Applied AI Engineer

Bright Vision Technologies•Alpharetta, GA

7d•$130,000 - $180,000•Remote

About The Position

Bright Vision Technologies is seeking a highly experienced Applied AI Engineer to design, develop, and deploy enterprise-scale AI solutions. The role combines hands-on development with technical leadership and requires the ability to architect scalable, secure, high-performance AI systems and take AI models from research through production. The position is 100% remote within the continental United States and is full-time, direct W2 employment. The stated annual salary range is $130,000–$180,000, based on experience. The engineer will work with AI, machine learning, deep learning, large language models, natural language processing, computer vision, and MLOps. The role collaborates with data scientists, software engineers, product managers, and business stakeholders to deliver production-ready solutions, while contributing to technical leadership, engineering practices, and ongoing evaluation of emerging AI technologies.

Requirements

Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related technical discipline.
10+ years of professional experience in Artificial Intelligence, Machine Learning, Deep Learning, or Applied AI.
Expert-level Python programming skills and extensive experience with PyTorch, JAX, or TensorFlow.
Proven experience developing and deploying large language models, 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 using AWS, Microsoft Azure, or Google Cloud Platform 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.

Nice To Haves

Experience with LLM fine-tuning, retrieval-augmented generation, agentic AI, multimodal AI, and vector databases such as Pinecone, Weaviate, Milvus, or FAISS.
Hands-on experience with AI orchestration frameworks such as LangChain, LlamaIndex, LangGraph, or similar technologies.
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 specializing in Artificial Intelligence, Machine Learning, Computer Vision, or Natural Language Processing.

Responsibilities

Design, develop, and deploy production-grade AI and machine learning solutions to address complex business challenges.
Architect scalable training, inference, and MLOps pipelines for enterprise AI applications.
Develop, fine-tune, evaluate, and optimize large language models, deep learning models, and multimodal AI systems.
Build AI applications using retrieval-augmented generation, vector databases, embeddings, prompt engineering, and agentic AI frameworks.
Design and implement machine learning pipelines for natural language processing, computer vision, recommendation systems, and predictive analytics.
Optimize model performance, latency, scalability, and infrastructure utilization across cloud and distributed computing environments.
Collaborate with data scientists, software engineers, product managers, and business stakeholders to deliver production-ready AI solutions.
Establish best practices for model evaluation, responsible AI, governance, security, monitoring, and lifecycle management.
Mentor junior AI engineers and contribute to technical leadership, architecture reviews, and engineering best practices.
Evaluate emerging AI technologies, foundation models, and frameworks to drive continuous innovation.