Note: The job is a remote job and is open to candidates in USA. OVA.Work is seeking an AI Platform Engineer to design, build, and maintain scalable AI infrastructure and platforms. The role involves enabling data scientists and machine learning engineers to efficiently develop, deploy, monitor, and manage AI/ML models.
Responsibilities
- Design, develop, and maintain AI/ML platforms and infrastructure
- Build scalable MLOps pipelines for model training, deployment, monitoring, and retraining
- Develop CI/CD workflows for machine learning applications
- Manage Kubernetes clusters and containerized AI workloads
- Implement model serving, feature stores, model registries, and experiment tracking solutions
- Optimize GPU infrastructure and distributed training environments
- Integrate Large Language Models (LLMs), vector databases, and AI frameworks into enterprise platforms
- Monitor platform performance, reliability, scalability, and security
- Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams
- Implement Infrastructure as Code (IaC) using tools such as Terraform
- Ensure platform governance, compliance, and cost optimization
- Troubleshoot production AI platform issues and improve operational efficiency
Skills
- Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field
- 4+ years of experience in Platform Engineering, DevOps, MLOps, or Cloud Engineering
- Strong programming skills in Python
- Experience with Docker and Kubernetes
- Hands-on experience with AWS, Azure, or Google Cloud Platform
- Experience building CI/CD pipelines using GitHub Actions, GitLab CI, or Jenkins
- Experience with Terraform or similar Infrastructure as Code tools
- Knowledge of Linux systems and networking
- Experience with monitoring tools such as Prometheus and Grafana
- Familiarity with distributed systems and scalable architectures
- Experience with ML platforms such as MLflow, Kubeflow, SageMaker, Vertex AI, or Azure ML
- Experience deploying and managing Large Language Models (LLMs)
- Knowledge of vector databases such as Pinecone, Milvus, Weaviate, or Chroma
- Experience with LangChain, LangGraph, LlamaIndex, or similar AI orchestration frameworks
- Experience with distributed training frameworks and GPU optimization
- Knowledge of Apache Airflow, Kafka, Spark, or Ray
- Familiarity with security best practices for AI infrastructure
Company Overview