skills. Candidate Profile \ Educational Qualifications Skills Diploma from IITM BS or Bachelor\or Master\degree in Computer Science, Artificial Intelligence, Data Science, or a related discipline from a reputed institution. Proficiency in programming languages such as Python, R, or Java, and familiarity with AI/ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn). Basic understanding of transformer models (BERT, GPT, LLaMA) and Generative AI concepts . Exposure to LangChain, RAG pipelines, and Vector Databases is a plus. Basic understanding of data processing, computer vision, or natural language processing for agricultural applications. Knowledge of cloud platforms (e.g., AWS, Azure) or IoT systems is a plus. Professional Experience Minimum 0\2 years of experience in AI/ML projects, internships, or research, preferably with exposure to agri-tech or rural technology deployment. Experience with data analysis, model development, or software development in academic or industry settings. Prior involvement in interdisciplinary projects or collaboration with non-technical stakeholders (e.g., farmers, FPOs) is an advantage. Performance-Based Incentives Jr. AI Engineers will be eligible for performance-based incentives, subject to periodic reviews and Governing Board approval. Incentives will be tied to project milestones, such as successful model deployment or farmer adoption rates. Separation Clause One monthotice in year one, two months in subsequent years, or salary in lieu. Application Process Submit your application through the Zoho Recruit portal Subject Line : Application for Jr. AI Engineer \ANNAM.AI Deadline : Applications are reviewed on a rolling basis until all the positions are filled.