AI / Machine Learning Engineer

Job summary

Design, develop, and deploy machine learning models and AI-powered solutions to solve business challenges. Build data pipelines, optimize model performance, and collaborate with cross-functional teams using MLOps best practices.

Job details

Position Summary We are seeking a motivated and innovative AI / Machine Learning Engineer to join our growing engineering team. This role is ideal for recent graduates and early-career professionals who are passionate about Artificial Intelligence, Machine Learning, and Generative AI technologies. As an AI / Machine Learning Engineer, you will contribute to the design, development, deployment, and optimization of intelligent applications and machine learning models that solve real-world business challenges. You will collaborate with data scientists, software engineers, and product teams to build scalable AI solutions using modern cloud and MLOps technologies. Key Responsibilities Design, develop, train, and deploy machine learning models for production applications. Develop AI-powered solutions using supervised, unsupervised, and deep learning techniques. Build and optimize data pipelines for machine learning workflows. Assist in developing Generative AI and Large Language Model (LLM) applications. Perform data preprocessing, feature engineering, and model evaluation. Collaborate with cross-functional teams to understand business requirements and translate them into AI solutions. Deploy machine learning models using cloud platforms and MLOps best practices. Monitor model performance and continuously improve prediction accuracy. Document technical designs, model architectures, and development processes. Stay current with emerging AI technologies, frameworks, and research. Required Qualifications Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Software Engineering, Mathematics, or a related field. 0–1 year of experience in AI, Machine Learning, Data Science, or Software Engineering (internships, research, and academic projects are considered). Strong programming skills in Python. Understanding of machine learning algorithms, statistics, and data structures. Experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn. Knowledge of SQL and relational databases. Familiarity with Git and version control systems. Strong analytical, problem-solving, and communication skills. Legally authorized to work in Canada. Preferred Qualifications Experience working with Large Language Models (LLMs) such as GPT, Llama, Gemini, or Mistral. Knowledge of Retrieval-Augmented Generation (RAG), prompt engineering, vector databases, and AI agents. Familiarity with cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform (GCP). Experience with Docker, Kubernetes, or containerized deployments. Exposure to MLOps tools such as MLflow, Kubeflow, or SageMaker. Experience using Hugging Face Transformers or LangChain. Knowledge of CI/CD practices and Agile development methodologies.

What you’ll do

Design, develop, and deploy machine learning models and AI-powered solutions to solve business challenges. Build data pipelines, optimize model performance, and collaborate with cross-functional teams using MLOps best practices.

Requirements

Requires a Master's degree in a related field and 0-1 years of experience in AI or software engineering. Candidates must have strong Python skills and familiarity with machine learning frameworks and SQL.

Listed skills

• Control · Preferred
• Software · Preferred
• Microsoft Azure · Preferred
• Analytical · Preferred
• CI/CD · Preferred
• Teams · Preferred
• Machine learning · Preferred
• Communication · Preferred
• Development · Preferred
• Agile · Preferred
• Amazon Web Services · Preferred
• Google Cloud · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Python
• Machine Learning
• Artificial Intelligence
• Generative AI
• Deep Learning
• Large Language Models
• TensorFlow
• PyTorch
• Scikit-learn
• SQL
• Git
• Data Pipelines
• MLOps
• RAG
• Prompt Engineering
• Cloud Platforms

Job areas

• Technology
• Engineering
• Data & Analytics
• Software
• Science & Research

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