Software Engineer, ML

Develop and maintain backend services and APIs that support AI models and intelligent assistants.
Improve scalability and performance of AI model serving and API interactions.Ensure system reliability by implementing logging, monitoring, and alerting solutions.

Assist in deploying AI models using Kubernetes and Docker, ensuring smooth model integration into production.
Contribute to CI/CD pipelines for AI applications, automating model testing and deployments.
Work on data pipelines and optimize storage and retrieval for AI workloads.
Work on infrastructure automation using Terraform, CloudFormation, or other Infrastructure as Code (IaC) tools.
Support cloud-based deployments on AWS, GCP, or Azure, optimizing resource usage.

Work closely with AI/ML engineers to understand infrastructure requirements for AI solutions.
Participate in code reviews, architecture discussions, and knowledge-sharing sessions.
Continuously learn and improve skills in backend development, cloud technologies, and DevOps.

4 years of experience in backend development using Python (preferred) or Java.
Experience with RESTful API development, microservices, and cloud-based architectures.
Familiarity with Kubernetes, Docker, and containerized deployments.
Hands-on experience with CI/CD tools (e.g., Jenkins, GitHub Actions, ArgoCD).
Basic understanding of cloud platforms (AWS, GCP, or Azure) and their services.
Strong problem-solving skills and a willingness to learn new technologies.

Preferred Experience

Exposure to AI/ML pipelines, model serving, or data engineering workflows.
Experience with monitoring and observability tools (e.g., Prometheus, Grafana, OpenTelemetry).