AI/ML/LLM Engineer (Healthcare & Edge AI)

Job Summary

We are seeking a highly motivated AI / ML / LLM Engineer to join our core technology team in Canada. The ideal candidate will have hands-on experience with training, fine-tuning, and deploying machine learning and large language models (LLMs) in real-world healthcare and embedded applications. This role involves working with multimodal data (text, image, time-series), optimizing models for edge deployment (e.g., on Jetson platforms), and collaborating with clinical and engineering teams to develop intelligent decision-support tools.

Key Responsibilities:

· Model Development & Training: Design and implement ML models and LLMs for clinical NLP, computer vision, and time-series analysis.

· LLM Fine-Tuning & Optimization: Fine-tune transformer-based LLMs (e.g., LLaMA, GPT, BERT) using domain-specific data.

· Multimodal Integration: Fuse data from EMR notes, physiological monitors, and video sources to build robust predictive systems.

· Edge AI Inference: Optimize and deploy ML/LLM models on edge platforms such as NVIDIA Jetson (Xavier, AGX Orin).

· Pipeline Automation: Build scalable training and inference pipelines using PyTorch, TensorFlow, and Hugging Face Transformers.

· Evaluation & Validation: Define performance metrics, conduct clinical validations, and refine models for safety-critical environments.

· Collaboration & Documentation: Work with firmware, frontend, and clinical teams; maintain technical documentation and research records.

Required Qualifications:

· 3+ years of experience in AI/ML development, including work on NLP and LLMs

· Proficiency in Python, PyTorch, and TensorFlow

· Hands-on experience with Hugging Face Transformers, LangChain, or OpenLLM frameworks

· Familiarity with NVIDIA CUDA, TensorRT, and ONNX for edge model acceleration

· Strong understanding of neural networks, model interpretability, and training workflows

· Experience with Git, version control, and collaborative development practices

· Solid grasp of medical or clinical datasets (notes, time-series, imaging) preferred

Preferred Qualifications:

· Experience deploying models on Jetson platforms (Nano, TX2, Xavier, Orin)

· Understanding of HIPAA, PHI, and secure model deployment in healthcare

· Knowledge of classical ML algorithms (XGBoost, SVM, clustering) for tabular data

· Experience with multimodal model architectures (e.g., vision-language models)

· Publications or participation in medical AI challenges (e.g., PhysioNet, MIMIC)

Why Join Us?

· Develop impactful AI solutions for neonatal and critical care

· Work at the intersection of healthcare, deep learning, and edge computing

· Collaborate with top clinicians, engineers, and researchers

· Competitive salary, benefits, and the opportunity to shape next-gen AI products