What are the responsibilities and job description for the AI/ML Engineering Lead position at Strategic Staffing Solutions?
Job Details
STRATEGIC STAFFING SOLUTIONS (S3) HAS AN OPENING!
AI/ML Engineering Lead
Iselin, NJ, Charlotte, NC or Chandler, AZ
12 months with possibility to convert
Hybrid onsite 2 days / 3 days remote
Required skillset
- Proven experience in Conversational AI and synthetic agent development, especially within Google Cloud environments.
- Hands-on expertise with GenAI orchestration tools (LangGraph, LangChain, ReACT, LLMs).
- Strong background in real-time, event-driven architectures and cloud-native technologies (Google Cloud Platform, Kafka, Pub/Sub, Big Table).
- Deep understanding of MLOps practices for scalable AI deployment and monitoring.
- Experience in Responsible AI (RAI) and regulatory AI governance, especially in Fintech or other highly regulated industries.
- Track record of cost-efficient AI model deployment, optimizing deterministic vs. probabilistic approaches.
Day to Day
- Develop Synthetic AI Agents using the Google Conversational Platform and playbooks to enhance automated interactions.
- Orchestrate multiple Generative AI Agents using LangGraph, LangChain (with ReACT), and LLM tooling for intelligent workflow automation.
- Architect and implement large-scale, low-latency, real-time systems with a focus on event-driven processing and extended conversational context using Big Table, Time Series, Pub/Sub, and Kafka.
- Leverage ML frameworks and MLOps best practices to streamline the deployment, monitoring, and maintenance of AI models.
- Continuously combat AI hallucinations by implementing real-time detection and correction mechanisms, rather than one-time adjustments.
- Design and implement guardrails, supervisory mechanisms, and observability frameworks to ensure AI transparency, reliability, and explainability.
- Lead Responsible AI (RAI) initiatives at scale, ensuring compliance with regulatory requirements for industries like Fintech.
- Optimize cost-efficiency of GenAI solutions through hybrid approaches, balancing deterministic and probabilistic methods.
- Integrate AI solutions into Google Cloud s native microservices and event-driven architectures, leveraging technologies such as Big Table, Pub/Sub, and AlloyDB.
*Beware of scams. S3 never asks for money during its onboarding process
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