Machine Learning Engineer
14 hours ago
🇦🇷 Argentina – Remote
⏳ Contract/Temporary
🟢 Junior
🟡 Mid-level
🤖 Machine Learning Engineer
🚫👨🎓 No degree required
Description
• Remote position (only for professionals based in Argentina or Uruguay) • The work schedule aligns with EST time zone. • We are seeking a skilled Machine Learning Engineer to join one of our client's teams. • In this role, you will work closely with data scientists, data engineers, and platform engineers to develop and deploy machine learning models and pipelines for various classification projects and more. • Key Responsibilities • Develop efficient, clean, and maintainable Python code for machine learning pipelines, leveraging our in-house libraries and tools • Collaborate with the team on code reviews to ensure high code quality and adhere to best practices established in our shared codebase • Contribute to building and maintaining our MLOps infrastructure from the ground up, with a focus on extensibility and reproducibility • Take ownership of projects by gathering requirements, creating technical design documentation, breaking down tasks, estimating efforts, and executing with key performance indicators (KPIs) in mind • Optimize machine learning models for performance and scalability • Integrate machine learning models into production systems using frameworks like SageMaker • Stay up-to-date with the latest advancements in machine learning and MLOps • Assist in improving our data management, model tracking, and experimentation solutions • Contribute to enhancing our code quality, repository structure, and model versioning • Help identify and implement the best practices for ML services deployment and monitoring • Collaborate on establishing CI/CD pipelines and promoting deployments across environments • Address technical debt items and refactor code as needed
Requirements
• 2+ years of experience in machine learning engineering or a related role • Strong proficiency in Python programming • Experience with machine learning frameworks such as PyTorch, TensorFlow, or scikit-learn • Familiarity with cloud platforms like AWS, including services like SageMaker, S3, and Secrets Manager • Experience with data processing, cleaning, and feature engineering for structured and unstructured data • Knowledge of software development best practices, including version control (Git), testing, and documentation • Excellent problem-solving and debugging skills • Strong communication and collaboration abilities • Ability to work independently and take ownership of projects • Experience with Infrastructure as Code (IaC) tools, preferably Pulumi or Terraform • Experience with classification models and libraries such as XGBoost, SentenceTransformers, or LLMs • Knowledge of data versioning, experiment tracking, and model registry concepts • Familiarity with data pipeline and ETL tools like Dagster, Snowflake, and DBT • Experience with monitoring logs, metrics, and performance testing for batch inference workloads • Contributions to open-source machine learning projects • Experience with deploying and monitoring machine learning models in production
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