Machine Learning Engineer

Job Title: Machine Learning Engineer (ML Engineer)

Location: Gurgaon

Experience: Freshers

Company Overview

Ingenious eBrain Solutions is a boutique consulting firm with expertise in 11 diverse domains. Founded in 2012, we provide premium, customized Business Intelligence and Technology Intelligence Research solutions. We enable our clients to make informed decisions and launch innovative products and services. As part of our growth in the healthcare domain, we are seeking a skilled Machine Learning Engineer specializing in Natural Language Processing (NLP) and Large Language Models (LLMs).

Job Summary

The Machine Learning Engineer will be responsible for developing and deploying advanced AI models, with a special focus on NLP and LLMs, to solve complex challenges in the healthcare industry. The role involves building robust ML pipelines and integrating state-of-the-art General AI and LLM technologies to enhance our data-driven consulting services.

Key Responsibilities

• Design, develop, and deploy ML models, focusing on NLP and LLMs, to analyze and interpret complex healthcare data.
• Build and maintain scalable machine learning pipelines for training and deploying models in a production environment.
• Collaborate with healthcare domain experts and data scientists to define problem statements, gather requirements, and deliver AI-driven solutions.
• Conduct research on the latest AI technologies and methodologies to continually improve the effectiveness of our solutions.
• Ensure the integrity and privacy of patient data in compliance with healthcare regulations and standards.
  
  

Qualifications

• Bachelor’s or master’s or PhD in Computer Science, Data Science, Artificial Intelligence, or a related field.
• Proven experience in NLP and deploying LLMs in real-world applications.
• Strong expertise in machine learning, deep learning, and statistical modeling.
• Experience in building and maintaining ML pipelines for large-scale projects.
• Proficiency in programming languages such as Python or R and ML frameworks like TensorFlow or PyTorch.
• Familiarity with cloud services (AWS, Azure, GCP) and ML lifecycle tools (MLflow, Kubeflow).
• Excellent analytical, problem-solving, and communication skills.
  
  

Preferred Qualifications

• Experience in the healthcare industry, particularly with clinical data and regulatory standards.
• Publications or presentations in well-known AI or ML conferences.