AgileEngine
Machine Learning Engineer Id (Remote)
Machine Learning Engineer Id | AgileEngine |Argentina
Machine Learning Engineer Id | AgileEngine | Argentina
If you like a challenging environment where you’re working with the best and are encouraged to learn and experiment every day, there’s no better place – guaranteed! 🙂
What you will do
- 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.
Must haves
- 3+ 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;
- Upper-intermediate English level.
Nice to haves
- 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.
The benefits of joining us
- Professional growth
Accelerate your professional journey with mentorship, TechTalks, and personalized growth roadmaps.
- Competitive compensation
We match your ever-growing skills, talent, and contributions with competitive USD-based compensation and budgets for education, fitness, and team activities.
- A selection of exciting projects
Join projects with modern solutions development and top-tier clients that include Fortune 500 enterprises and leading product brands.
- Flextime
Tailor your schedule for an optimal work-life balance, by having the options of working from home and going to the office – whatever makes you the happiest and most productive.
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