We are hiring: AI Engineer (31-July-2026)

Company: NeuralScale Solutions

Client ID: 684QMTR

Job ID: 315LKPV

Workplace Type: Remote

Job Location: Canada

Job Type: Full-Time

Employment Type: FULL_TIME

Salary: $428,500 per YEAR

Hiring Organization: NeuralScale Solutions

Employer Address: 1200 Innovation Drive, Toronto, ON, Canada

Freshers Can Apply: Yes

Role Overview

NeuralScale Solutions is at the forefront of the artificial intelligence revolution. We are seeking a highly analytical and technically proficient AI Engineer to join our remote-first machine learning team. In this role, you will be responsible for the end-to-end design, development, and deployment of sophisticated machine learning models that solve real-world problems at scale. Whether you are an experienced ML researcher or a brilliant, math-driven fresher eager to push the boundaries of current AI technology, this role offers the perfect environment for professional growth. You will work on massive, diverse datasets to build systems that learn, predict, and innovate, all within a collaborative and cutting-edge remote environment.

Key Responsibilities

• Design and architect advanced machine learning models (Deep Learning, NLP, Reinforcement Learning).
• Develop and maintain scalable, production-grade AI pipelines that handle large-scale data processing.
• Optimize neural network performance and resource utilization to ensure fast, efficient inference.
• Implement predictive analytics and recommendation systems tailored to specific business requirements.
• Automate data labeling, preprocessing, and training workflows to accelerate model experimentation.
• Collaborate with data engineers and product teams to integrate AI capabilities into end-user applications.
• Monitor model performance in production, iterating on architectures to improve accuracy and reduce bias.

Required Qualifications

• Bachelor’s, Master’s, or PhD in Computer Science, Artificial Intelligence, Mathematics, or a related field.
• Expert-level proficiency in Python and deep experience with ML frameworks like PyTorch or TensorFlow.
• Solid understanding of linear algebra, calculus, and probability theory as applied to machine learning.
• Experience with building and deploying ML models in a production environment (MLOps awareness).
• Excellent analytical and problem-solving skills, with a focus on debugging complex model behaviors.
• Demonstrated capacity to work effectively in a 100% remote team, exhibiting strong self-direction and collaborative communication.

Preferred Skills

• Experience with Large Language Models (LLMs), Transformer architectures, or generative AI.
• Familiarity with cloud-based AI infrastructure (AWS SageMaker, Google Vertex AI, Azure ML).
• Knowledge of distributed computing frameworks (Spark, Ray) for high-volume data workloads.
• Experience with containerization (Docker, Kubernetes) and CI/CD tools for AI deployment.
• Prior participation in open-source AI projects or a strong portfolio of ML research and applications.

What We Offer

• Industry-leading annual compensation of $428,500.
• 100% remote flexibility with a generous annual home-office equipment budget.
• Comprehensive health, dental, and disability insurance coverage.
• Significant annual budget for professional development, research conferences, and advanced technical certifications.
• Opportunity to work on bleeding-edge AI infrastructure that influences the future of the industry.
• Generous paid time off, public holidays, and a focus on long-term employee well-being and balance.

Standard Application Notice

NeuralScale Solutions is an equal opportunity employer. We value a diversity of technical backgrounds and unique perspectives as a core driver of innovation. We encourage all qualified applicants, including entry-level candidates with a strong foundational understanding of ML principles, to apply. Please submit your application, including your resume and a portfolio of your ML/data project experience, via the form below. Only shortlisted candidates will be contacted for an interview.