Requirements:

• Expertise in public cloud services, particularly in GCP.

• Experience working with VertexAI / Kubeflow Pipelines or other MLOps tools like MLFlow.

• Experience with machine learning frameworks (TensorFlow, PyTorch) and libraries (e.g., scikit-learn, HuggingFace).

• Knowledge of prompt engineering methods, LangChain, Vector databases and machine learning algorithms.

• Knowledge of LLMOps concepts and practices, including model versioning, deployment, monitoring, and efficient resource utilization for large language models.

• Experience in Infrastructure and Applied DevOps principles utilizing tools for continuous integration and continuous deployment (CI/CD), and Infrastructure as Code (IaC) like Terraform to automate and improve development and release processes.

• Knowledge of containerization technologies such as Docker and Kubernetes to enhance the scalability and efficiency of applications.

• Proven experience in engineering machine learning systems at scale.

• Strong programming abilities in SQL, Java and Python.

• Proven experience with the entire ML lifecycle (processing, training, evaluation, deployment, serving, monitoring).

• Familiarity with model performance monitoring, data drift detection, and anomaly detection (hands-on experience preferred).

• Strong understanding of IT infrastructure and operations, with the ability to set up monitoring/alerting tools and access controls for both infrastructure and applications.

• Have strong communication skills to collaborate effectively with cross-functional teams.

• Demonstrate a willingness to adapt to new technologies and methodologies in the ever-evolving AIOps landscape.

Must Have:

• Overall 4+ years experience in ML Ops.

• 2+ years of experience building end-to-end data pipelines.

• 2+ years of experience building and deploying ML models in a GCP.

• 3+ years of experience working with SQL, Java, Python for data analysis.

programming.

• Technical degree: Computer Science, software engineering or related

• Based in Bangalore and willing to work from the office 3 days a week