Precision Planting is seeking an AI Engineer to build next-generation farmer-facing tools that harness artificial intelligence to deliver actionable insights for growers, advancing predictive maintenance, anomaly detection, and natural-language insight generation.
Requirements
- 2+ years professional experience in data science, ML engineering, or cloud-data and ML infrastructure
- Strong grasp of statistics, probability, and time‑series analysis.
- Hands‑on experience building and operating cloud infrastructure preferably in AWS (Terraform, CDK, CloudFormation, Lambda, SageMaker, ECS)
- Familiarity with collaborative development workflow and version control systems (ie., Git)
- Shipped production ML project, preferably in predictive maintenance, anomaly detection, or performance analytics.
- Experience fine‑tuning or prompt‑engineering LLMs (OpenAI, Hugging Face, etc.).
- Familiarity with vector databases (FAISS, Pinecone, pgvector), embeddings, and retrieval‑augmented generation.
Responsibilities
- Develop and advance cloud-based machine learning models and algorithms and deploy them into web and mobile digital ag applications.
- Build and maintain scalable data pipelines on AWS to collect, prepare, and serve datasets for model and algorithm development.
- Prototype and ship LLM‑powered features (RAG, natural‑language diagnostics, contextual help) that translate complex telemetry into clear, grower‑friendly insight.
- Own projects end to end: curate data, design features, evaluate models, deploy services, monitor performance, and iterate from customer feedback.
- Collaborate with data scientists, data engineers, computer‑vision engineers, and cloud and mobile software developers to create, refine, and deploy LLM and computer‑vision AI features.
Other
- Bachelor's degree in Computer Science, Computer Engineering, Statistics, Data Science, Mathematics, or equivalent experience in applied machine learning
- Self-driven with the organizational and communication skills required to work autonomously, deliver full solutions, mentor teammates, and foster a supportive team environment.
- MS Degree in Computer Science, Computer Engineering, Statistics, Data Science, Mathematics, or equivalent experience in applied machine learning data science
- Edge‑AI or embedded Linux deployment experience.
- Experience applying machine learning techniques to computer vision applications
