What are the responsibilities and job description for the DevOps Engineer (MLOps, Automotive / IoT Platforms) position at PROLIM Corporation?
We are seeking a DevOps Engineer with MLOps expertise to design, build, and manage scalable AI/ML infrastructure. This role focuses on enabling seamless deployment, monitoring, and lifecycle management of machine learning models in production environments, with a strong focus on automotive, IoT, and connected systems.
Key Responsibilities
- Design and implement CI/CD pipelines for AI/ML workflows (training & deployment)
- Manage cloud infrastructure across AWS, Azure, or GCP
- Implement MLOps practices (model versioning, reproducibility, monitoring)
- Deploy and manage applications using Docker & Kubernetes
- Automate infrastructure using Terraform, ARM, or CloudFormation
- Monitor system performance, reliability, and cost optimization
- Collaborate with Data Scientists & ML Engineers to productionize models
- Ensure security, compliance, and governance of AI systems
- Support incident response & root cause analysis
- 3 years in DevOps / SRE / Platform Engineering
- Strong cloud experience (AWS / Azure / GCP)
- Hands-on with Docker, Kubernetes, microservices
- CI/CD tools (GitHub Actions, Jenkins, GitLab CI, Azure DevOps)
- Familiarity with ML tools (MLflow, Kubeflow, SageMaker, Vertex AI, Azure ML)
- Proficiency in Python / Bash / PowerShell
- Strong knowledge of Linux, networking, observability
- Required / Strongly Preferred: Experience in Automotive, IoT, or Connected Systems (telematics, connected vehicles, edge platforms)
- Experience with large-scale model deployment (LLMs, GenAI, real-time inference)
- Knowledge of data pipelines (Airflow, Spark, Kafka)
- Experience with model monitoring (data drift, latency, performance)
- Understanding of AI security & compliance