Machine Learning Engineer

Summary

We are looking for highly motivated and experienced Machine Learning Engineers to join our advanced analytics and AI team. The ideal candidates will have strong proficiency in building, training, and deploying machine learning models at scale using modern ML tools and frameworks. Experience with LLMs (Large Language Models) such as OpenAI and Hugging Face Transformers is highly desirable.

Role & responsibilities

• Design, develop, and deploy machine learning models for real-world applications.
• Implement and optimize end-to-end ML pipelines using PySpark and MLflow.
• Work with structured and unstructured data using Pandas, NumPy, and other data processing libraries.
• Train and fine-tune models using scikit-learn, TensorFlow, or PyTorch.
• Integrate and experiment with Large Language Models (LLMs) such as OpenAI GPT, Hugging Face Transformers, etc.
• Collaborate with cross-functional teams including data engineers, product managers, and software developers.
• Monitor model performance and continuously improve model accuracy and reliability.
• Maintain proper versioning and reproducibility of ML experiments using MLflow.

Preferred candidate profile

• Strong programming experience in Python.
• Solid understanding of machine learning algorithms, model development, and evaluation techniques.
• Experience with PySpark for large-scale data processing.
• Proficient with MLflow for tracking experiments and model lifecycle management.
• Hands-on experience with Pandas, NumPy, and Scikit-learn.
• Familiarity or hands-on experience with LLMs (e.g., OpenAI, Hugging Face Transformers). Understanding of MLOps principles and deployment best practices.
• Bachelors or Master’s degree in Computer Science, AI/ML, Data Science, or a related field.
• Experience in cloud ML platforms (AWS SageMaker, Azure ML, or GCP Vertex AI) is a plus.
• Strong analytical and problem-solving abilities.
• Excellent communication and teamwork skills.