This job is closed
We regret to inform you that the job you were interested in has been closed. Although this specific position is no longer available, we encourage you to continue exploring other opportunities on our job board.
Research Engineer, Model Inference
Otter.Ai - Moffett Field, CA
posted 2 months ago
About the position
The Research Engineer position at Otter.ai focuses on model optimization and integration of machine learning models into production environments. The role aims to enhance the efficiency and performance of AI technologies to improve the value of conversations through innovative solutions. The engineer will collaborate with cross-functional teams to deploy machine learning models for real-time applications, ensuring low latency and high throughput while maintaining scalability.
Responsibilities
- Collaborate with machine learning researchers to understand model architectures and algorithms.
- Implement optimization techniques to enhance machine learning models' efficiency and inference speed on production.
- Work closely with product engineers to integrate machine learning models into production systems in a scalable way.
- Optimize models for real-time inference, ensuring low latency and high-throughput.
- Set up monitoring systems to track model performance in real time.
- Ensure models can scale horizontally to handle increased load.
- Implement strategies for resource-efficient inference, considering factors such as memory usage and CPU/GPU utilization.
- Provide technical expertise on inference-related matters during the model development lifecycle.
- Document the deployment and optimization processes for machine learning models.
Requirements
- Master's degree + 3 years of industry experience or Ph.D. degree in computer science, machine learning, speech/language processing or related field.
- Experience in PyTorch.
- Proficiency in Python.
- Experience in C++.
- Basic knowledge of CUDA.
- Strong understanding of machine learning models, algorithms, and deployment strategies.
- Experience with model optimization techniques and performance profiling.
- Familiarity with Docker and Kubernetes.
- Knowledge of AWS.
- Experience with monitoring tools.
Benefits
- Competitive salary range of $175,000 to $220,000 USD per year.
- Comprehensive total rewards package.
