Engineer - Machine Learning

Responsibilities

1. Collaboration:
   • Work with product managers and business owners to understand requirements.
2. Data to Model:
   • Create data pipelines and preprocess data from diverse sources (text, imaging, genomics, HER, etc.) to make it ready for model training. Monitor data quality through the process.
   • Build scalable and efficient ML pipelines powered by GPUs.
   • Implement a comprehensive model evaluation mechanism to measure and enhance model performance for superior metrics.
3. Model Enhancement and System Augmentation:
   • Augment capabilities of the foundation model using agent-based tooling such as LangChain and LlamaIndex.
   • Implement high-performant vector databases, knowledge graphs, reasoning engines, and other similar components to augment the capabilities of a foundation model.
4. Deployment, Testing, and Prototyping:
   • Deploy the AI models in a highly available and scalable manner.
   • Create model APIs for the software developers to consume in their applications.
   • Implement A/B testing mechanisms.
   • Implement guards against unintended inputs or unsupported usage of the system.
   • Prototype and present demo-ready AI solutions to various stakeholders.

Qualifications
Experience, Education, Skills:

• 3+ years of ML Engineering experience.
• Experience of building models using structured and unstructured data.
• Bachelor's/Master's degree in Computer Science, Machine Learning, AI, or related fields.
• Experience with building products powered by NLP models and hands-on experience with MLOps tools, e.g., MLFlow.