As a Machine Learning Engineer at Sumo Logic, you will actively contribute in the design and development of innovative ML-powe'red product capabilities to help our customers make sense of their huge amounts of log data. This involves working 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
• Assessing requirements and approaches for large-scale data and ML platform components
• Driving technical delivery through the full feature lifecycle, from idea to production and operations
• Helping the team design and implement extremely high-volume, fault-tolerant, scalable backend systems that process and manage petabytes of customer data.
• Collaborating within and beyond the team to identify problems and deliver solutions
• Work as a member of a team, helping the team respond quickly and effectively to business needs.

Requirements

• B.Tech, M.Tech, or Ph.D. in Computer Science or related discipline
• 4+ years of industry experience with a proven track record of ownership and delivery
• Experience formulating use cases as ML problems and putting ML models into production
• Solid grounding in core ML concepts and basic statistics
• Experience with software engineering of production-grade services in cloud environments handling data at large scale

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
• Experience in multi-threaded programming and distributed systems
• Agile software development experience (test-driven development, iterative and incremental development) is a plus.