Position Name: Senior MLOps Engineer
Years of Experience: 4+
Location: Bangalore, India
Notice Period: 15-30 days

Skill Required:

• Kubeflow
• MLflow
• Python
• LLM (Large Language Model)

Key Responsibilities:

1. ML Workflow Management: Design, implement, and optimize ML workflows using Kubeflow and MLflow to streamline the development, training, and deployment of machine learning models.
2. Model Deployment: Deploy ML models into production environments using Kubeflow pipelines, ensuring scalability, reliability, and performance.
3. LLM Management: Implement and manage large language models (LLMs) for natural language processing tasks, including training, fine-tuning, and inference.
4. Infrastructure Orchestration: Utilize Kubernetes for container orchestration and manage scalable, fault-tolerant infrastructure for ML workloads.
5. Automation: Develop automation scripts and tools to automate deployment, monitoring, and maintenance tasks, minimizing manual intervention and improving efficiency.
6. Version Control: Implement version control for ML models, datasets, and experiments using Git and MLflow, ensuring reproducibility and traceability.
7. Monitoring and Logging: Set up monitoring and logging systems to track the performance and health of ML workflows and infrastructure components, and implement alerts for proactive issue resolution.
8. Security and Compliance: Implement security best practices and compliance standards for sensitive data handling in ML workflows, ensuring adherence to privacy regulations.
9. Collaboration: Collaborate closely with data scientists, software engineers, and other stakeholders to integrate ML models into production systems effectively.
10. Documentation: Document deployment processes, infrastructure configurations, and troubleshooting procedures to facilitate knowledge sharing and ensure system reliability.

About the Role:
We are actively searching for a highly skilled and motivated Senior MLOps Engineer with expertise in Python and MLOps to become a key member of our team. The successful candidate will be responsible for deploying, managing, and monitoring machine learning (ML) workflows using cutting-edge tools like Kubeflow, MLflow, and LLM (Large Language Model) management systems. This role requires expertise in both machine learning techniques and DevOps practices, with a focus on scalability, reliability, and automation.

About Company:
Autonomize, Inc is seeking a highly motivated, driven Senior MLOps Engineer with Python & MLOps expertise to join our team on a journey to help organizations scale across the globe. Autonomize is on a mission to help organizations make sense of the world's data. We help organizations harness the full potential of data to unlock business outcomes. Unstructured dark data contains nuggets of information that when paired with human context will unlock some of the most impactful insights for most organizations, and it’s our goal to make that process effortless and accessible. We are an ambitious team committed to human-machine collaboration. Our founders are serial entrepreneurs passionate about data and AI and have started and scaled several companies to successful exits. We are a global company with expertise in building amazing data products, captivating human experiences, disrupting industries, being ridiculously funny, and of course scaling AI.