Your Purpose

As a Machine Learning Engineer, your primary objective is to enable advanced analytics products for Product squads, Technology, Finance, Operations and others to drive value for our users following best software practices. You’ll bridge the gap between advanced analytics and software engineering within the machine learning(ML) team. On top of that, you’ll be able to develop machine learning models that directly impact our users.

You will play a pivotal role in the MLOps team: fostering best practices throughout the entire model lifecycle: enabling libraries for optimal data consumption, nurturing and defining taxonomies in our feature store, driving best in class model documentation, maintaining and creating serving architectures, maintaining the CI/CD pipelines, and monitor our ML pipelines performance.

Your experience enables you to effectively work with other engineers inside the technology team, translating ML models requirements into scalable and maintainable software solutions. Your expertise will be instrumental in automating processes, enhancing efficiency and maintaining reliability for our ML models

Who You Are

• Have a degree in a quantitative field such as mathematics, computer science, data science, or actuarial scienc
• 3+ years of ML Engineer experience
• A proven track record of machine learning solutions for batch and On-demand solutions
• Knowledge of DevOps/MLOps practices and tools for automatization and CI/CD
• Experience with cloud platforms such as AWS, Azure or Google cloud platform
• Strong proficiency in Python & SQL
• Experience in Databricks and MLflow
• Understanding of software engineering best practices, including version control, code reviews and automatic testing
• Strong communication skills and the ability to convey complex technical concepts to both technical and non-technical stakeholders

Nice to have

• An advanced degree(Master’s or Ph.D.) in Machine learning, Data Science, Computer science or any related field
• Data Engineering experience
• Experience with Terraform

What You Will Do

• Collaborate with data scientists to understand model requirements and implementation details
• Design and develop CI/CD pipelines for ML models, ensuring reproducibility, scalability, and reliability.
• Creation and maintenance of model serving architectures
• Creation of libraries that enable efficient modeling processing at any stage of the model lifecycle
• Drive best practices in code taxonomy, model registry, model monitoring and maintenance
• Create classic machine learning models and GenAi models
• Work closely with software engineers to integrate ML Models into production, addressing deployment challenges and optimizing performance
• Monitor and troubleshoot production ML deployments, identifying and resolving issues in a timely manner
• Stay up to date on advancements in ML technologies, MLOps, LLMOps, sharing knowledge within the team and contributing to skill development of other data scientists

Research in Diversity, Equity, and Inclusion suggests that individuals may hesitate to apply for jobs if they do not meet all the listed criteria. At Bitso, we value diversity and your unique strengths could be just what we're looking for. If this role excites you but you don't match every point in the description, we still want to hear from you.

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