AI/ML Architect

  • Plano, TX
  • Posted 1 day ago | Updated 1 day ago

Overview

Hybrid
$80 - $90
Full Time
Accepts corp to corp applications
No Travel Required
Able to Provide Sponsorship

Skills

AI/ML
AWS
Python
RAG
MLOPS

Job Details

Role: AI/ML Architect

Location: Reston, VA / Plano, TX (Hybrid)

Duration: Long term

Mode of interview: In- Person

Job Description

As an Applied AI/ML Architect, you will be responsible for leading architectural decisions for the

Cloud, and Data Enterprise Portfolios. You must have a deep understanding of technical architecture

and have implemented AI/ML solutions in a cloud environment. Knowledge of industry best

practices around enterprise AI/ML adoption, security, architectures, and patterns. Experience with

micro-services architectures and cloud migration for data is a plus. Technical experience with multicloud environments (AWS, Azure, Google Cloud Platform) is a plus. Strong interpersonal communications skill isrequired.

Qualifications

  • Should have a bachelor s degree in Computer Science or related field. Master s degree is

preferred or equivalent Desired Experiences

  • 10+ years of progressive hands-on experience in application development with 5-6 years of

solution architecture, systems architecture and engineering, analysis and applications

programming in AI related discipline. Technical team leadership role is preferred

  • A minimum of 5 years experience in working with a cloud provider (AWS or Azure)
  • Experience with Architecture principles and TOGAF framework is a plus
  • AI/ML relevant AWS Professional Certification is preferred

Required Skills

  • Proven track record of implementing machine learning solutions, AI services and statistical

analysis related projects in production

  • Technical leadership with analytical, problem solving and communication skills
  • Familiarity with cloud AI/ML platform offerings, features
  • Understanding of AI services for speech, vision and text.
  • Machine learning background with algorithms
  • Expertise in MLOps and dataops lifecycles and engineering implementation in enterprise
  • Ability to code in Python, Spark or R as a programming language
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