Machine Learning Engineer, Content and Catalog Management

Requirements

• 2+ years of hands-on experience in developing and deploying machine learning models in a production environment.
• Practical experience in implementing ML systems using languages like Python or Scala and are familiar with relevant ML libraries and frameworks (e.g., TensorFlow or PyTorch).
• Solid understanding of various machine learning algorithms (e.g., classification, regression, clustering) and their practical applications.
• Proficient in data manipulation and analysis using tools like SQL and Pandas.
• Broad ML skillset and are happy to work on all aspects of ML problems. Not only modeling, but also feature work in data pipelines, some implementation in data pipeline workflows, experimentation setup and analysis.
• Experience with model evaluation metrics and techniques for ensuring model quality and generalization.
• Experience with cloud platforms (e.g., GCP, AWS, Azure) and their ML services.
• Comfortable communicating technical concepts clearly and effectively within the team and with non-technical stakeholders.
• Proactive problem-solver with a strong sense of ownership and a drive to learn.

What You'll Be Doing

• Drive the full lifecycle of ML solutions for CoCaM services, including research, design, development, evaluation, and deployment.
• Manage Machine Learning projects ranging from Supervised Learning, to Reinforcement Learning, to LLMs.
• Optimize and monitor deployed ML model performance, implementing improvements based on analysis.
• Document and standardize ML processes, pipelines, and model specifications.
• Collaborate with cross-functional teams spanning research, engineering, data science, product managers and other stakeholders to understand business needs and identify opportunities for ML applications.
• Work closely with engineering teams to integrate ML models into existing systems and workflows.
• Be an active participant of a group of machine learning engineers, staying updated with the latest advancements, participating in code reviews, and contributing to knowledge sharing across the team.

Perks and Benefits

• Extensive learning opportunities, through our dedicated team, GreenHouse.
• Flexible share incentives letting you choose how you share in our success.
• Global parental leave, six months off - fully paid - for all new parents.
• All The Feels, our employee assistance program and self-care hub.
• Flexible public holidays, swap days off according to your values and beliefs.