Role overview
Build and integrate end to end lifecycles of large-scale, distributed machine learning systems using the latest public cloud & open source technologies. Train, evaluate, and debug machine learning models for complex tasks. Develop tools and services for improving ML systems reliability & accuracy beyond modeling choices — model ops. Collaborate with data engineers to solve complex data problems at scale. Lead technical projects to completion. Collaborate with Data scientists & analysts. Contribute to a team culture that values engineering excellence, continuous improvement and innovation. Estimated salary range for this position is $129932.84 - $168912.69 / year depending on experience.
What we're looking for
Degrees:
- Bachelors.
Additional Qualifications:
- Bachelors, Masters, or PhD Degree in Computer Science/Machine Learning or equivalent professional experience.
- Strong background in machine learning and artificial intelligence with expertise in one or more of: computer vision, NLP, speech, optimization, deep learning, reinforcement learning, time series, generative models, signals, and distributed systems.
- Proficiency in ML modeling frameworks.
- Strong overall software development approach.
- Significant experience building end to end data systems.
- Strong software engineering skills with proven experience crafting, prototyping, and delivering advanced algorithmic solutions.
- Proficiency in one or multiple machine learning languages (ex: Python) & development environments such as AWS Sagemaker.
EOE, including disability/vets