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Intellisoft Technologies
Glen Allen,VA
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Intellisoft Technologies
Glen Allen,VA
Description
Position: AI Engineer Location: Fort Mill, SC Duration: 12 Months Client: Apex Visa Restrictions: No OPT, CPT & H1b Sub Vending: No Pay Rate: $60/Hr on W2 without benefits Bill Rate: $84 Candidate must be authorized to work without sponsorship Yes Exclusive to Apex Yes
Required Skills Need experience end to end expeirence building and deploying AI tools into production Python and PySpark LLM and NLP tuning RAG building Full stack dev experience including UI Dev React and FAST API Azure ML Ops skills Additional Skills Job Description Duties:
Required Skills Need experience end to end expeirence building and deploying AI tools into production Python and PySpark LLM and NLP tuning RAG building Full stack dev experience including UI Dev React and FAST API Azure ML Ops skills Additional Skills Job Description Duties:
- Collaborate with product team to design, develop, and deploy AI enabled products into production
- Guide the architecture, infrastructure, tools, and processes used to develop, maintain AI/ML products
- Deeply understand a wide variety of algorithms to understand vulnerabilities, strengths, and weaknesses
- Standardize, optimize and scale products in production environments
- Design and implement scalable and efficient ML Ops pipelines for ingesting, processing, and storing large volumes of structured and unstructured data
- Expert understanding and experience deployment to production AI/ML architectures, tools, and data infrastructure to public cloud platforms.
- Experience in LLM, NLP, RAG development and tuning
- Expert level programming skills including Python/PySpark.
- Designing and building user interfaces using HTML, CSS, and JavaScript frameworks like React or Angular.
- Strong understanding of cloud computing, containerization, and DevSecOps practices
- Strong understanding of layers of software stack including API design, development and production deployment at scale.
- Expert in data engineering and data orchestration best practices with large scale structured and unstructured data
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