Machine Learning Engineer

About the Role:

We are looking for an experienced Python Backend Developer who specializes in scripting and has expertise in Flask and FastAPI, with a strong focus on handling large datasets in SQL databases. The ideal candidate will excel in building scalable backend systems, optimizing data-heavy processes, and writing efficient Python scripts for automation and data manipulation.

Key Responsibilities:

· Develop, maintain, and optimize Python scripts for backend processes, data handling, and automation.

· Build and scale web applications and RESTful APIs using Flask and FastAPI.

· Design and implement efficient solutions for managing and querying large datasets in SQL databases (e.g., PostgreSQL, MySQL).

· Write high-performance SQL queries and optimize database structures to handle large volumes of data.

· Collaborate with data engineers, product managers, and frontend developers to define requirements and ensure smooth integration of large datasets across the system.

· Optimize Python scripts for data processing, analysis, and workflow automation.

· Troubleshoot and resolve issues related to data handling, performance bottlenecks, and system reliability.

· Ensure the security and integrity of data through effective handling of authentication, authorization, and data protection practices.

· Participate in code reviews, focusing on improving Python scripting efficiency and SQL database optimization.

Requirements:

· 3+ years of professional experience with Python, focusing on backend development, scripting, and data automation.

· Strong expertise in Flask and FastAPI frameworks.

· Proven experience in handling large datasets using SQL databases (e.g., PostgreSQL, MySQL), including writing complex queries and optimizing for performance.

· Deep understanding of database management principles, indexing, and query optimization for big data.

· Experience with asynchronous programming, concurrency, and task queues (e.g., Celery, Redis).

· Ability to write clean, logical, and reusable Python code, focusing on performance and scalability.

· Familiarity with containerization tools such as Docker and orchestration with Kubernetes is a plus.

· Proficiency in version control systems (Git) and collaborative development workflows.

· Strong analytical skills and problem-solving ability, particularly when working with large-scale data solutions.

· Excellent communication skills and ability to work within a team-oriented, agile environment.

Nice-to-Have:

· Experience with other Python web frameworks (Django, Tornado).

· Knowledge of data pipeline tools, ETL frameworks, or big data technologies (e.g., Spark, Hadoop).

· Familiarity with cloud-based databases or large-scale database management (e.g., AWS RDS, Google Cloud SQL).

· Strong background in system automation and scripting tools for DevOps.

· Exposure to machine learning frameworks and libraries such as scikit-learn, Keras, and TensorFlow, with experience implementing models for predictive analytics and data-driven solutions.

· Experience with deploying machine learning models in production environments, using tools like Docker, Kubernetes, or cloud platforms (e.g., AWS SageMaker, Google AI Platform).

· Proficiency in data analysis libraries like pandas and NumPy, with the ability to work with large datasets for insight generation and statistical analysis.