Senior Machine Learning Engineer

Akkodis group; Toronto; Hybrid; CAD 100,000 - 150,000; Full time

Job summary

A leading company is seeking a Senior Machine Learning Engineer to spearhead the development of advanced machine learning and NLP solutions. This role involves leveraging deep learning models, particularly transformer architectures like BERT, to enhance data-driven decision-making across key initiatives. The ideal candidate will have a strong background in machine learning algorithms, NLP, and experience with TensorFlow or PyTorch.

Qualifications

• Strong understanding of machine learning algorithms and concepts.
• Proven expertise in NLP, especially with BERT and transformer models.
• Hands-on experience with TensorFlow or PyTorch for training deep learning models.

Responsibilities

• Design, train, and deploy machine learning and deep learning systems.
• Conduct experiments and implement appropriate algorithms to meet business goals.
• Analyze datasets, perform preprocessing, and validate data quality.

Skills

Machine Learning Algorithms

Natural Language Processing (NLP)

Python

TensorFlow

PyTorch

Model Optimization

Hyperparameter Tuning

Transfer Learning

Tools

NumPy

Pandas

Scikit-learn

Job description

The Client is seeking a Senior Machine Learning Engineer to lead the development and deployment of advanced machine learning and NLP solutions. This role focuses on leveraging deep learning models, especially transformer-based architectures like BERT, to support data-driven decision-making across key initiatives.

Job Title:Senior Machine Learning Engineer

Job Location:Toronto, ON/Hybrid

Job Description:

Must Haves:

· Strong understanding of machine learning algorithms and concepts

· Proven expertise in Natural Language Processing (NLP), especially with BERT and transformer models

· Hands-on experience with TensorFlow or PyTorch for training and fine-tuning deep learning models

· Proficiency in Python, including NumPy, Pandas, and Scikit-learn

· Experience in text preprocessing, tokenization, and working with word embeddings

· Skilled in model optimization, hyperparameter tuning, and transfer learning techniques

Key Responsibilities:

· Design, train, and deploy machine learning and deep learning systems

· Conduct experiments and implement appropriate algorithms to meet business goals

· Analyze datasets, perform preprocessing, and validate data quality

· Monitor and improve model performance using robust metrics

Collaborate with cross-functional teams to align models with business objectives