Description

You will architect and lead the development of scalable machine learning systems, driving the end-to-end lifecycle from data pipelines to model deployment and monitoring.

This role is remote.

Responsibilities

• Architect and build scalable machine learning systems leveraging optimization, natural language processing, and advanced analytics.
• Lead end-to-end machine learning lifecycle including data pipelines, model training, deployment, and monitoring.
• Build and maintain production-grade machine learning pipelines using continuous integration and continuous deployment practices.
• Optimize model performance, latency, and scalability while ensuring data security and governance requirements.
• Evaluate emerging technologies such as Generative AI, Large Language Models, and agent-based workflows for adoption.

Required Skills

• 8-10 years of experience in software engineering and machine learning.
• 2+ years in a technical leadership role.
• Strong proficiency in Python and Machine Learning concepts.
• Hands-on experience with PyTorch and TensorFlow.
• Experience with cloud platforms AWS and Azure.
• Proficiency with containerization and orchestration tools Docker and Kubernetes.
• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or related field (or equivalent combination of education and experience).

Preferred Skills

• Experience with R programming, Keras, Google Cloud Platform, Databricks, Apache Spark, Hive, Airflow, MLOps practices, CI/CD, Natural Language Processing, optimization algorithms, Generative AI, Large Language Models, agent-based workflows, data engineering, system design, and technical leadership experience.

Key Skills

Education

Any Graduate