Machine Learning Engineer Researcher

## About Farm Insights Farm Insights is a cutting-edge agritech company providing farmers with real-time insights into plant health, soil health, and chemical analysis for outdoor and indoor farming. Our platform leverages machine learning and real-time data streams to help farmers optimize their operations with actionable intelligence and detailed reports. We are seeking a talented Machine Learning Engineer to join our growing team and help drive the development of new AI models and system-wide optimizations. ## Role Overview As a Machine Learning Engineer at Farm Insights, you will be at the core of our AI efforts—designing, developing, testing, and optimizing state-of-the-art computer vision and NLP models. You'll work closely with our technical and product teams to deliver robust, production-ready machine learning solutions that power our platform and deliver meaningful impact for farmers worldwide. ## Key Responsibilities - Collaborate with the team to develop and maintain front-end and back-end components of the web application. - Integrate machine learning models to deliver real-time plant and soil health feedback. - Build interactive dashboards and reporting tools to visualize data insights. - Optimize data flow, APIs, and database performance. - Write clean, maintainable, and well-documented code. - Assist in testing, debugging, and deploying new features. ## What We're Looking For - Bachelor's, Master's, or PhD in Computer Science, Electrical Engineering, Data Science, or a related field, OR equivalent practical experience. ### Machine Learning & Deep Learning Skills - Hands-on experience developing and training models using frameworks such as PyTorch and/or TensorFlow. - Strong proficiency in Python and familiarity with key libraries (NumPy, Pandas, Scikit-learn, OpenCV, HuggingFace Transformers, etc). - Demonstrated experience with image and/or text data, data augmentation, and synthetic data generation is a plus. - Familiarity with MLOps best practices, including versioning, monitoring, and CI/CD for models. ### Evaluation & Optimization - Experience designing experiments and evaluating models with metrics and benchmarks. - Skills in optimizing model performance for inference (e.g., quantization, pruning, ONNX, TensorRT). ### Production & Engineering - Comfort deploying models as APIs or within end-user products, ideally on cloud platforms (AWS, GCP, or Azure). - Familiarity with Docker, RESTful APIs, and scalable infrastructure is an advantage. - Strong Problem-Solving Skills and a desire to learn and adapt. ## Why Join Us? - **Impact**: Your work will directly contribute to a platform improving agricultural productivity and sustainability worldwide. - **Growth**: Work on challenging, real-world AI problems with an experienced team at the intersection of agriculture and technology. - **Ownership**: Play a key role in shaping the future of our AI platform. - **Flexibility**: Remote or hybrid work options