Senior Machine Learning Engineer – Context Engineering

GEICO

full-time

Posted on: 9/21/2025

Origin: • 🇺🇸 United States • California, New York

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💰 $115,000 - $230,000 per year

Senior

AirflowJavaKafkaKubernetesNeo4jOpen SourcePostgresPythonSDLC

About the role

Own development of key platform components that power end-to-end GenAI agentic workflows (knowledge curation & management, search, context management, workflow orchestration).
Collaborate with cross-functional teams including data scientists, ML engineers, software engineers, product managers, designers to gather requirements, define project scope and prioritize feature backlogs.
Establish pragmatic visions & roadmaps balancing business outcomes, product release timelines and engineering excellence.
Contribute to selection, evaluation, and implementation of software technologies, tools, and frameworks.
Lead a small team of engineers for feature & system implementation.
Troubleshoot and resolve complex software issues ensuring optimal platform performance and reliability.
Mentor and guide junior engineers via code reviews and design sessions, elevating AI engineering best practices across the company.

5+ years of experience designing and building AIML platform and systems utilizing components such as vectordb (e.g. Qdrant, Milvus), data warehouse (e.g. snowflake), streaming platform (e.g. Kafka), relational database (e.g. postgresql), knowledge graph (e.g. neo4j), workflow orchestration (e.g. Airflow, Temporal).
Proficient in Python, Java and similar general-purpose programming languages.
3+ years’ experience managing end-to-end software development life cycle (e.g. CICD pipelines, Kubernetes-based deployments, testing, monitoring & alerting, production support etc.) for backend systems and APIs.
2+ years’ experience building training, finetuning, real-time/batch inferencing and evaluation systems for AIML models and LLMs, esp. utilizing GPU-powered infrastructure.
Bachelor’s degree or above in Computer Science, Engineering, Statistics or a related field.
3+ years of experience building enterprise-level semantic knowledge-graph & related capabilities (preferred).
2+ years’ experience utilizing and/or finetuning open source LLMs, Llama, Mistral, Claude etc. (preferred).
Strong communication and problem-solving skills.