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Senior Machine Learning Engineer

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Randstad

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Location:
Canada , Toronto

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Category:
IT - Software Development

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Contract Type:
Not provided

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Salary:

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Job Description:

Our client is looking for a Senior Machine Learning Engineer for a 6 month contract in Toronto. This is a hybrid role. From October 20, 2025, the candidate is required to work onsite 4 days a week and 1 day from home. From January 5, 2026, the candidate is required to work onsite 5 days a week fully.

Job Responsibility:

  • 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

Requirements:

  • Deep Understanding of Machine Learning Concepts: Proficiency in fundamental machine learning concepts, algorithms, and techniques
  • Expertise in Natural Language Processing (NLP): Knowledge of NLP techniques and models, especially BERT and other transformer-based models, for tasks like text classification, sentiment analysis, and language understanding
  • Experience with Deep Learning Frameworks: Proficiency in deep learning libraries such as TensorFlow or PyTorch. Experience with implementing, training, and fine-tuning BERT models using these frameworks is crucial
  • Data Preprocessing Skills: Ability to perform text preprocessing, tokenization, and understanding of word embeddings
  • Programming Skills: Strong programming skills in Python, including experience with libraries like NumPy, Pandas, and Scikit-learn
  • Model Optimization and Tuning: Skills in optimizing model performance through hyperparameter tuning and understanding of trade-offs between model complexity and performance
  • Understanding of Transfer Learning: Knowledge of how to leverage pre-trained models like BERT for specific tasks and adapt them to custom datasets
  • 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
What we offer:
  • Earn a competitive rate within the industry
  • Potential for extension

Additional Information:

Job Posted:
January 11, 2026

Expiration:
March 10, 2026

Work Type:
Hybrid work
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