Remote Senior Machine Learning Engineer

Summary

Join Trafilea, a dynamic Tech E-commerce Group, as a Senior Machine Learning Engineer to lead the development and deployment of advanced models, driving innovation and efficiency across the organization.

Requirements

• Graduated in Computer Science, Mathematics, Statistics, or a related field with a strong focus on machine learning, or advanced student (min 3rd degree completed)
• Minimum of 5 years of experience in machine learning engineering, with a proven track record of developing and deploying robust, scalable machine learning models
• Expertise in writing production-ready code, with a strong understanding of the testing pyramid and experience in writing comprehensive tests
• Deep knowledge of the machine learning development lifecycle, including the KDD process, Deep Learning ecosystems, MLOps practices, and data engineering
• Ability to integrate business strategy with technical execution, contributing to business discussions and ensuring alignment of machine learning projects with business objectives
• Strong communication skills, capable of conveying complex technical concepts in simple terms to a diverse audience, and fostering a culture of open, effective communication within the team
• Leadership in fostering a culture of continuous improvement, knowledge sharing, and mentorship within the team
• Proficiency in advanced ML tools and programming languages used in data science (e.g., Python, R, SQL)
• Proficiency in ML cloud services and Saas tools like MLFlow and AWS ecosystem
• Proven experience in marketing, e-commerce marketplace, or growth teams

Responsibilities

• Develop and maintain production-ready machine learning code that is testable, well-documented, and accounts for edge cases and errors
• Design code that aligns with the service architecture, utilizing effective abstractions and code isolation
• Write comprehensive tests covering edge cases, errors, and happy paths following the testing pyramid
• Gain a high-level understanding of the team's domain and develop expertise in a specific portion of it, contributing significantly to the team's projects
• Apply the scientific method to bring insights from research directly into all areas of the team's project, showcasing innovative ideas, technologies, or techniques
• Master the application of theory to practice, iterating through the KDD process, understanding the Deep Learning ecosystem, focusing on robust and scalable ML processes, and developing efficient data pipelines
• Integrate business and technical strategies, contributing to business discussions and aligning technical projects with business goals
• Ensure tasks are critically reviewed, appropriately sized, and prioritized, and dependencies are managed for continuous integration and incremental delivery
• Deliver and encourage the delivery of constructive feedback within the team and to business stakeholders, fostering a culture of continuous improvement
• Communicate effectively in both technical and non-technical terms, ensuring clarity and audience engagement, while actively listening and paying attention to nonverbal cues
• Share knowledge frequently, contribute to team documentation, and encourage a culture of knowledge sharing and mentorship within the team

Benefits

• Remote work
• 15 working days of paid holidays
• Learning subsidy