Description:
As part of a cross-functional team of engineers, data scientists, and product owners, you will be responsible for designing, implementing, optimizing, and maintaining our machine learning operations (MLOps) infrastructure. If you are passionate about bringing machine learning models from development to production seamlessly and efficiently, Avrioc is the place to be for you!
Responsibilities:
- Build, deploy, and manage AI models and applications in production environments, ensuring scalability and reliability.
- Productionize AI deployments, leveraging Kubernetes, Ray, and LLMOps to run models and services at scale.
- Develop and optimize APIs using FastAPI, enabling smooth integration of AI models into various applications.
- Use tools like Chainlit, Streamlit, and vllm to build and deploy interactive AI applications, including chatbots and intelligent agents.
- Integrate large language models (LLMs) with external APIs (e.g., internet search or other services) to create advanced, multi-functional agents.
- Work with cloud platforms such as AWS and Azure to deploy, monitor, and scale AI applications effectively.
- Collaborate with Data Scientists, AI Engineers, and Software Engineers to design solutions that support both research and production needs.
- Manage and version control code using Git, ensuring efficient collaboration and deployment processes.
- Utilize machine learning frameworks such as PyTorch and TensorFlow to build and fine-tune models for production use cases.
- Contribute to the continuous improvement of the AI/ML pipeline, implementing best practices in model deployment, monitoring, and maintenance.
Requirements:
- Bachelor’s or Master’s degree in Computer Science, AI, Data Science, or a related field.
- 4+ years of experience in AI engineering or similar roles, with a focus on production-level AI deployments.
- Proficiency with Kubernetes, Ray, and cloud platforms (AWS, Azure) for scaling AI solutions.
- Hands-on experience with machine learning frameworks such as PyTorch and TensorFlow.
- Strong programming skills in Python and experience with FastAPI.
- Experience with version control systems, especially Git, in a collaborative environment.
- Knowledge of LLMOps, Chainlit, Streamlit, and vllm is required.
- Proven ability to build and deploy large-scale AI applications that involve real-time or high-performance requirements.