Machine Learning Engineer

🔬 Machine Learning Engineer – Deep Tech Startup | High Compensation + Equity

We’re working with a venture-backed AI startup building a next-gen video intelligence platform for real-world environments. Their elite founding team (ex-Big Tech, top AI labs) is solving cutting-edge ML and systems problems at the intersection of computer vision, edge computing, and deep learning.

They’re now looking for a Machine Learning Engineer to help deploy vision models into production systems that operate with tight latency and throughput constraints.

🎯 What You’ll Be Doing

• Fine-tuning open-source PyTorch vision models on proprietary datasets
• Optimizing and deploying models into real-time C++ runtimes for inference at the edge
• Designing experiments to explore accuracy vs latency trade-offs
• Owning model integration across the product and measuring impact in production
• Maintaining and improving ML systems deployed across a distributed environment
• Staying up-to-date with the latest research in deep learning, vision, and foundation models, and turning ideas into deployed features

🧠 What You Bring

• Strong foundations in ML: linear algebra, probability, supervised/self-supervised learning
• Solid software engineering skills — you can write clean, production-grade code
• Curiosity and fluency in modern AI research, particularly in vision and LLMs
• Understanding of Docker and containerized workflows

⚙️ Bonus Experience

• PyTorch: training, fine-tuning, model export
• C++ for production inference and deployment
• Tools like TorchScript, ONNX Runtime, TensorRT
• Familiarity with quantization (INT8, FP16) and performance optimization for inference