The role

Develop and evaluate AI approaches for agricultural tools and systems, connecting field data and machine perception to clearly defined user needs.

Responsibilities

  • Work with agricultural engineers to define use cases, data requirements, and evaluation criteria.
  • Build data pipelines and computer-vision or sensor-analysis models using representative agricultural observations.
  • Plan data collection, labeling, dataset versioning, and validation across changing field conditions.
  • Evaluate accuracy, uncertainty, robustness, and failure modes across crop, terrain, lighting, and weather variations.
  • Collaborate with mechanical, embedded, and software contributors to integrate perception and decision-support components.
  • Explore edge deployment, inference efficiency, monitoring, and human oversight.
  • Document experiments and translate research findings into reproducible prototypes.

Requirements

  • At least 6 years of relevant AI/ML, computer vision, or applied data-science experience.
  • Strong Python and experience with frameworks such as PyTorch or TensorFlow and computer-vision tools.
  • Practical model evaluation, data-quality, experimental-design, and deployment experience.
  • Ability to work with imperfect datasets and communicate the limits of a model clearly.
  • Experience collaborating across disciplines and maintaining reproducible research code.

Working arrangements

The role is remote. Any prototype integration or field-data visits will be agreed in advance.

Helpful experience

Agricultural imagery, robotics perception, geospatial data, edge AI, sensor fusion, or embedded deployment.

Engagement and compensation

This is a remote, Hyderabad-based contract-to-hire opportunity. The monthly INR range depends on relevant skills and years of experience. Contract duration, working arrangements, and deliverables will be agreed in writing. Conversion to permanent employment depends on performance, business needs, and mutual agreement and is not guaranteed.

Applying

Submit your CV and a short explanation of relevant work through the form on this page. Share your availability and anonymized examples; do not include client secrets or identity documents. We assess applicants on relevant skills and experience and welcome applicants from all backgrounds.