Staff Engineer – Machine Learning at Sumo Logic
Redwood City, CA, US
Staff Engineer – Machine Learning
“It would be an unsound fancy and self-contradictory to expect that things which have never yet been done can be done except by means which have never yet been tried.” – Francis Bacon, Novum Organum Scientiarum (1620)
At Sumo Logic, we empower software-driven businesses by providing unpreceded real-time visibility into their applications and infrastructure via the analysis of vast quantities of machine data such as logs and metrics.
But even with full observability, the scale and complexity of this machine data threatens to overwhelm the attention and capabilities of the engineers entrusted with the security and reliability of business-critical systems. The path forward for understanding machine behavior leads to machine collaboration: human experts interacting with and being assisted by powerful machine learning algorithms capable of drawing insights from petabytes of data.
As the industry’s only cloud-based multi-tenant unified machine data analytics platform, Sumo Logic is uniquely positioned to execute on this vision, and we’re looking for a product-driven, customer-oriented machine learning engineer to join us on this journey. This role is an incredible opportunity to use machine learning to build product features that amplify the capabilities of the engineers who are driving digital businesses and transformations across the global economy. If you’re currently juggling both the Google SRE book and Goodfellow et al’s Deep Learning, we’d love to talk.
We are looking for a versatile technologist whose responsibilities will include:
working with users and Product Managers to formulate customer needs as ML problems
driving technical delivery: dataset creation, experimentation, prototyping, implementation, testing, deployment, monitoring and continuous improvement
collaborating with UX/UI teammates on the usability of data-driven product features
assessing needs and solutions for large-scale data infrastructure
owning the uptime and reliability of ML-related services and capabilities
B.S. / M.S. / Ph.D. in Computer Science or related disciplines
≥ 5 years professional experience in software engineering and applied machine learning
strong technical background in: machine learning/statistics, software engineering of production-grade services, theoretical thinking, problem formulation and solving
excellent collaboration and communication skills