Teckhorizon Inc
Machine Learning Engineer
Teckhorizon IncCanada3 days ago
ContractEngineering, Information Technology
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

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