Senior Machine Learning Engineer JP245

Pathlion; Toronto; On-site; CAD 110,000 - 180,000; Full time

Job summary

Pathlion is seeking a Senior Machine Learning Engineer to deploy, monitor, and operationalize AI models using modern MLOps practices. The role will establish reusable deployment patterns, tooling, monitoring, and automation that enable AI solutions to move reliably from development into production and scale across the enterprise.

You will design and run ML experiments, select appropriate algorithms, validate data quality, and collaborate with teams to meet business objectives.

Qualifications

• Strong background in statistics and machine learning theory.
• Experience with model deployment and production ML systems.
• Proficient in data cleaning and preprocessing.
• Ability to design validation strategies.
• Proven track record of meeting deadlines.
• Team-oriented with client relationships experience.

Responsibilities

• Creates machine learning models and uses data to train them.
• Analyzes data to identify relationships between inputs and outputs.
• Aligns models with business objectives and defines metrics.
• Designs and develops ML and DL systems.
• Runs ML experiments and compares algorithms.
• Implements suitable ML algorithms.

Skills

MLOps

Python

Data analysis

Statistics

Cloud computing

Model deployment

Experimentation

Team collaboration

Data preprocessing

Data visualization

Tools

TensorFlow

PyTorch

scikit-learn

Jupyter

Git

Job description

The Senior Machine Learning Engineer will deploy, integrate, monitor, and operationalize AI and machine-learning solutions using modern MLOps practices. The role will establish reusable deployment patterns, tooling, monitoring, and automation that enable AI solutions to move reliably from development into production and scale across the enterprise.

Responsibilities:

• Creates machine learning models and utilizes data to train models
• Focuses on analyzing data to find relations between the input and the desired output
• Understands business objectives and develops models that help achieve them, along with metrics to track their progress
• Designs and develops machine learning and deep learning systems
• Runs machine learning tests and experiments
• Implements appropriate machine learning algorithms

General Skills:

• Experience managing available resources such as hardware, data, and personnel so that deadlines are met
• Experience analyzing the machine learning algorithms that could be used to solve a given problem and ranking them by their success probability
• Experience exploring and visualizing data to gain an understanding of it, then identifying differences in data distribution that could affect performance when deploying the model in the real world
• Experience verifying data quality, and/or ensuring it via data cleaning
• Experience supervising the data acquisition process if more data is needed
• Experience finding available datasets online that could be used for training
• Experience defining validation strategies
• Experience defining the preprocessing or feature engineering to be done on a given dataset
• Background in statistics and computer programming
• A team player with a track record for meeting deadlines, managing competing priorities and client relationship management experience