Description

You will design, build, and maintain production-grade AI solutions on Azure, focusing on model reliability and deployment automation.

Responsibilities

• Design and implement scalable, secure, and resilient ML, DL, and LLM solutions for production environments.
• Develop and maintain CI/CD pipelines to automate the build and deployment of AI models.
• Monitor deployed model performance, diagnose production issues, and apply configuration optimizations.
• Collaborate with data science and DevOps teams to ensure seamless integration and successful deployments.

Required Skills

• Proficiency in Python, SQL, R, or Scala for engineering tasks.
• Hands-on experience with Kubernetes and Docker for containerization and orchestration.
• Working knowledge of cloud platforms, specifically Azure and AWS.
• Experience building CI/CD pipelines and working within Agile frameworks.
• Understanding of machine learning techniques, statistical modeling, and predictive modeling.
• Ability to design scalable Model as a Service (MaaS) architectures.
• Familiarity with ML engineering tools such as MLflow, Airflow, Langchain, Langfuse, or LLM Guard.

Preferred Skills

• Bachelor’s degree in Statistics, Mathematics, Engineering, Data Science, or Computer Science.
• 3+ years of professional experience in AI Ops, ML engineering, or DevOps.

Key Skills

Education

Any Graduate