Associate Machine Learning Engineer
RemoteUnited States
Job Summary
Design and deploy machine learning models for agricultural applications including crop classification, yield prediction, and disease detection. Process large datasets from satellite imagery, drone footage, and sensors to build robust data pipelines for training and inference. Collaborate with agronomists and researchers to optimize model performance, pre-train, fine-tune, and evaluate foundation models while documenting findings for stakeholders. Work remotely on a renewable two-year contract with potential extension, supported by industry-standard compensation and access to IIT Ropar's Center of Excellence in AI for Agriculture. Contribute to research publications and large-scale societal transformation through direct application of AI for public good.
Required Qualifications
- B.Tech/M.Tech/MS in Computer Science, Data Science, AI/ML, or a related field
- Strong foundation in machine learning, deep learning, and statistical modeling
- Proficiency in Python and familiarity with libraries such as PyTorch, TensorFlow, and scikit-learn
- Good understanding of data preprocessing, model evaluation, and validation techniques
- Experience with tools such as Jupyter, Git, and cloud platforms (AWS/GCP/Azure)
- Strong analytical and problem-solving skills with a passion for applying AI for social good
Desired Qualifications
- Exposure to LLMs, NLP, computer vision, remote sensing, or geospatial data
- Prior experience in building or adapting Foundation Models in text, speech or Geo AI or multi-modal / multi-lingual models
- Experience working with agricultural or environmental datasets
- Familiarity with model deployment tools and frameworks such as Docker, Flask, or FastAPI
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