Senior MLOPS Engineer
■ Your Role and Responsibilities
- Develop and maintain scalable pipelines for deploying LLMs, focusing on efficient, low-latency inference.
- Utilize tools like Hugging Face and MLFlow for seamless model integration and version control.
- Automate deployment processes, including model validation and continuous integration.
- Implement comprehensive monitoring frameworks to track performance and reliability of models in production.
- Use advanced observability tools to proactively detect and address performance issues.
- Deploy alerting systems to ensure rapid response to anomalies in model behavior.
- Architect and optimize cloud and on-premise infrastructure to support large-scale LLM operations.
- Collaborate with cloud providers like AWS, Azure, and GCP to optimize costs and performance.
- Work with backend engineers to ensure smooth integration of AI models into conversational platforms.
- Partner with AI engineers and data scientists to align on project objectives and deployment strategies.
- Document MLOps processes, best practices, and tools to maintain operational excellence.
- Provide training and support to team members on MLOps methodologies and tools.
■ Work Location
■ Experience and Qualifications
- 5+ years of experience in MLOps, DevOps, or related fields, with a focus on deploying and managing LLMs or other large-scale machine learning models.
- Proven experience with tools like Hugging Face, MLFlow, and containerization technologies (Docker, Kubernetes).
- Strong experience with cloud platforms (AWS, Azure, GCP) and infrastructure as code (Terraform).
- Hands-on experience in reducing inference latency and optimizing AI infrastructure.
Technical
- Proficiency in Python, with experience in ML libraries such as TensorFlow, PyTorch, and related frameworks.
- Expertise in CI/CD pipelines, version control (Git), and orchestration tools.
- Familiarity with Generative AI, prompt engineering, and deploying models at scale.
■ Additional Preferred Qualifications
- Excellent problem-solving skills with the ability to tackle complex challenges independently.
- Strong communication skills, with the ability to translate technical concepts for non-technical stakeholders.
- A proactive mindset with a focus on continuous learning and staying updated with industry trends.