Machine Learning Engineer

Job summary

Design, train, evaluate, and deploy machine learning models and scalable pipelines for predictive analytics and other business applications. Collaborate with data and software teams to integrate, monitor, document, and continuously improve production ML solutions.

Job details

Job Title: Machine Learning Engineer Job Type: Full-Time Experience Level: 2–5 Years Location: Toronto, Ontario Work Mode: Remote Job Overview We are looking for a skilled and motivated Machine Learning Engineer to design, develop, implement, and optimize machine learning models that solve real-world business problems. The ideal candidate will have a strong foundation in Python, machine learning algorithms, statistical analysis, and data processing, along with experience deploying scalable ML solutions in production environments. The candidate will collaborate with data scientists, software engineers, and cross-functional teams to transform complex data into actionable insights and intelligent applications. Key Responsibilities Design, develop, train, and deploy machine learning models for predictive analytics, classification, regression, and other business applications. Collect, clean, preprocess, and analyze structured and unstructured datasets. Apply machine learning algorithms, statistical methods, and feature engineering techniques to improve model performance. Build and maintain scalable machine learning pipelines for data processing, model training, and inference. Evaluate models using appropriate performance metrics and continuously improve accuracy, efficiency, and reliability. Collaborate with data scientists, data engineers, and software development teams to integrate ML models into existing applications. Implement model monitoring, performance tracking, and retraining processes. Work with cloud platforms and ML frameworks to develop production-ready solutions. Document model architectures, experiments, methodologies, and deployment procedures. Stay updated with emerging machine learning technologies, tools, and industry best practices. Required Qualifications Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, or a related field, or equivalent practical experience. 2–5 years of relevant experience in machine learning, data science, or software engineering. Strong programming skills in Python. Hands-on experience with machine learning libraries such as Scikit-learn, TensorFlow, or PyTorch. Strong understanding of supervised and unsupervised learning algorithms. Experience with data manipulation and analysis using Pandas, NumPy, and SQL. Knowledge of statistics, probability, linear algebra, and optimization techniques. Experience with model evaluation, feature engineering, and hyperparameter tuning. Familiarity with Git, APIs, and software development best practices. Preferred Qualifications Experience deploying machine learning models using cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform. Familiarity with Docker, Kubernetes, CI/CD, and MLOps practices. Experience with MLflow, model versioning, experiment tracking, or model monitoring tools. Knowledge of big data technologies such as Apache Spark. Experience with NLP, computer vision, recommendation systems, or generative AI. Understanding of REST APIs and production model-serving architectures. Key Skills Python Programming Machine Learning Algorithms Data Preprocessing and Feature Engineering Statistical Modeling TensorFlow / PyTorch / Scikit-learn SQL and Data Analysis Model Deployment and Monitoring Cloud Computing MLOps and Model Optimization Analytical Thinking and Problem-Solving What We Offer Opportunities to work on challenging machine learning projects. A collaborative and growth-oriented work environment. Opportunities for professional development and technical learning. Competitive compensation based on experience, skills, and employer requirements. Exposure to modern machine learning tools, technologies, and real-world applications. Equal Opportunity Statement We are committed to providing equal employment opportunities to qualified applicants. Employment decisions are based on relevant qualifications, skills, experience, and applicable legal requirements. How to Apply Interested candidates can submit their updated resume and relevant project details through the designated application channel. Shortlisted candidates will be contacted regarding the next steps in the recruitment process.

What you’ll do

Design, train, evaluate, and deploy machine learning models and scalable pipelines for predictive analytics and other business applications. Collaborate with data and software teams to integrate, monitor, document, and continuously improve production ML solutions.

Requirements

Requires 2–5 years of relevant experience and a bachelor's or master's degree in a related field, or equivalent practical experience. Candidates should have strong Python skills, experience with ML libraries and data tools, and knowledge of algorithms, statistics, model evaluation, feature engineering, and software development practices.

Benefits

• Professional Development Opportunities
• Technical Learning Opportunities
• Competitive Compensation

Listed skills

• SQL · Preferred
• Data analysis · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Python Programming
• Machine Learning Algorithms
• Data Preprocessing
• Feature Engineering
• Statistical Modeling
• TensorFlow
• PyTorch
• Scikit-Learn
• SQL
• Data Analysis
• Model Deployment
• Model Monitoring
• Cloud Computing
• MLOps
• Model Optimization
• Analytical Thinking

Job areas

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

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