RQ09318 - Machine Learning Engineer â Senior
RQ09318 - Machine Learning Engineer â Senior
Posted on :
25-05-2025
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1 Vacancy
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Job Description
Job Title: RQ09318 - Machine Learning Engineer Senior
Client: Ministry of Public and Business Service Delivery and Procurement
Work Location: 222 Jarvis St. Toronto Ontario Hybrid
Estimated Start Date:
Estimated End Date:
#Business Days: 250.00
Extension: Probable after the initial mandate
Hours per day or Week:7.25 hours per day
Security Level: No Clearance Required
Must haves:
Responsibilities:
Deep Understanding of Machine Learning Concepts - 15%
Client: Ministry of Public and Business Service Delivery and Procurement
Work Location: 222 Jarvis St. Toronto Ontario Hybrid
Estimated Start Date:
Estimated End Date:
#Business Days: 250.00
Extension: Probable after the initial mandate
Hours per day or Week:7.25 hours per day
Security Level: No Clearance Required
Must haves:
- 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.
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
- 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
Deep Understanding of Machine Learning Concepts - 15%
- 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.
- Proficiency in deep learning libraries such as TensorFlow or PyTorch.
- Experience with implementing training and fine-tuning BERT models using these frameworks is crucial.
- 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.
- Skills in optimizing model performance through hyperparameter tuning and understanding of trade-offs between model complexity and performance.
- Knowledge of how to leverage pre-trained models like BERT for specific tasks and adapt them to custom datasets.
Required Experience:
Senior IC
Employment Type
Contract
Key Skills
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