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AI Application Architect

Job in Indiana Borough, Indiana County, Pennsylvania, 15705, USA
Listing for: Openkyber
Full Time position
Listed on 2026-07-04
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 53 USD Hourly USD 53.00 HOUR
Job Description & How to Apply Below

Title:

AI/ML Developer

Location:

Indianapolis, IN (Onsite)
Duration: 6 Months
Rate: $53/Hr
On W2
Relevant Experience (in Yrs.): 6+

Responsibilities
  • Technical Leadership:
    Set engineering standards, conduct code reviews, and mentor a team of AI/ML engineers across the full development lifecycle.
  • Model Development Design:
    Design, build, and optimize machine learning and deep learning models for production use cases including NLP, computer vision, and predictive analytics.
  • Architecture & Infrastructure:
    Define scalable AI/ML system architecture; oversee data pipelines, model training, and deployment infrastructure on cloud platforms (Azure, AWS, Google Cloud Platform).
  • MLOps & Deployment:
    Establish and maintain CI/CD pipelines, model versioning, monitoring, and retraining workflows to ensure reliability in production.
  • Evaluation & Governance:
    Define model evaluation frameworks; ensure solutions meet performance, fairness, safety, and compliance standards.
  • Innovation:
    Stay current on emerging AI trends and frameworks; identify opportunities to adopt new tools and techniques that advance team capabilities.
Qualifications
  • 6+ years of relevant experience.
  • Strong proficiency in Python and ML frameworks (PyTorch, Tensor Flow, scikit-learn).
  • Experience with LLMs, prompt engineering, and generative AI platforms.
  • Hands‑on knowledge of cloud-based AI/ML services (Azure ML, AWS Sage Maker, Vertex AI).
  • Familiarity with vector databases, RAG pipelines, and API development.
  • Prior experience leading engineering teams in an Agile/Scrum environment.
  • Essential skills:
    Python (PyTorch/Tensor Flow), generative AI, Azure, AWS, Agile/APIs (Google Cloud Platform), MLOps.
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