AI Engineer
Stateside · United States ·
- Work mode
- Remote
- Category
- AI engineering
- Experience
- 6+ years
Stateside · United States ·
Stateside is hiring an AI Engineer to design, build, and maintain production AI systems spanning deep learning, NLP, and computer vision. Day to day, they develop AI-powered APIs and services in Python, integrate models into web/mobile/enterprise stacks, optimize inference (quantization, pruning, ONNX), and experiment with generative AI, using tools like PyTorch, TensorFlow, Hugging Face, and MLfl
We are seeking a dynamicAI Engineerto help design and deploy cutting-edge artificial intelligence systems that drive innovation and automation across our platforms. This role bridges the gap between data science and software engineering, requiring expertise in developing, integrating, and optimizing AI-powered solutions.
Design and develop AI systems and intelligent applications, leveraging deep learning, NLP, and computer vision.
Collaborate with cross-functional teams to identify business problems solvable through AI.
Build production-ready APIs that expose AI capabilities across platforms.
Integrate AI solutions into mobile, web, or enterprise software stacks.
Research and experiment with generative AI (LLMs, GANs), reinforcement learning, and other advanced techniques.
Optimize inference performance and latency using quantization, pruning, or ONNX.
Maintain AI systems through continuous evaluation, retraining, and performance tuning.
Develop reusable AI components and tools that accelerate engineering velocity.
Bachelor’s or Master’s degree in Computer Science, AI, Electrical Engineering, or related discipline.
3–6+ years of experience delivering AI/ML models into production systems.
Strong programming skills in Python and familiarity with C++, Java, or Go.
Proficiency with AI/ML libraries like TensorFlow, PyTorch, Hugging Face Transformers, OpenCV.
Experience building RESTful APIs and microservices that expose AI logic.
Familiarity with AI model lifecycle tools like MLflow, Triton Inference Server, ONNX Runtime.
Experience deploying AI solutions to cloud platforms (Azure, AWS, GCP).
Experience with LLMs (e.g., GPT-3/4, Claude, Mistral) and prompt engineering.
Familiarity with vector databases (Pinecone, Weaviate) and RAG systems.
Hands-on experience with AI infrastructure tools (NVIDIA Triton, Ray, or DeepSpeed).
AI-related certifications or contributions to open-source AI projects.