(Part-Time)
We're looking for a talented and self-driven Part-Time AI Engineer with hands-on experience in deploying Computer Vision, and machine learning models to production environments.
You'll play a key role in designing and integrating intelligent systems into real-world applications, with a focus on fast iteration and production-readiness.
Key Responsibilities:
Assist in developing and fine-tuning computer vision models for tasks such as detection, recognition, and tracking.
Assist in integrating AI agent workflows using LLMs (e.g., GPT, Claude) with tools like LangChain or AutoGen.
Design and implement scalable model deployment pipelines (REST APIs, containers, etc.).
Collaborate with team members across product, design, and backend teams.
Maintain code quality, versioning, and experiment tracking.
Qualifications:
Must-have:
Strong experience with Python, PyTorch, and OpenCV.
Knowledge of MLOps best practices and CI/CD.
Familiarity with LLMs and building agents (e.g., LangChain, OpenAI API, HuggingFace).
Familiarity with tools like Streamlit or Gradio for rapid prototyping.
Experience deploying models with FastAPI, Docker, AWS/GCP, or similar.
Understanding of model lifecycle management and version control (e.g., Git, MLflow).
Ability to work independently and manage time effectively.
Familiarity with research papers and experience reading arXiv or conference papers
Excellent communication skills
Nice-to-have:
Experience with edge deployment (e.g., TensorRT, mobile inference).
Optimize inference for production (ONNX, TorchScript, quantization, etc.).
Background in Reinforcement Learning or Autonomous Agents.
Send your resume, GitHub/portfolio link, and a brief intro explaining your relevant experience to [sethuraman@yoona.ai]. Please include links to any deployed apps, AI agents, or CV projects.
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