Machine Learning EngineerGlodaris Technologies

• Deploy models to production
• Optimize models for better latency and throughput
• A/B testing of candidate models
• Inference testing on variety of hardware: edge, CPU, GPU
• Monitoring model performance, maintenance, debugging
• Maintaining model versions, experiments and metadata

Tech Stack:

• Linux
• Cloud: AWS/Azure/GCP; SageMaker, S3, EC2, Boto
• Machine learning: Scikit-learn, Fast.ai, AllenNLP, OpenCV, HuggingFace
• Deep learning: TensorFlow, PyTorch, MXNet, JAX, Chainer etc.
• Serving: TensorFlow Serving, TensorRT, TorchServe, MXNet Model Server
• Python
• C++
• Scala
• Bash
• Git, Github/Bitbucket

Requirements

• Bachelor's Degree with 4 years experience.

Skills:

• Data structures
• Data modeling
• Programming
• Software engineering
• ML frameworks like TensorFlow, PyTorch, Scikit-learn etc.
• Statistics
• Conceptual knowledge of ML to understand use cases and interact with data scientists and other stakeholders