Machine Learning Engineer Id (Remote)

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.