Machine Learning Engineer

Teckhorizon Inc

Canada · Contract · Mid-Senior

About The Role

Our Client is seeking a Senior Machine Learning Engineer to design, build, and optimize advanced machine learning and deep learning models—primarily with NLP (BERT/Transformers). The ideal candidate has deep technical expertise, strong statistical foundations, and experience developing ML solutions end-to-end, from data preprocessing to model deployment and optimization.

The Machine Learning Engineer will run experiments, evaluate algorithms, manage data pipelines, and collaborate with cross-functional teams to align ML solutions with business objectives.

Key Responsibilities

Design, develop, and deploy machine learning and deep learning systems, with a focus on NLP and transformer models.
Build, train, and fine-tune BERT and Transformer-based models for classification, sentiment analysis, and language understanding.
Analyze datasets, explore relationships between features and outcomes, and ensure ML solutions align with business goals.
Conduct ML experiments, evaluate model performance, and implement appropriate ML algorithms for various problem types.
Perform data preprocessing, including cleaning, tokenization, and feature engineering (e.g., embeddings).
Manage and verify data quality, ensuring clean, well-structured training datasets.
Define validation strategies, experiment tracking, and evaluation metrics.
Optimize ML models with hyperparameter tuning, monitoring performance trade-offs.
Supervise data acquisition pipelines and identify additional training data sources when required.
Leverage transfer learning, adapting pre-trained transformer models to custom datasets and business use cases.
Collaborate with teams to meet project deadlines, manage competing priorities, and support stakeholder expectations.

Required Skills (Must-Haves)

Machine Learning Expertise (15%)
Strong understanding of ML fundamentals, algorithms, and modeling techniques.
NLP Skills (15%)
Hands-on experience with NLP, specifically BERT and Transformer-based architectures.
Deep Learning Frameworks (20%)
Proficiency in TensorFlow or PyTorch.
Ability to implement, train, and fine-tune BERT and transformer models.
Data Preprocessing & Programming (30%)
Skilled in text preprocessing, tokenization, word embeddings.
Strong programming experience with Python, NumPy, Pandas, Scikit-learn.
Model Optimization (20%)
Experience with hyperparameter tuning, performance optimization, and understanding model trade-offs.
Transfer Learning (15%)
Proficiency in leveraging pre-trained transformer models for custom tasks.

Key Skills

Ranked by relevance

machine learning deep learning technical expertise tensorflow pytorch python pandas numpy

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