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Automation QA with AI
Jersey City, NJ
Jersey City
NJ
07399
Date
: May-19-25
2025-05-19
2026-05-09
Automation QA with AI
Jersey City, NJ
May-19-25
Work Authorization
US Citizen
GC
H1B
GC EAD, TN EAD, H4 EAD, L2 EAD
Preferred Employment
Corp-Corp
W2-Permanent
W2-Contract
1099-Contract
Contract to Hire
Job Details
Experience
:
Architect, Senior
Rate/Salary ($)
:
Market
Duration
:
6 months
Sp. Area
:
AI, ML, NLP, Data Science
Sp. Skills
:
[AI] Artificial Intelligence
Permanent Direct Hire
Consulting / Contract
FULL_TIME, CONTRACTOR
Required Skills
:
Artificial Intelligence, DevOps, Machine learning, Continuous deployment, JAVA, Natural Language Processing, Python, Scala, Selenium, Windows Azure
Preferred Skills
:
Domain
:
Financial
Work Authorization
US Citizen
GC
GC EAD, TN EAD, H4 EAD, L2 EAD
H1B
Preferred Employment
Corp-Corp
W2-Permanent
W2-Contract
1099-Contract
Contract to Hire
Job Details
Experience
:
Architect, Senior
Rate/Salary ($)
:
Market
Duration
:
6 months
Sp. Area
:
AI, ML, NLP, Data Science
Sp. Skills
:
[AI] Artificial Intelligence
Permanent Direct Hire
Consulting / Contract
FULL_TIME, CONTRACTOR
Required Skills
:
Artificial Intelligence, DevOps, Machine learning, Continuous deployment, JAVA, Natural Language Processing, Python, Scala, Selenium, Windows Azure
Preferred Skills
:
Domain
:
Financial
Synkriom
Edison, NJ
Post Resume to
View Contact Details &
Apply for Job
Job Description
:
Job Description:
Experience in QA Engineering, AI/ML, and automation frameworks
Proven experience in Designing and implementing AI-based test automation frameworks.
NLP, LLMs (e.g., GPT-4, BERT), and data annotation techniques.
Tools such as TensorFlow, PyTorch, Hugging Face, or equivalent.
Strong programming background: Python, Java, or Scala.
Experience with test automation tools like Selenium, Cypress, TestNG, or equivalent.
Solid understanding of payment systems, financial services regulations, and transactional risk analysis
Knowledge of CI/CD pipelines, DevOps, and tools like Jenkins, GitHub Actions, Azure DevOps, etc.
Experience working with structured/unstructured data, data lakes, and data pipelines.
Demonstrated success in delivering greenfield AI/ML initiatives from concept to scale.
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