Job Title: Senior AI Engineer
Location: Plano, TX | New York, NY / New Jersey | Columbus, OH
Work Model: Onsite (3 Days / Week)
Job Type: Contract
Role Overview
We are seeking an experienced Senior AI Engineer to join our team in building advanced artificial intelligence and machine learning solutions. In this role, you will design, build, and deploy production-grade AI models and systems to drive business impact. This position requires working 3 days onsite at one of our primary locations in Plano, NY/NJ, or Columbus.
Key Responsibilities
AI & ML Architecture: Architect, build, and scale machine learning, deep learning, and Generative AI (LLM) solutions for production environments.
Model Pipeline Development: Design end-to-end data pipelines and feature engineering workflows to support model training, fine-tuning, and evaluation.
Deployment & MLOps: Deploy AI models into high-availability cloud infrastructure and implement CI/CD pipelines for model monitoring, testing, and automated retraining.
Cross-Functional Collaboration: Partner with product managers, data engineers, and software architects to integrate AI capabilities seamlessly into enterprise software systems.
Performance Optimization: Optimize inference speed, latency, and resource consumption for complex AI systems.
Qualifications & Requirements
Experience: 10+ years of experience in software engineering, with 7+ years specifically focused on building and deploying AI/ML solutions in production.
Technical Stack:
Proficiency in Python and modern frameworks (PyTorch, TensorFlow, Hugging Face, LangChain).
Strong experience with modern Generative AI paradigms (RAG, LLM fine-tuning, prompt engineering, vector databases).
Cloud infrastructure experience (AWS, Azure, or GCP) including containerization (Docker, Kubernetes).
Solid grounding in software design patterns, REST APIs, and database design (SQL/NoSQL).
Onsite Expectation: Ability to work full-time onsite (5 days/week) at our location in Plano (TX), NY/NJ area, or Columbus (OH) .
Preferred Qualifications
Master s or Bachelor s degree in Computer Science, Data Science, AI, or a related quantitative field.
Background in financial services, healthcare, or high-throughput enterprise technology environments.
Hands-on experience with MLOps frameworks (e.g., MLflow, Kubeflow, SageMaker).
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