Staff Engineer- Machine Learning

April 10

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Sumo Logic

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Sumo Logic’s vision is to make the world's digital experiences reliable and secure.

Log Management • Analytics • SaaS • Big Data • Machine Data

501 - 1000

💰 $110M Series G on 2019-05

Description

The proliferation of machine log data has the potential to give organizations unprecedented real-time visibility into their infrastructure and operations. With this opportunity comes tremendous technical challenges around ingesting, managing, and understanding high-volume streams of heterogeneous data. As a Staff Software Engineer - Machine Learning, you will actively contribute and lead in the design and development of innovative ML-powered product capabilities. This team collaborates closely with other Product Development teams and works through the entire feature lifecycle including ideation, dataset construction, experimental validation, prototyping, production implementation, deployment, and operations.

Requirements

• B.S. / M.S. / Ph.D. in Computer Science or related disciplines • 6-8+ years of industry experience with a proven track record of ownership and delivery • Excellent collaboration and communication skills • Experience with software engineering of production-grade services in cloud environments • Experience formulating use cases as ML problems and putting ML models into production • Knowledge of and/or curiosity to learn about specific Sumo Logic customer problem domains • Operational excellence orientation: SLIs/SLOs, monitoring and troubleshooting, on-call rotations • Solid grounding in core ML concepts, basic statistics, and the judicious use of abstraction • Cloud-based application and infrastructure deployment and management • Common ML libraries (eg, scikit-learn, PyTorch) and components (eg, Airflow, MLFlow) • Relevant cloud provider services (eg, AWS Sagemaker) • LLM core concepts, libraries, and application design patterns

Benefits

• Health, Dental, Vision- Insurance • 401k and Life Insurance options • Unlimited PTO with 15+ days of recognized holidays • Quarterly Wellness days • 100% remote with the option to be in the office if you want (Bay Area, Austin, Denver, NYC) • 3 months of paid parental leave