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