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AI ARCHITECT

Remote:

Full Remote

Contract:

Full time

Experience:

Senior (5-10 years)

Work from:

United States

Offer summary

Qualifications:

Graduate or Doctorate in IT or related field, 8-10 years experience in AI solutions, Experience with generative AI and LLMs, Proficient in Python and machine learning, Expertise in cloud computing, preferably Azure.

Key responsabilities:

Develop client AI solutions for MedTech
Optimize business analytics using AI
Design and optimize NLP systems
Build scalable applications with LLMs
Conduct data analysis for language model training

Danta Technologies SME https://www.dantatechnologies.com

51 - 200 Employees

See more Danta Technologies offers

Job description

AI Architect

Location : Dallas TX (Remote Ok)

Location : Remote

Roles and Responsibilities:

· 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 Client solutions, with a specific focus on generative AI and LLMs in the MedTech/Healthcare/Life Sciences domain.

· Prior experience in identifying new opportunities to optimize the business through analytics, AI/Client 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 LangChain, LlamaIndex, etc and productionizing 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 Client 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., TensorFlow, PyTorch), hands-on experience in deploying AI/Client 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.