AI/ML Expert
Job in
Plano, Collin County, Texas, 75086, USA
Listed on 2026-10-23
Listing for:
TechDigital Group
Full Time
position Listed on 2026-10-23
Job specializations:
-
IT/Tech
Machine Learning/ ML Engineer, AI Engineer (Applied/Software), Data Scientist, Data Analyst
Job Description & How to Apply Below
Generative AI & Large Language Models (LLM)
Python Skills
- Educational
Qualifications:
Graduate or Doctorate degree in information technology, Neuroscience, Business Informatics, Biomedical Engineering, Computer Science, Artificial Intelligence, or a related field. Specialization in Natural Language Processing is preferred. - Experience Requirements: 8-10 years of experience in developing Data Science, AI, and ML solutions, with a specific focus on generative AI and LLMs in the Med Tech/Healthcare/Life Sciences domain.
- Prior experience in identifying new opportunities to optimize the business through analytics, AI/ML and use case prioritization.
- The individual should be a thought leader having a well-balanced analytical business acumen, domain, and technical expertise.
- Large Language Model Expertise:
Experience in working with and fine-tuning Large Language Models (LLMs), including the design, optimization of NLP systems, frameworks, and tools. - Application Development with LLMs:
Experience in building scalable applications using LLMs, utilizing frameworks such as Lang Chain, Llama Index, etc and product ionizing machine learning and AI models. - Language Model Development:
Utilize off-the-shelf LLM services, such as Azure OpenAI, to integrate LLM capabilities into applications. - Cloud Computing Expertise:
Proven architect kind of experience in cloud computing, particularly with Azure Cloud Services. - Technical Proficiency:
Strong skills in UNIX/Linux environments and command-line tools. - Programming and ML
Skills:
Proficiency in Python, with a deep understanding of machine learning algorithms, deep learning, and generative models. - Advanced AI Skills and Testing:
Familiarity with deep learning frameworks (e.g., Tensor Flow, PyTorch), hands-on experience in deploying AI/ML solutions as a service/REST API on Cloud or Kubernetes, and proficiency in testing of developed AI components. - Responsibilities also include data analysis/preprocessing for training and fine-tuning language models.
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