Senior Machine Learning Engineer with Generative AI Expertise

14 hours ago

Ahmedabad, Gujarat, India OmniMD Full time

About OmniMD

OmniMD is a leading healthcare IT vendor that has embarked on a journey to revolutionize the Clinical Decision Support System (CDSS) space through its OmniScient suite of applications.

The company's mission is to leverage machine learning, AI, and generative AI to improve patient outcomes and streamline clinical workflows.

Job Overview

We are seeking an experienced Senior Machine Learning Engineer with expertise in Generative AI, Retrieval-Augmented Generation (RAG), LLaMA models, and vector-databases to join our dynamic team.

The ideal candidate will have a strong background in machine learning, deep learning, and generative AI, with experience in leveraging RAG techniques, LLaMA models, and vector-databases to create groundbreaking solutions that address complex challenges across various industries.

Key Responsibilities

  • Design, develop, and deploy advanced machine learning models and algorithms, particularly in Generative AI, LLaMA models, RAG, and vector-databases for various applications.
  • Analyze and interpret complex datasets to identify patterns and trends that can be leveraged for ML/AI, Generative AI, and RAG solutions.
  • Deploy machine learning models into production, ensuring scalability, reliability, and robustness, with an emphasis on Generative AI, LLaMA models, RAG, and vector-database integration.
  • Stay up-to-date with the latest developments in machine learning, AI, Generative AI, LLaMA models, RAG, and vector-databases, and apply new techniques and methodologies as appropriate.
  • Work closely with cross-functional teams, including data scientists, software engineers, and product managers, to integrate ML/AI, Generative AI, LLaMA models, RAG, and vector-database solutions into products.
  • Optimize and fine-tune machine learning models, RAG techniques, LLaMA models, and vector-database queries for performance, efficiency, and cost-effectiveness.
  • Provide guidance and mentorship to junior ML/AI engineers and data scientists, particularly in the areas of Generative AI, LLaMA models, RAG, and vector-databases.
  • Maintain comprehensive documentation of models, algorithms, and processes, with a focus on Generative AI, LLaMA models, RAG, and vector-database techniques.

Requirements

  • Bachelor's, master's, or Ph.D. in Computer Science, Data Science, Statistics, Mathematics, or a related field.
  • 2 to 15 years of experience in machine learning, AI, or a related field, with a minimum of 2-5 years of relevant experience in the US Healthcare Domain preferred.
  • Proficiency in programming languages such as Python or Java.
  • Strong understanding of machine learning frameworks (e.g., TensorFlow, PyTorch, Keras).
  • Extensive experience with Generative AI models (e.g., GANs, VAEs, transformers).
  • Expertise in Retrieval-Augmented Generation (RAG) techniques, integrating retrieval mechanisms with generative models.
  • Experience with LLaMA (Large Language Model Meta AI) models, including their development, fine-tuning, and deployment.
  • Proficiency with vector-databases (e.g., Pinecone, Weaviate, FAISS) for efficient similarity search and retrieval tasks.
  • Experience with big-data technologies (e.g., Hadoop, Spark) and data-processing pipelines.
  • Familiarity with cloud platforms (e.g., AWS, Google Cloud, Azure).
  • Expertise in deep learning techniques and neural networks.
  • Proficiency in natural language processing (NLP) and computer vision, especially in Generative AI and RAG applications.
  • Experience with reinforcement learning and generative models.
  • Familiarity with MLOps/DevOps practices and tools for ML (e.g., Docker, Kubernetes).
  • Strong problem-solving skills and the ability to think algorithmically.
  • Experience with data-visualization tools (e.g., Matplotlib, Seaborn).
  • Proficiency in SQL and NoSQL databases.
  • Experience with version control systems (e.g., Git).

Estimated Salary: $120,000 - $180,000 per year

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