Applied AI Engineer
New
B
Bright Vision TechnologiesSoftware Development
100% Remote (Continental United States)Full-TimeSenior
Salary130,000 - 180,000 USD per year
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Job Details
- Experience
- 10+ Years
- Required Skills
- PythonMachine LearningPyTorchTensorflowDeep LearningNLPLLMMLOpsComputer Vision
Requirements
- Bachelor's or Master's degree in Computer Science, AI, 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 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, Microsoft Azure, or Google Cloud Platform (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.
Responsibilities
- Design, develop, and deploy production-grade AI and machine learning solutions that address complex business challenges.
- Architect scalable training, inference, and MLOps pipelines for enterprise AI applications.
- Develop, fine-tune, evaluate, and optimize Large Language Models (LLMs), deep learning models, and multimodal AI systems.
- Build AI applications leveraging Retrieval-Augmented Generation (RAG), vector databases, embeddings, prompt engineering, and agentic AI frameworks.
- 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.
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