Machine Learning Engineer

As a Machine Learning Engineer at this level, you will be a key contributor to our team, responsible for building and deploying end-to-end machine learning models. You will work with a degree of autonomy on well-defined projects, translating business needs into functional and scalable ML solutions. This role is perfect for hands-on ML Engineers looking to deepen their expertise and take on more complex challenges.

Responsibilities:

• Independently build, train, and deploy machine learning models for complex projects.
• Design and maintain robust, end-to-end ML pipelines, from data processing to model serving.
• Contribute to technical design discussions and provide input on system architecture and best practices.
• Collaborate with business, product, and other engineering teams to understand requirements and translate them into technical specifications.
• Write high-quality, production-ready code and participate in code reviews to maintain our standards of excellence.
• Mentor interns or junior engineers, sharing your knowledge and expertise.

Requirements:

• Bachelor's or Master's degree in Engineering, Mathematics, Statistics, or a related field.
• 4-6 years of professional experience in machine learning engineering.
• Proven experience in building and deploying ML models in a production environment.
• Strong proficiency in Python, SQL, and experience with a distributed computing framework (e. g., Spark).
• Familiarity with workflow orchestration tools (e. g., Airflow) and ML platforms (e. g., MLflow) is preferred.
• Knowledge of classification models, regression models, anomaly detection, boosted models, deep learning, and simulation problems, particularly with large datasets.
• Strong problem-solving skills and the ability to work independently on projects.