Artificial Intelligence Scientist

precision-ai; Calgary; Hybrid; CAD 120,000 - 160,000; Full time

Job summary

Precision AI is seeking an Artificial Intelligence Scientist to drive research and applied AI initiatives at the intersection of advanced AI and agricultural applications. You will conceive and translate novel AI approaches into practical, production-ready solutions that address real-world farming challenges.

You will shape the scientific direction, design research-driven projects, and advance state-of-the-art models in computer vision, NLP, and multimodal settings, collaborating with agronomy

Qualifications

• PhD required or equivalent research record in AI/ML.
• Proven publication track record in AI, ML, CV, or NLP.
• Experience translating research into production systems.

Responsibilities

• Lead applied AI research to develop novel approaches for agricultural challenges such as crop monitoring, yield forecasting, and sustainability.
• Explore and prototype emerging AI paradigms, including reasoning-enhanced LLMs, self-reflection, and self-supervised learning.
• Translate research ideas into validated prototypes and production-ready methods.
• Design and evaluate models across computer vision, NLP, time-series, and multimodal learning.
• Advance model robustness, generalization, and efficiency under real-world agricultural constraints.
• Integrate domain knowledge from agronomy, climate, and geospatial data into model design.
• Mentor engineers and scientists on research methodology and experimental analysis.
• Communicate findings through reports and presentations.

Skills

AI/ML model design

Research leadership

Python programming

Cross-functional collaboration

Model deployment

Experimental design

Communication

Distributed data processing

Education

PhD in computer science, computer engineering, statistics, or mathematics

Tools

PyTorch

TensorFlow

Hugging Face

CI/CD tooling

MLflow

Job description

Role Overview

TheArtificial Intelligence Scientistat Precision AI willdrive innovation at the intersection of advanced AI research and agricultural applications. This roleis responsible forconceiving, researching, and translating novel AI approaches into practical solutions that address complex challenges in agriculture.

The AI Scientist will lead the scientific direction of AI initiatives by designing and overseeing research-driven AI projectsanddeveloping and advancingstate-of-the-artmachine learning models.This roleemphasizes problem discovery and ideation, developing novel solutions, and driving research from concept through deployment in collaboration with internal and external partners.

Working closely with AI leadership, engineers, agronomy experts, and strategic partners, the AI Scientist will shape both the long-term technical vision and the day-to-day execution of Precision AI’s AI-powered agricultural solutions.

This hybrid role is based in Calgary and will work from Precision AI’s headquarters 3 days a week.

Key Responsibilities

Research & Innovation

• Lead applied AI research to develop novel approaches for agricultural challenges such as crop monitoring, yield forecasting, and sustainability.
• Explore and prototype emerging AI paradigms, including reasoning-enhanced LLMs (e.g., chain-of-thought, self-reflection, tool use), recursive or iterative modeling, reinforcementlearningand RLHF-style training, and self-supervised or foundation models.
• Translate research ideas into validated prototypes and production-ready methods.

Advanced Model Development

• Design and evaluatestate-of-the-artmodels across computer vision, NLP, time-series, and multimodal learning (e.g., satellite/drone imagery, sensor data, text).
• Apply modern techniques such as representation learning, domain adaptation, few-shot learning, multimodal fusion, spatiotemporal modeling, and efficient fine-tuning.
• Advance model robustness, generalization, and efficiency under real-world agricultural constraints.

Agricultural Intelligence Integration

• Integrate domain knowledge from agronomy, climate, and geospatial data into model design and evaluation.
• Develop methods that handle noisy, sparse, seasonal, and region-dependent data, common in agricultural systems.

Scientific Leadership & Mentorship

• Set standards for scientific experimentation, and reproducibility across AI research efforts.
• Mentor engineers and scientists on researchmethodology, model design, and experimental analysis.

Collaboration & Knowledge Sharing

• Collaborate with cross-functional teams and external research partners to align research outcomes with real-world impact.
• Communicate researchfindings clearlythrough technical reports, presentations, and internal knowledge sharing.

Relevant Experience

• 4+ years of experience in AI/ML model design, training, and deployment in production environments.
• Provenexpertisein building andoptimizingmodels, including LLMs, VLMs,computer vision, and multimodalarchitecture.
• Experience withmodern learning paradigmssuch astransfer learning, self-supervised learning, domain generalization, and few-shot or representation learning.
• Experiencewith emerging and novel techniques, including retrieval-augmented generation (RAG), diffusion models, reasoning-enhanced LLMs (e.g., chain-of-thought, self-reflection), and reinforcement learning–based training or optimization.
• Strong programming skills in Python with solid knowledge of data structures, algorithms, and software engineering best practices.
• Hands-on experience with large-scaledata sets, data lakearchitecturesand distributed data processing
• Fluency inML frameworks (e.g.,PyTorch, TensorFlow, Hugging Face) andMLOpspractices (CI/CD, experiment tracking, reproducibility).
• Strong technical communication skills, withthe ability to document research, present results, and collaborate effectively across technical and non-technical teams.
• Proven ability to stay current with AI research,critically evaluate new methods, and apply them to complex real-world problems.

Academic Requirements

• PhDormaster'sincomputer science, computer engineering, statistics, or mathematics
• Strong publication record in reputable conferences or journals in AI, machine learning, computer vision, NLP, or related areas