Key Responsibilities
- Develop and deploy machine learning models for production-scale applications
- Design and optimize ML pipelines for training, evaluation, and inference
- Collaborate with data scientists to translate research into scalable solutions
- Implement MLOps practices for model monitoring, versioning, and CI/CD
- Optimize model performance for latency, accuracy, and resource efficiency
- Lead technical discussions on model architecture and deployment strategies
Requirements
- 7+ years of experience in applied machine learning or related fields
- Expertise in deep learning frameworks (TensorFlow, PyTorch) and ML tooling
- Strong background in statistics, linear algebra, and optimization
- Experience with cloud platforms (AWS/GCP) and distributed computing
- Ability to design scalable ML systems and drive technical innovation