Join us as a Machine Learning Engineer and help bring our zero-shot discovery models from research to production. You'll bridge the gap between cutting-edge ML research and scalable, reliable systems.

Responsibilities

• Deploy and optimize ML models for production serving.
• Build robust MLOps pipelines for training, evaluation, and deployment.
• Optimize CUDA kernels and model inference for latency-critical applications.
• Implement micro-batching, caching, and quantization strategies.
• Collaborate with researchers to productionize novel architectures.

Qualifications

• 3+ years of experience in ML engineering or related roles.
• Deep knowledge of PyTorch and deep learning fundamentals.
• Experience with ONNX, TensorRT, or model quantization.
• Strong software engineering skills (Python, testing, CI/CD).
• Familiarity with distributed training and serving infrastructure.