Description

Required Technical Skills:

• Deep expertise in Python, standard ML/scientific computing libraries (e.g., TensorFlow, PyTorch, scikit-learn, Pandas)
• Deep theoretical and practical understanding of various machine learning algorithms, including modern deep learning architectures and methodologies
• Proven expertise with MLOps tools, cloud-native services (e.g., Kubeflow, MLflow, Docker, Kubernetes)
• Hands-on designing and deploying scalable ML solutions on cloud platforms (AWS, Azure, GCP)
• Solid understanding of data warehousing, ETL processes, and familiarity with distributed computing frameworks (e.g., Spark)
• Ability to design, articulate, and implement complex, highly available, fault-tolerant AI production systems
• Proven ability to set coding standards, lead code reviews, and manage software development lifecycles
• Strong technical leadership skills with the ability to set technical vision and guide a team
• 10+ years’ experience in machine learning engineering
• Bachelor's or master’s degree in computer science
• Demonstrated experience successfully taking multiple ML models from research/prototype phase into large-scale production environments
• Prior experience working with big data technologies and designing robust data pipelines for ML training

Key Skills

Education

Bachelor's or Master's degrees