About Tror
Tror Private Limited is a global IT consulting and technology company delivering innovative digital, data, and AI-driven solutions. We empower businesses to optimize operations, automate workflows, and scale intelligently through cloud, data, and machine learning technologies.
Role Overview
As an MLOps Engineer at Tror, you will work collaboratively with Data Scientists and Data Engineers to deploy, manage, and optimize machine learning systems. You will automate workflows, streamline deployment processes, and build tools for continuous integration, monitoring, and maintenance of production environments. This role requires a strong understanding of ML lifecycle management and cloud-based infrastructure.
Key Responsibilities
• Operate and maintain systems supporting the provisioning of new clients, applications, and features.
• Monitor production environments to ensure all services and applications are performing optimally and SLAs are consistently met.
• Manage software deployment and configuration in QA and production environments.
• Collaborate with Data Scientists and Engineers to containerize ML models and build automated deployment pipelines for new modules.
• Design, build, and optimize containerization and orchestration solutions using Docker, Kubernetes, and AWS or Azure.
• Automate application and infrastructure deployments; develop build and deployment automation scripts to integrate between services.
• Serve as a subject-matter expert on DevOps, CI/CD, and Configuration Management practices.
• Ensure high system availability, reliability, and scalability across distributed ML workloads.
Required Skills & Qualifications
• Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related field.
• 3–10 years of experience in cloud services, DevOps, or MLOps engineering.
• Strong expertise with Docker, Kubernetes, and cloud platforms such as AWS, Azure, or Google Cloud Platform.
• Experience with MLFlow, Kubeflow, MLTracking, and MLExperiment tools.
• Hands-on experience in Python and Shell scripting for automation.
• Proficiency with CI/CD tools such as Jenkins, Travis CI, or CloudBees.
• Knowledge of configuration management tools like Ansible or Chef.
• Experience with monitoring tools (Prometheus, Grafana, AlertManager, PagerDuty) and logging systems (Splunk, ElasticSearch, Kibana, Logstash).
• Understanding of big data technologies — Hadoop, Hive, Spark, Kafka — is preferred.
• Familiarity with machine learning frameworks such as TensorFlow, PyTorch, Keras, MXNet, or Scikit-Learn.
• Strong background in Unix/Linux environments and Agile engineering practices.
• Excellent analytical, problem-solving, and communication skills.
Preferred Qualifications
• Experience building and maintaining end-to-end ML pipelines in cloud environments.
• Understanding of MLOps best practices for model deployment, scaling, and monitoring.
• Exposure to HDFS, Ambari, ZooKeeper, or Kafka ecosystems is an added advantage.
• Proven ability to work effectively in cross-functional, fast-paced teams.
What We Offer
• Competitive salary and performance-based bonuses.
• Flexible work environment (remote or hybrid).
• Opportunity to work on enterprise-scale AI and cloud automation projects.
• Continuous learning and certification support.
• A collaborative and innovation-driven work culture.
How to Apply
Send your updated resume and portfolio to info@tror.ai with the subject line:
📩 Application for MLOps Engineer
