[Remote] Machine Learning Engineer

Note: The job is a remote job and is open to candidates in USA. Sumo Logic, Inc. helps make the digital world secure, fast, and reliable by unifying critical security and operational data through its Intelligent Operations Platform. 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 and work on cutting-edge LLM infrastructure.

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

Skills

• 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
• Must be authorized to work in the United States at time of hire and for duration of employment
• 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

Benefits

• Bonus or commission plans
• Benefits offerings
• Equity awards

Company Overview