Applied AI Engineer
New
B
Bright Vision TechnologiesArtificial intelligence
100% Remote (Continental United States)Full-TimeSenior
Salary130,000 - 180,000 USD per year
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Job Details
- Experience
- 10+ years of professional experience in Artificial Intelligence, Machine Learning, Deep Learning, or Applied AI.
- Required Skills
- AWSPythonPyTorchTensorflowMLOpsComputer Vision
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 programming skills in Python.
- Extensive experience with PyTorch, JAX, or TensorFlow.
- Production experience developing and deploying LLMs, NLP, computer vision, and deep learning applications.
- 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 AWS, Microsoft Azure, or Google Cloud Platform for AI workloads.
- Strong understanding of machine learning algorithms, statistics, model evaluation, experimentation, and optimization techniques.
- Preferred: experience with LLM fine-tuning, RAG, agentic AI, multimodal AI, and vector databases.
- Preferred: experience with LangChain, LlamaIndex, LangGraph, or similar AI orchestration frameworks.
- Preferred: experience deploying AI applications using Kubernetes, Docker, Ray, or distributed inference frameworks.
Responsibilities
- Design, develop, and deploy production-grade AI and machine learning solutions.
- Architect scalable training, inference, and MLOps pipelines for enterprise AI applications.
- Develop, fine-tune, evaluate, and optimize LLMs, deep learning models, and multimodal AI systems.
- Build AI applications using RAG, vector databases, embeddings, prompt engineering, and agentic AI frameworks.
- Design and implement machine learning pipelines for NLP, 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 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.
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