Engineer - Machine Learning
1 week ago
- Collaboration:
- Work with product managers and business owners to understand requirements.
- 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.
- 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.
- 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.
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