Cactus Communications
Website:
cactusglobal.com
Job details:
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 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 orchestration
- Containerization: Docker, Kubernetes, Helm charts, container registries, and microservices architecture for ML workloads
- CI/CD: Jenkins, GitLab CI, GitHub Actions, Azure DevOps with specialized ML pipeline integration and automated testing
- Infrastructure-as-Code: Terraform, CloudFormation, Ansible for reproducible ML infrastructure provisioning and management
- Cloud 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/Java
- Database & Storage: Feature stores (Feast, Tecton), model registries, data versioning (DVC), and distributed storage systems
- Workflow Orchestration: Apache Airflow, Prefect, Argo Workflows for complex ML pipeline scheduling and dependency management.
About Cactus:
Established in 2002, CACTUS (cactusglobal.com) 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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