Lead Machine Learning Engineer

8 hours agoLead Hyderabad, Telangana, India Onsite Full Time Ai Jobs by Flare Capital Partners

Skills

Ocr Model Training Model Evaluation Pytorch Transformers Nlp Deep Learning Generative Ai Machine Learning Aws Retrieval-Augmented Generation Model Deployment Python Sagemaker Data Preprocessing Experimental Design

About the Role

As a Lead Machine Learning Engineer, you'll join a growing team of world-class machine learning engineers and clinical experts to deploy machine learning models that help automate burdensome administrative clinical practices. You'll design, develop, and deploy advanced machine learning algorithms for retrieval, classification, and generative use cases, while building reliable and scalable production ML systems. You'll write and maintain reusable codebases for data preprocessing, model training, evaluation, and deployment, and provide software and machine learning best practice guidance to junior engineers. You'll work cross-functionally with product managers, clinicians, and technical leadership to align ML solutions with core objectives.

Requirements

Minimum 7+ years of experience in applied ML with a masters degree or 5+ years with a PhD, ideally in a senior or lead role in a large technology or healthcare company
Clear understanding of model building, model maintenance and the measures that optimize models for production use
Understand experimental design and can independently perform collection, measurement, and interpretation of results
Expert in Python with experience in deep learning frameworks (e.g., PyTorch)
Hands on experience building deep learning models (e.g., transformers) for NLP tasks
MS or PhD required
Experience with generative AI or Retrieval Augmented Generation (RAG)
Experience working with unstructured healthcare data (e.g., clinical notes)
Experience with OCR or image-based document understanding techniques
Hands on experience using AWS tools such as SageMaker Studio

Responsibilities

Design, develop and deploy advanced machine learning algorithms for retrieval, classification and generative use cases
Develop reliable and scalable production machine learning systems
Write and maintain reusable codebases to perform data preprocessing, model training, evaluation, and deployment
Provide software and machine learning best practice guidance to junior engineers
Work cross-functionally with diverse stakeholders, including product managers, clinicians, and technical leadership to align ML solutions with core objectives