ML Ops

Overview:CACTUS is a remote-first organization and we embrace an accelerate from anywhere culture. You may be required to travel to our Mumbai office based on business requirements or for company/team events.We are looking for an MLOps Lead to design and manage the high-stakes CI/CD pipelines powering our AI/ML deployments. In this role, you will establish foundational mechanisms for model versioning, monitoring, and automated rollbacks to ensure system stability and traceability. You will lead the definition of infrastructure-as-code templates and standardized containerized workflows, ensuring all deployments strictly adhere to Responsible AI guidelines and bias auditing. If you are a technical leader with a deep background in microservices and a passion for building scalable, reproducible ML infrastructure, this role offers a strategic opportunity to shape our operational excellence.Responsibilities:Design and manage continuous integration and delivery (CI/CD) pipelines for AI/ML models across multiple environments.Establish model versioning, deployment, monitoring, and rollback mechanisms to ensure stability and traceability.Automate training, testing, and serving workflows using containerized solutions.Define infrastructure-as-code templates for scalable AI deployment on on-prem or cloud environments.Collaborate with Data Science and Engineering teams to standardize model input/output formats and performance metrics.Implement logging, monitoring, and alerting for deployed models to ensure high availability and accuracy over time.Ensure compliance with Responsible AI guidelines for deployment, including bias auditing and explainability tracking.Requirements:B.Tech / M.Tech / M.S. in Computer Science, Data Engineering, AI or related discipline.Certification in cloud DevOps or MLOps platforms (AWS DevOps Engineer, Azure DevOps Expert, GCP Professional ML Engineer) is highly desirable.Contributions to MLOps or DevOps open source projects is preferred.7–10 years in machine learning operations or DevOps engineering.Minimum 4 years building CI/CD pipelines for AI/ML model deployment in enterprise or government ecosystems.Proven experience with containerized and microservice architectures.Technical Competencies: MLOps Platforms: MLflow, Kubeflow, Azure ML, AWS SageMaker Pipelines, GCP Vertex AI Pipelines for end-to-end ML workflow orchestrationContainerization: Docker, Kubernetes, Helm charts, container registries, and microservices architecture for ML workloadsCI/CD: Jenkins, GitLab CI, GitHub Actions, Azure DevOps with specialized ML pipeline integration and automated testingInfrastructure-as-Code: Terraform, CloudFormation, Ansible for reproducible ML infrastructure provisioning and managementCloud Platforms: AWS (EKS, Lambda, ECR, S3), Azure (AKS, Container Registry, Blob Storage), GCP (GKE, Cloud Build, Cloud Storage)Model Serving: TorchServe, TensorFlow Serving, Seldon, KServe, REST APIs, and real- time inference infrastructure.Programming Languages: Python for automation, Bash scripting, YAML for configuration management, basic understanding of Go/JavaDatabase & Storage: Feature stores (Feast, Tecton), model registries, data versioning (DVC), and distributed storage systemsWorkflow Orchestration: Apache Airflow, Prefect, Argo Workflows for complex ML pipeline scheduling and dependency management.About Cactus:Established in 2002, Cactus Communications () is a leading technology company that specializes in expert services and AI-driven products which improve how research gets funded, published, communicated, and discovered. Its flagship brand Editage offers a comprehensive suite of researcher solutions, including expert services and cutting-edge AI products like Mind the Graph, Paperpal, and R Discovery. With offices in Princeton, London, Singapore, Beijing, Shanghai, Seoul, Tokyo, and Mumbai and a global workforce of over 3,000 experts, CACTUS is a pioneer in workplace best practices and has been consistently recognized as a great place to work.

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