Applied AI Engineer

About the role

The Applied AI Engineer will design, develop and deploy enterprise‑scale AI solutions, providing technical leadership and hands‑on implementation of scalable, secure, high‑performance models. Working remotely across the US, the role collaborates with data scientists, engineers and product teams, mentors junior staff and drives innovation in LLMs, NLP, computer vision and MLOps.

About the company

Bright Vision Technologies is a minority‑owned, product‑focused AI technology company headquartered in Bridgewater, New Jersey. Founded in July 2020, it builds the Lumina platform – an AI‑powered talent intelligence and enterprise automation solution that combines hybrid cloud and blockchain to serve enterprises in financial services, healthcare, manufacturing and retail.

Requirements

• Bachelor’s or Master’s degree in Computer Science, AI, ML, Data Science, or related field
• 10+ years professional experience in Artificial Intelligence, Machine Learning, Deep Learning, or Applied AI
• Expert‑level Python programming with extensive experience using PyTorch, JAX, or TensorFlow
• Proven experience developing and deploying Large Language Models (LLMs), NLP, Computer Vision, and deep learning applications in production
• Strong knowledge of distributed training, GPU optimization, model serving, and production ML deployment
• Hands‑on experience with MLOps, CI/CD pipelines, model monitoring, feature engineering, and automated ML workflows
• Experience with cloud platforms such as AWS, Azure, or GCP for AI workloads
• Strong understanding of machine learning algorithms, statistics, model evaluation, experimentation, and optimization techniques
• Excellent problem‑solving, communication, collaboration, and technical leadership skills
• Experience with LLM fine‑tuning, Retrieval‑Augmented Generation (RAG), agentic AI, multimodal AI, and vector databases (Pinecone, Weaviate, Milvus, FAISS)
• Hands‑on experience with AI orchestration frameworks such as LangChain, LlamaIndex, LangGraph, or similar
• Experience deploying AI applications using Kubernetes, Docker, Ray, or distributed inference frameworks
• Publications in AI/ML conferences, open‑source contributions, patents, or recognized technical leadership in the AI community
• Knowledge of Responsible AI, AI governance, model security, fairness, explainability, and regulatory compliance
• Ph.D. or Master’s degree with specialization in AI, ML, Computer Vision, or Natural Language Processing