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AI - LLM Engineer – Agronomist Expert System

Location: Hybrid or Remote

Company: IoT That

Job Type: Full-Time

About Us

We are building a next-generation agronomist expert system powered by large language models (LLMs) and real-world agricultural data. Our mission is to empower farmers and agronomists with intelligent, context-aware recommendations to optimize yield, irrigation, fertilization, and disease detection using AI. We’re looking for an AI Engineer with deep LLM experience who is excited to work at the intersection of machine learning, agriculture, and real-world deployment.

Responsibilities

  • Design and fine-tune large language models (LLMs) tailored to agronomic applications
  • Engineer a conversational expert system that understands and responds to real-world farm management queries
  • Integrate structured agronomy datasets (e.g., weather, soil, satellite) into LLM workflows
  • Develop pipelines for model training, evaluation, and continual fine-tuning
  • Collaborate with agronomists to translate domain knowledge into usable prompts, embeddings, and model objectives
  • Ensure models produce accurate, safe, and useful agronomic recommendations

Requirements

  • 3+ years of experience in machine learning or NLP, with focus on LLMs (GPT, LLaMA, Mistral, etc.)
  • Proficiency in Python, Hugging Face Transformers, LangChain, or similar frameworks
  • Experience with prompt engineering, fine-tuning, or RAG (Retrieval-Augmented Generation) pipelines
  • Understanding of knowledge graphs, embeddings, and contextual memory for dialogue agents
  • Ability to work across product, engineering, and domain expert teams
  • Excellent communication skills and documentation practices

Nice to Have

  • Experience with agricultural or environmental datasets (e.g., NDVI, evapotranspiration, pest detection)
  • Familiarity with sensor data, edge AI, or IoT deployment
  • Background in agronomy, plant science, or environmental modeling
  • Experience deploying LLMs on GPU/TPU infrastructure or optimizing for inference (ONNX, quantization)

What We Offer

  • Competitive salary, equity, and benefits
  • Opportunity to shape the core architecture of a real-world AI product in agtech
  • Access to agronomists, on-farm data, and validation partners
  • A mission-driven team solving high-impact sustainability challenges

How to Apply

Please send your resume, portfolio/GitHub, and a short statement on why this mission excites you to:

info@iot-that.com

Embedded Systems Engineer – AI Time Series Forecasting

Location: Hybrid or Remote

Company: IoT That

Job Type: Full-Time

About the Role

We're seeking a skilled Embedded Systems Engineer with a strong background in time series forecasting and AI integration to join our R&D team. This role involves working on intelligent edge devices that process and predict sensor data using real-time machine learning algorithms, including models like Facebook Prophet. You will help design, implement, and optimize embedded solutions that integrate forecasting algorithms into low-power hardware environments for applications in [e.g., agriculture, energy, or industrial IoT].

Key Responsibilities

  • Design, develop, and test embedded firmware (C/C++/Micro Python) for microcontroller-based platforms (e.g., STM32, ESP32, ARM Cortex-M)
  • Integrate lightweight AI models and time series forecasting (e.g., Prophet) into embedded Linux or edge environments
  • Work with time series sensor data (e.g., environmental, telemetry, telemetry) and apply preprocessing, compression, and ML inference
  • Interface with cloud or edge pipelines for model training and deployment
  • Collaborate cross-functionally with AI/ML engineers, data scientists, and hardware designers
  • Optimize runtime memory, power consumption, and model execution on-device

Requirements

  • BSc/MSc in Electrical Engineering, Computer Engineering, or related field
  • 3+ years of experience in embedded systems development
  • Proficiency in C/C++, RTOS, and embedded debugging
  • Experience with Python-based ML libraries: Prophet, NumPy, Pandas, scikit-learn
  • Solid understanding of time series data, statistical forecasting, and signal processing
  • Familiarity with cross-compiling or deploying models to embedded Linux or microcontroller targets
  • Experience working with serial/UART, I2C, SPI, ADC, and wireless protocols (Wi-Fi, BLE, LoRa)

Nice to Have

  • Hands-on experience with TensorFlow Lite, uTensor, or Edge Impulse
  • Experience using Git, CI/CD pipelines, and containerized workflows (Docker)
  • Knowledge of sensor fusion, anomaly detection, or edge AI applications
  • Domain experience in agriculture, energy, or IoT verticals
  • What We Offer

  • Competitive salary and benefits
  • Opportunity to work at the intersection of AI and embedded innovation
  • Access to cutting-edge edge-AI toolchains and real-world datasets
  • Flexible work environment with a hybrid/remote option
  • How to Apply

    Send your resume, cover letter, and (if applicable) links to relevant projects or GitHub to:

    info@iot-that.com