Agentic AI Developer with Verizon Experience

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an "Agentic AI Developer with Verizon Experience" on a long-term contract in Irving, TX (3 days onsite weekly), offering competitive pay. Requires 3+ years in AI/ML, proficiency in Python, and experience with LLMs and autonomous agents.
🌎 - Country
United States
πŸ’± - Currency
$ USD
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πŸ’° - Day rate
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πŸ—“οΈ - Date discovered
May 22, 2025
πŸ•’ - Project duration
Unknown
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🏝️ - Location type
On-site
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πŸ“„ - Contract type
Unknown
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πŸ”’ - Security clearance
Unknown
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πŸ“ - Location detailed
Irving, TX
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🧠 - Skills detailed
#Python #ML (Machine Learning) #Transformers #Computer Science #AI (Artificial Intelligence) #Cloud #Reinforcement Learning #Langchain #"ETL (Extract #Transform #Load)" #Scala
Role description
Agentic AI developer Irving, TX (3 days onsite in a week) Longterm Contract Key Responsibilities β€’ Develop agentic AI systems capable of autonomous decision-making, task decomposition, and adaptive behavior in real-world or simulated environments. β€’ Integrate large language models (LLMs), symbolic reasoning, and other AI components into cohesive agent frameworks. β€’ Collaborate with cross-functional teams (e.g., product, UX, robotics, cloud engineering) to deploy agents in production environments. β€’ Optimize performance of agentic systems for scalability, latency, and robustness. β€’ Conduct experiments and evaluations on agent behavior, adaptability, and long-term autonomy. β€’ Stay current with research and best practices in autonomous agents, AI planning, reinforcement learning, and related domains. Qualifications Required: β€’ Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Robotics, or a related field β€’ 3+ years’ experience in AI/ML software development, with a focus on autonomous agents or AI planning. β€’ Strong proficiency in Python and familiarity with frameworks such as LangChain, AutoGen, or custom agentic toolkits. β€’ Experience with LLMs, transformers, and integrating language models into agent workflows. β€’ Solid understanding of one or more of: reinforcement learning, cognitive architectures, symbolic reasoning, or decision-making systems.