Sumo Logic
Machine Learning Engineer
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
Machine Learning Engineer , you’ll build the intelligence behind the next generation of
agentic AI systems
that reason over massive, heterogeneous log data. You’ll combine machine learning, prompt engineering, and rigorous evaluation to create autonomous AI agents that help organizations understand and act on their data in real time. You’ll be part of a small, high-impact team shaping how AI agents understand complex machine data. This is an opportunity to work on cutting-edge LLM infrastructure and contribute to defining best practices in context engineering and AI observability. Responsibilities
Design, implement, and optimize
agentic AI components including context engineering, memory management, and prompts. Develop and maintain
golden datasets by defining sourcing strategies, working with data vendors, and ensuring quality and representativeness at scale. Prototype and evaluate
novel prompting strategies and reasoning chains for model reliability and interpretability. Collaborate cross-functionally
with product, data, and infrastructure teams to deliver end-to-end AI-powered insights. Operate autonomously
in a fast-paced, ambiguous environment - defining scope, setting milestones, and driving outcomes. Ensure reliability, performance, and observability
of deployed agents through rigorous testing and continuous improvement. Maintain a strong bias for action —delivering incremental, well-tested improvements that directly enhance customer experience. Required Qualifications
B.Tech, M.Tech, or Ph.D. in Computer Science, Data Science, or a related field. 1-2 years of hands‑on industry experience with demonstrable ownership and delivery. Strong understanding of machine learning fundamentals, data pipelines, and model evaluation. Proficiency in Python
and ML/data libraries (NumPy, pandas, scikit‑learn); familiarity with JVM languages is a plus. Working knowledge of
LLM core concepts , prompt design, and
agentic design patterns . Strong communication skills and a passion for shaping emerging AI paradigms. Desired Qualifications
Prior experience
building and deploying AI agents
or LLM applications in production. Familiarity with modern
agentic AI frameworks
(e.g., LangGraph, LangChain, CrewAI). Experience with
ML infrastructure and tooling
(PyTorch, MLflow, Airflow, Docker, AWS). Exposure to
LLM Ops
- infrastructure optimization, observability, latency, and cost monitoring. Located in the Pacific Time zone 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 www.sumologic.com. Sumo Logic Privacy Policy. Employees will be responsible for complying with applicable federal privacy laws and regulations, as well as organizational policies related to data protection. The expected annual base salary range for this position is $148,000 - $173,200. 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. 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. Must be authorized to work in the United States at time of hire and for duration of employment. At this time, we are not able to offer nonimmigrant visa sponsorship for this position.
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Machine Learning Engineer , you’ll build the intelligence behind the next generation of
agentic AI systems
that reason over massive, heterogeneous log data. You’ll combine machine learning, prompt engineering, and rigorous evaluation to create autonomous AI agents that help organizations understand and act on their data in real time. You’ll be part of a small, high-impact team shaping how AI agents understand complex machine data. This is an opportunity to work on cutting-edge LLM infrastructure and contribute to defining best practices in context engineering and AI observability. Responsibilities
Design, implement, and optimize
agentic AI components including context engineering, memory management, and prompts. Develop and maintain
golden datasets by defining sourcing strategies, working with data vendors, and ensuring quality and representativeness at scale. Prototype and evaluate
novel prompting strategies and reasoning chains for model reliability and interpretability. Collaborate cross-functionally
with product, data, and infrastructure teams to deliver end-to-end AI-powered insights. Operate autonomously
in a fast-paced, ambiguous environment - defining scope, setting milestones, and driving outcomes. Ensure reliability, performance, and observability
of deployed agents through rigorous testing and continuous improvement. Maintain a strong bias for action —delivering incremental, well-tested improvements that directly enhance customer experience. Required Qualifications
B.Tech, M.Tech, or Ph.D. in Computer Science, Data Science, or a related field. 1-2 years of hands‑on industry experience with demonstrable ownership and delivery. Strong understanding of machine learning fundamentals, data pipelines, and model evaluation. Proficiency in Python
and ML/data libraries (NumPy, pandas, scikit‑learn); familiarity with JVM languages is a plus. Working knowledge of
LLM core concepts , prompt design, and
agentic design patterns . Strong communication skills and a passion for shaping emerging AI paradigms. Desired Qualifications
Prior experience
building and deploying AI agents
or LLM applications in production. Familiarity with modern
agentic AI frameworks
(e.g., LangGraph, LangChain, CrewAI). Experience with
ML infrastructure and tooling
(PyTorch, MLflow, Airflow, Docker, AWS). Exposure to
LLM Ops
- infrastructure optimization, observability, latency, and cost monitoring. Located in the Pacific Time zone 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 www.sumologic.com. Sumo Logic Privacy Policy. Employees will be responsible for complying with applicable federal privacy laws and regulations, as well as organizational policies related to data protection. The expected annual base salary range for this position is $148,000 - $173,200. 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. 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. Must be authorized to work in the United States at time of hire and for duration of employment. At this time, we are not able to offer nonimmigrant visa sponsorship for this position.
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