Senior Data Science and Machine Learning Engineer
You will design, build, and scale data-driven systems powering advanced analytics and machine learning.
Responsibilities
• Develop, deploy, and maintain machine learning models in production environments.
• Collaborate with data scientists, analysts, and product managers to define and deliver data-driven features.
• Architect and maintain data platforms for experimentation, model serving, and feature engineering.
• Explore and integrate Large Language Models (LLMs) and generative AI into business applications and data workflows.
• Mentor junior engineers and data scientists, influencing architectural decisions and technical best practices.
Required Skills
• 10+ years of experience in data engineering or machine learning engineering.
• Strong proficiency in Python, including Pandas, NumPy, and PySpark.
• Solid understanding of ML model development, training, and deployment pipelines.
• Experience with deep learning frameworks like TensorFlow and PyTorch.
• Familiarity with MLOps practices, CI/CD, and Git version control.
• Experience with ML model monitoring and observability frameworks.
• Knowledge of LLMs and generative AI integration.
• Strong problem-solving and analytical skills.
• Excellent communication abilities across technical and non-technical teams.
Apply tot his job
Apply To this Job
Responsibilities
• Develop, deploy, and maintain machine learning models in production environments.
• Collaborate with data scientists, analysts, and product managers to define and deliver data-driven features.
• Architect and maintain data platforms for experimentation, model serving, and feature engineering.
• Explore and integrate Large Language Models (LLMs) and generative AI into business applications and data workflows.
• Mentor junior engineers and data scientists, influencing architectural decisions and technical best practices.
Required Skills
• 10+ years of experience in data engineering or machine learning engineering.
• Strong proficiency in Python, including Pandas, NumPy, and PySpark.
• Solid understanding of ML model development, training, and deployment pipelines.
• Experience with deep learning frameworks like TensorFlow and PyTorch.
• Familiarity with MLOps practices, CI/CD, and Git version control.
• Experience with ML model monitoring and observability frameworks.
• Knowledge of LLMs and generative AI integration.
• Strong problem-solving and analytical skills.
• Excellent communication abilities across technical and non-technical teams.
Apply tot his job
Apply To this Job