Infra Engineer (MLOps Engineer)
- orcapod
- 6 - 8 years
- Bengaluru
- 6 months ago
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Job Description
**APPLICABLE ONLY FOR IMMEDIATE JOINERS**
Job Title: Infra Engineer (MLOps Engineer)
Location: Bangalore, India
Job Type: Full-Time
Work Mode: 5 days WFO
Job Overview:
We are looking for an experienced Infrastructure Engineer with strong MLOps expertise to support, scale, and optimize our machine learning workflows in production. The ideal candidate will work at the intersection of DevOps, Data Engineering, and Machine Learning, ensuring that AI/ML systems are reliable, secure, and efficient across environments.
Key Responsibilities:
- Design and implement MLOps pipelines for training, testing, deployment, and monitoring of ML models
- Build and maintain scalable cloud infrastructure (AWS, GCP, or Azure) to support AI/ML workloads
- Automate CI/CD workflows for ML models using tools like GitHub Actions, Jenkins, or GitLab CI
- Manage containerized environments using Docker and Kubernetes
- Monitor, log, and troubleshoot production ML systems to ensure high availability
- Ensure version control for models, datasets, and experiments using tools like MLflow, DVC, or Weights & Biases
- Collaborate with data scientists and backend teams to streamline model deployment and scaling
Required Skills & Experience:
- 6-8 years of experience in DevOps, Infrastructure Engineering, or MLOps roles
- Strong hands-on experience with cloud platforms (AWS, GCP, or Azure)
- Proficient in containerization (Docker) and orchestration (Kubernetes)
- Solid understanding of CI/CD pipelines, infrastructure as code (Terraform, Ansible)
- Experience with ML pipeline orchestration tools such as Kubeflow, Airflow, or SageMaker Pipelines
- Familiarity with ML lifecycle management and versioning tools (MLflow, DVC, etc.)
- Proficiency in scripting languages: Python, Bash, or Shell
- Strong debugging and system monitoring skills (Prometheus, Grafana, ELK, etc.)
Preferred Qualifications:
- Experience supporting large-scale machine learning platforms in production
- Understanding of security, networking, and compliance in ML systems
- Knowledge of model serving frameworks (TensorFlow Serving, TorchServe, Triton, etc.)
- Certification in AWS/GCP or Kubernetes is a plus
Job Classification
Industry: IT Services & ConsultingFunctional Area / Department: Data Science & AnalyticsRole Category: Data Science & Machine LearningRole: Machine Learning EngineerEmployement Type: Full timeContact Details:
Company: Forbes GlobalLocation(s): Bengaluru
Keyskills: Infrastructure Infrastructure Design Machine Learning Algorithms Machine Learning Operations Machine Learning Infrastructure Development Infrastructure Planning
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