We are looking for an experienced AI / MLOps Engineer to help design, deploy and operate production-grade AI platforms and machine learning solutions.
If you are passionate about Machine Learning, Cloud technologies, automation, and modern AI operations, we'd love to hear from you.
- Design and implement scalable ML pipelines for training, deployment, and monitoring
- Automate data ingestion, preprocessing, and feature engineering workflows
- Integrate AI/ML models into enterprise applications and APIs
- Develop and maintain CI/CD pipelines for Machine Learning systems
- Monitor model performance, detect model drift, and automate retraining processes
- Deploy AI workloads using Docker and Kubernetes
- Ensure security, compliance, and operational excellence across AI services
- Collaborate closely with Data Scientists, DevOps Engineers, Software Developers, and business stakeholders
Required Skills
- 3+ years of experience in AI/ML Engineering, MLOps, Machine Learning Engineering, or related roles
- Strong Python programming skills
- Experience deploying ML models into production environments
- Hands-on experience with Azure, AWS, or GCP
- Solid knowledge of Docker, Kubernetes, and CI/CD practices
- Experience with monitoring and observability tools
- Understanding of software engineering best practices and infrastructure automation
- Experience working in Agile environments
Technologies We Use
- Python
- TensorFlow
- PyTorch
- Scikit-Learn
- MLflow
- Kubeflow
- Apache Airflow
- Docker
- Kubernetes
- Microsoft Azure
- AWS
- Google Cloud Platform (GCP)
- Apache Spark
- Apache Kafka
- Terraform
- Prometheus
- Grafana
Nice to Have
- Experience with Generative AI (GenAI), Large Language Models (LLMs), or Agentic AI solutions
- AI, Machine Learning, Cloud, or Kubernetes certifications
- Experience working in large-scale enterprise environments
- Knowledge of Responsible AI, MLOps governance, and model lifecycle management
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