Description

You will lead and drive ML projects from inception through production, partnering with data scientists and business teams.

This role is hybrid.

Responsibilities

• Design, implement, and train ML models in collaboration with data science partners.
• Enhance ML platform scalability, stability, and performance by collaborating with infrastructure teams.
• Develop and optimize data pipelines required to feed ML models.
• Establish model monitoring, governance, and operationalization processes.

Required Skills

• 5+ years of software engineering experience with applied ML engineering.
• Advanced proficiency in Python, Java, and Scala.
• Solid computer science fundamentals, including algorithms and data structures.
• Experience with Generative AI, LangChain, or RAG techniques.
• Proficiency with ML/DL libraries: XGBoost, Scikit-learn, TensorFlow, and PyTorch.
• Cloud expertise with AWS or GCP, specifically using ML platforms like SageMaker.
• Hands-on experience with containerization and deploying production ML applications via automated pipelines.
• Bachelor's or Master's degree in Computer Science or Engineering.

Key Skills

Education

Bachelor's or Master's degrees