Lead AI Engineer
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Key skills for this role
Key Skills for This Role
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Call for Applications for Lead AI Engineer (R-06) – ANNAM.AI
- AI Strategy and Innovation
- Define and execute ANNAM.AI’s AI strategy, identifying high-impact use cases for machine learning, computer vision, and data analytics in agriculture.
- Lead the design and development of advanced AI models for applications like crop monitoring, soil health analysis, and pest management.
- Drive innovation by integrating emerging AI technologies (e.g., LLMs, RAG-based models) into agricultural solutions.
- Project Leadership and Execution
- Oversee end-to-end AI project lifecycles, from ideation and model development to deployment and scaling in rural ecosystems.
- Manage the integration of diverse data sources (e.g., satellite imagery, IoT sensors, weather data) into robust AI systems.
- Lead pilot projects and proof-of-concept initiatives to validate AI solutions for farmer adoption.
- Team Leadership and Mentorship
- Mentor and guide a team of AI engineers, data scientists, and field practitioners to deliver high-quality, impactful solutions.
- Foster a culture of innovation, collaboration, and farmer-first thinking within ANNAM.AI.
- Coordinate with interdisciplinary teams, including agricultural scientists and external stakeholders, to align AI solutions with real-world needs.
- Partnerships and Ecosystem Engagement
- Build and maintain strategic partnerships with government bodies (e.g., MoA&FW, ICAR, NABARD), research institutes, startups, and agri-businesses.
- Represent ANNAM.AI as a technical ambassador on national and international platforms to promote AI-driven agricultural transformation.
- Engage with donor agencies, CSR partners, and private sector stakeholders to secure funding and support for large-scale AI initiatives.
- Research and Policy Contributions
- Create case studies on AI applications in agriculture to enhance ANNAM.AI’s thought leadership.
- Provide technical inputs to government agencies on AI adoption, food security, and sustainable agriculture policies.
- Develop capacity-building initiatives, such as workshops and hackathons, to train students, startups, and innovators in agri-tech.
Candidate Profile
Bachelor’s, Master’s or PhD degree in Computer Science, Artificial Intelligence, Data Science, or a related discipline from a reputed institution.
Expertise in AI/ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn) and advanced techniques (e.g., deep learning, computer vision, LLMs, RAG).
Strong programming skills in Python, C++, or Java, with experience in cloud platforms (e.g., AWS, Azure, GCP) and IoT systems.
Knowledge of agricultural data sources (e.g., satellite imagery, sensor data) and their application in AI solutions is highly desirable.
Professional Experience
Proven Track in AI/ML development, with experience in leadership or Sr. technical roles.
Proven track record in leading large-scale AI projects, preferably in agri-tech, healthcare, or rural technology ecosystems.
Experience managing interdisciplinary teams and collaborating with external stakeholders (e.g., government bodies, startups, FPOs).
Prior contributions to research publications or open-source projects in AI is an advantage.
Performance-Based Incentives
About ANNAM.AI
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