AI Engineer Job Town of Texas Wisconsin USA,IT/Tech

Location: Town of Texas

Mandatory

Skills:

Gen AI/ Python/ Azure OpenAI/ Tensor Flow/ Azure ML/ Bus. Process-Life Sciences

SR. AI Engineer

Skills:

Advanced AI Skills

Proficiency in Python

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:

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, AIML, 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 and 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 AIML 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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