onsite
Engineer - Machine Learning
Engineer - Machine Learning
As a Machine Learning Engineer at M42, you will develop and enhance AI systems utilizing foundation models, including LLM, Imaging, Genomics, and EHR. Your role involves creating data and ML pipelines, augmenting model capabilities with agent-based tooling, and deploying scalable AI solutions to drive innovation in healthcare.
About the role
Overview
As a Machine Learning Engineer at M42, you will work on building AI systems powered by foundation models (Language - LLM, Imaging, Genomics, EHR). Your expertise will drive the seamless integration and enhancement of our foundation models with other components to improve overall performance and capabilities of the AI systems.
Responsibilities
- 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.
Soft skills:
- Outstanding problem-solving abilities, critical thinking skills, and team-player spirit.
- A strong interest in learning and growing - we work in a fast-evolving field.
What To Expect
Work Environment:
- Challenging healthcare AI problems, involving some of the largest datasets in the world.
- Accomplished colleagues who are highly collaborative and collegial.
- Fairly flat hierarchy (merit of ideas over rank) with high ownership for solving problems.
Career Growth:
- Opportunities for career progression.
- Regular learning and development opportunities as a team (weekly reading/discussion groups) to help you grow in healthcare AI.