Machine Learning Engineer

Key Skills

Aartificial intelligence, API, GPUs, Large Language Models - LLMs, Machine learning techniques, MLflow, MLOps tools, Natural Language Processing (NLP)

Job Description

As a Machine Learning Engineer at M42, you will have the exciting opportunity to 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.