Senior Machine Learning Engineer at Caylent

Yes, the position is 100% remote, and Caylent operates fully remote with employees in Canada, the United States, and Latin America.

Candidates need strong experience in building ML models for real-world applications, at least one of AWS ML Services/SageMaker or ML libraries like Keras/Tensorflow/PyTorch/Scikit-learn or MLOps tools, data processing with Spark/Hadoop/Python/Pandas/SQL, and understanding of feature definition, hyperparameter tuning, and deep learning concepts.

Benefits include pay in USD, 100% remote work, generous holidays and flexible PTO, competitive phantom equity, paid exams and certifications, peer bonus awards, state-of-the-art laptop and tools, equipment & office stipend, individual professional development plan, annual stipend for learning and development, and working with an amazing worldwide team.

Caylent puts people first, celebrates the culture of each team member, fosters a community of technological curiosity, and offers an incredible corporate culture with an amazing worldwide team. Employees participate in daily standups, bi-weekly agile ceremonies, and weekly 1:1s with managers for career guidance.

A strong candidate has hands-on experience building ML models for real-world applications, expertise in AWS SageMaker or major ML libraries and MLOps tools, proficiency in big data processing and feature engineering, plus excellent communication skills.