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    Staff Engineer- Machine Learning - Redwood City, California, United States - Sumo Logic

    Sumo Logic
    Sumo Logic Redwood City, California, United States

    Found in: beBee S2 US - 3 weeks ago

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    Description

    Staff Engineer - Machine Learning


    Location- 100% remote within USA or Canada

    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.

    Responsibilities:

    • Identifying and validating opportunities for the application of ML or data-driven techniques
    • Driving technical delivery through the full feature lifecycle, from idea to production and operations
    • Collaborating within and beyond the team to identify problems and deliver solutions
    • Assessing requirements and approaches for large-scale data and ML platform components
    • Collaborating with UX/UI teammates on the usability of product features
    • Owning the uptime and reliability of delivered services and capabilities, including on-call rotation
    • Developing supporting tooling, automation, and microservices to accelerate the team

    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

    Desirable:

    • 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

    About Us

    Sumo Logic, Inc. empowers the people who power modern, digital business. Sumo Logic enables customers to deliver reliable and secure cloud-native applications through its Sumo Logic SaaS Analytics Log Platform, which helps practitioners and developers ensure application reliability, secure and protect against modern security threats, and gain insights into their cloud infrastructures. Customers worldwide rely on Sumo Logic to get powerful real-time analytics and insights across observability and security solutions for their cloud-native applications. For more information, visit

    Sumo Logic Privacy Policy

    The expected annual base salary range for this position is $190,000 - $235, % bonus. In addition to base pay, certain roles are eligible to participate in our bonus or commission plans, as well as our benefits offerings, and equity awards. Compensation varies based on a variety of factors which include (but aren't limited to) role level, skills and competencies, qualifications, knowledge, location, and experience.

    Other details

    • 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

    #LI-DNI

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