Llm/mlops Engineer, It

Job ID: 16604- Location: Digital Hub, SG- Description:

- **JOB RESPONSIBILITIES**

**On-Premise Open-Source LLM Hosting and Deployment**:

- Lead the deployment and management of open-source models like Llama, Mistral, and others in on-premise environments.
- Design and implement infrastructure that supports large-scale LLM hosting, ensuring security, scalability, and resource optimization.
- Develop best practices for the deployment and lifecycle management of open-source LLMs, from testing to production monitoring.

**Multi-Modal LLM Operations**:

- Collaborate with NLP and data science teams to ensure multi-modal models are trained, optimized, and deployed for cross-functional use cases.
- Implement strategies for efficient data handling, storage, and processing of multi-modal inputs and outputs.

**Data Preparation for AI Models**:

- Coordinate with data engineering teams to ensure data quality and readiness for ML and LLM use cases, specifically for open-source and multi-modal models.
- Perform and oversee data cleaning, transformation, and augmentation processes for optimized training and inference.
- Implement data versioning and lineage strategies to support model reproducibility and compliance.

**MLOps Pipeline Development and Management**:

- Develop, deploy, and monitor machine learning and LLM pipelines for training, testing, and production.
- Automate workflows to streamline the development and deployment of ML and LLM models, with a focus on reducing latency and computational overhead.
- Set up CI/CD pipelines for continuous integration and delivery of ML models.

**Model Monitoring, Optimization, and Maintenance**:

- Establish monitoring and alerting frameworks for model performance and drift, particularly for on-premise open-source models.
- Implement automated retraining and update processes to maintain model accuracy and relevance.

**Collaboration and Documentation**:

- Work closely with cross-functional teams, including data scientists, engineers, and product managers, to align on project requirements and deliver optimized AI solutions.
- Document all MLOps workflows, procedures, and guidelines for hosting and managing open-source and multi-modal models, enhancing team knowledge sharing and onboarding.

**Collaborate Across Teams: Work closely with various departments to ensure seamless integration and effective deployment of AI solutions.**

**Leadership and Teamwork: Exhibit strong leadership qualities and work collaboratively with the team to achieve project goals.**

**Solution Selling: Effectively communicate and advocate for the adoption of AI solutions within the organization.**

**Continuous Learning: Stay abreast of the latest developments in Generative AI and related fields.**

**Job Requirements**:

- 5-10 years of experience in MLOps, Data Engineering, or similar roles with a focus on ML model deployment and operationalization.
- Strong knowledge of MLOps, LLM deployment, and open-source model hosting, with hands-on experience in models like Llama and Mistral.
- Expertise in multi-modal LLMs and handling diverse data types (text, image, audio).
- Proficiency in Python, SQL, and ML/LLM frameworks (e.g., Hugging Face Transformers, TensorFlow, PyTorch).
- Familiarity with containerization and orchestration tools (Docker, Kubernetes) and cloud platforms (AWS, GCP, Azure) as well as on-premise infrastructure.
- Experience with CI/CD tools (Azure DevOps, GitLab, or similar).
- Strong problem-solving skills and the ability to adapt to a fast-paced, dynamic environment.