Job responsibilities
Manage AI Platform: Set up and oversee both development and production infrastructure for AI/ML workloads, ensuring reliability, scalability, and performance.
Data Infrastructure: Build robust data ingest and transformation pipelines to support AI/ML model training and inference at scale.
Model Deployment: Collaborate closely with data scientists to convert AI/ML models into deployable services using best practices in MLOps.
System Integration: Integrate AI solutions with existing platforms and business systems through APIs, microservices, or other means.
Access Enablement: Develop APIs or lightweight UIs to make AI capabilities easily accessible to partners and business users.
Coordinate with different functional teams to implement models and monitor outcomes
Job Requirements
Fluent in Python programming, Linux Systems,
Strong background in software engineering, data engineering, or AI infrastructure
Experience with cloud platforms (Azure) and containerization tools (Docker, Kubernetes)
Familiarity with building RESTful APIs and/or frontend tools for AI interfaces
Solid understanding of MLOps practices and tools (e.g., MLflow, FastAPI)
Excellent written and verbal communication skills for coordinating across teams
A drive to learn and master new technologies and techniques
Good to have
Exposure to big data processing and streaming tools (e.g., Kafka, Spark)
Proficient in Python and AI/ML frameworks (TensorFlow, PyTorch, etc.)
Experience with CI/CD and infrastructure-as-code (Terraform, Jenkins)
Familiarity with security, monitoring, and performance tuning for AI services
Job Type: Full-time
Pay: $7,000.00 - $10,000.00 per month