MLOps Engineer
18 hours ago
6 Month Contract - High Likelihood of Extension
**THIS ROLE IS HYBRID AND BASED IN NYC - URGENT NEED SO RELOCATION REQUIREMENT WILL NOT BE CONSIDERED**
Role Responsibilities:
- Develop and implement MLOps pipelines to automate the end-to-end machine learning workflow.
- Design and maintain infrastructure as code, ensuring scalability and reliability of data processing.
- Build event tables for effective data ingestion and storage, focusing on vector databases.
- Create and manage code for data ingestion, including automated versioning using GitHub Actions.
- Collaborate with data scientists to integrate LLM frameworks and enhance machine learning models.
- Monitor and capture errors during processes, ensuring timely notifications and resolutions via email alerts.
- Optimize existing data pipelines and frameworks for efficiency and performance.
- Work closely with cross-functional teams to ensure seamless integration of ML systems.
- Proven experience in data engineering and machine learning engineering, with a focus on MLOps practices.
- Strong understanding of large language models (LLMs) and relevant frameworks, such as LlamaIndex.
- Proficiency in cloud platforms, particularly AWS and Azure.
- Experience with infrastructure as code tools and methodologies.
- Familiarity with automated deployment processes and CI/CD practices.
- Ability to work in a fast-paced environment and adapt to evolving technologies.
- Hands-on experience in coding and problem-solving in a practical engineering role, preferably outside of corporate settings.
- A "unicorn" candidate who blends expertise in data engineering and ML engineering with a touch of data science.
- Self-motivated and innovative, with a strong desire to industrialize machine learning processes.
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