What are the responsibilities and job description for the AI Implementation Engineer position at Syntricate Technologies?
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This is a contract position and we are offering payment options of W2 / 1099 & C2C per hour.
The interview process will be initiated as soon as possible.
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Job Description :
Role : AI Implementation Engineer
Duration : : Long-Term Contract
Location : Memphis, TN - 100% Remote
TOP SKILLS in order of preference.
AI Solution Design and Implementation
Machine Learning and Data Science Expertise
AI Architecture and Pipeline Planning
QUALIFICATIONS / EXPERIENCE
Proven experience as a Data Engineer, AI Engineer, or similar role, with a focus on production, customer facing implementation of data orchestration and AI technologies.
Proficiency in programming languages (Python, Java), familiarity with related AI / ML frameworks (ex. LangChain, TensorFlow, PyTorch).
Experience with prompt flows, prompt engineering best practices, and AI patterns (ex. Retrieval Augmented Generation (RAG))
Development and production deployment experience with data products on public cloud platforms (Azure and AWS preferred)
Strong development practices including source control, testing methodologies, and, preferably, DevOps or CI / CD processes and tooling
Familiarity with vector databases, search indexes, and embeddings
Experience with application and API development practices
ESSENTIAL JOB FUNCTIONS
Collaboration : Work with AI architect, infrastructure, and other engineers to develop and deploy AI models based on jointly created designs.
Operations : Ensure scalability, reliability, and security of AI and data orchestration systems. Design systems to produce ethical, un-biased output.
Support : Provide SME level support, document, and guidance for implemented AI processes.
Governance and Improvement : Monitor and improve AI systems based on performance metrics and user feedback. Implement governance and observation methodologies to provide transparency to model operations.
Data Preparation : Design and implement processes to improve data quality, synthesize data, produce training sets, and generally prepare data for AI usage.
EDUCATION
Bachelor's degree in Computer Science, Engineering, or a related field
CERTIFICATIONS
Relevant certifications in AI, data engineering, or cloud computing
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