AI Engineer

Axya Inc.; Montreal; Remote; CAD 80,000 - 120,000; Full time

Job summary

An innovative startup is seeking an AI Engineer to shape the future of industrial procurement through intelligent automation and AI. In this role, you will design and optimize Retrieval-Augmented Generation (RAG) pipelines, deploy advanced computer vision models, and contribute to cloud-based solutions. Join a dynamic team that values creativity and collaboration while making a real-world impact. This is your chance to work on cutting-edge AI systems with flexibility and ownership, all while enjoying competitive compensation and benefits. If you're passionate about pushing the boundaries of technology, this opportunity is for you.

Benefits

Competitive compensation

Stock options

Flexible working hours

Health benefits

Collaborative team environment

Qualifications

• 5+ years in Machine Learning Engineering with focus on AI systems.
• Experience in building RAG architectures and MLOps best practices.

Responsibilities

• Design and deploy RAG-based AI systems for internal and client applications.
• Collaborate on computer vision initiatives and optimize cloud solutions.

Skills

Machine Learning Engineering

RAG architectures

MLOps best practices

Cloud platforms (AWS preferred)

Python programming

Computer vision models

Tools

Haystack

AWS S3

AWS EC2

AWS Lambda

AWS SageMaker

PyTorch

TensorFlow

Job description

AI Engineer

French version below

Location: Remote (Quebec or Ontario)

About Us: At Axya, we’re reshaping the future of industrial procurement with intelligent automation and cutting-edge AI. We believe that technology should simplify complex systems — and that’s exactly what we’re building. As we scale, we’re looking for curious minds and sharp technologists who are excited about solving real-world problems with real impact.

The Role: We're on the hunt for an AI Engineer passionate about pushing the boundaries of AI-driven systems. Your work will focus on building and optimizing Retrieval-Augmented Generation (RAG) pipelines, deploying vision models, and scaling solutions in the cloud. Bonus points if you're well-versed in knowledge graphs — we’re exploring ways to enrich our internal intelligence systems with structured knowledge.

What You’ll Be Working On:

• Designing, developing, and deploying RAG-based AI systems for internal tools and client-facing applications
• Implementing and optimizing cloud-based solutions (preferably AWS, but Azure or GCP works too)
• Collaborating on computer vision initiatives — from data pipelines to model fine-tuning and deployment
• Contributing to the architecture of AI workflows, ensuring modularity, scalability, and efficiency
• Integrating or leveraging knowledge graphs to enhance information retrieval and contextual awareness in our systems

What We’re Looking For:

• Minimum 5 years of experience in Machine Learning Engineering
• Proven experience building RAG architectures using tools like Haystack, or custom pipelines
• Strong experience in MLOps best practices
• Solid understanding of cloud platforms (AWS preferred), including services like S3, EC2, Lambda, and SageMaker
• Hands-on experience with advanced computer vision models (e.g., YOLO, CLIP, Detectron2) across training, evaluation, and deployment, along with proficiency in DevOps practices within cloud-based environments
• Strong coding skills in Python and experience with frameworks like PyTorch or TensorFlow

Nice to Have:

• Experience with LLM orchestration tools like LlamaIndex, etc.
• Exposure to vector databases (Pinecone, FAISS, Weaviate, etc.)
• Understanding of data privacy, security, and ethical AI principles
• Understanding of knowledge graphs, ontologies, or graph databases like Neo4j, RDF, or TigerGraph

Why Join Us:

• Make a real-world impact at a growing startup
• Collaborate with a sharp, motivated, and down-to-earth team
• Work on cutting-edge AI systems with flexibility and ownership
• Competitive compensation, stock options, and benefits

**Axya is an equal opportunity employer and encourages applications from Indigenous peoples, persons with disabilities, members of visible minority groups, and women.