Machine Learning Engineer

Hirevantis LLC; Toronto; On-site; CAD 90,000 - 150,000; Full time

Benefits offered by this job

Competitive compensation

Professional development opportunities

Collaborative environment

Job summary

Hirevantis LLC is seeking a skilled Machine Learning Engineer to design, develop, deploy, and optimize ML models for real-world business problems in a Toronto-based role. You will collaborate with data scientists and software engineers to transform complex data into actionable insights and intelligent applications.

The ideal candidate brings strong Python expertise, experience with ML frameworks, and a track record of deploying scalable ML solutions in production environments.

Qualifications

• Bachelor’s or Master’s degree in a related field or equivalent practical experience.
• 2–5 years of ML, DS, or software engineering experience.
• Strong Python programming and ML library experience.

Responsibilities

• Design, develop, train, and deploy ML models for business applications.
• Collect, clean, preprocess, and analyze structured/unstructured data.
• Apply algorithms, statistical methods, and feature engineering to boost performance.
• Build scalable ML pipelines for data processing, training, and inference.
• Evaluate models with appropriate metrics and improve accuracy and reliability.
• Collaborate with data scientists, engineers, and teams to integrate models.
• Implement monitoring, retraining, and deployment procedures.
• Work with cloud platforms and ML frameworks to productionize solutions.
• Document architectures, experiments, and deployment processes.
• Stay updated on ML tooling, techniques, and industry best practices.

Skills

Python Programming

Machine Learning Algorithms

Data Preprocessing

Statistical Modeling

Feature Engineering

Model Deployment

Cloud Computing

MLOps & Optimization

Education

Bachelor's or Master's in CS/DS/Statistics/Math

Tools

Scikit-learn

TensorFlow

PyTorch

Pandas

NumPy

SQL

Docker

Kubernetes

Job description

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.