Sr ML Engineer, Admin Central

Description

The company is a Fortune 500 AI platform for managing people, money, and agents, and it is hiring two teams of Senior ML Engineers.

The Admin Central team is changing how administrators work across the platform, replacing scattered tools and disconnected AI with one unified experience where implementations rely on built-in intelligence instead of manual effort.

The Business Process Optimize (BPO) team builds the core platform infrastructure, including distributed systems, high-availability usage pipelines, agentic features, and event-driven data flows across global regions to keep enterprise billing accurate at scale. The team builds from scratch and moves quickly, and its work reaches thousands of admins daily.

Responsibilities

• Build and run end-to-end ML pipelines, from distributed data ingestion and feature engineering through training, evaluation, and production deployment.
• Design algorithms and LLM-driven recommendation features, such as IDD insights and next-best-action models, that improve agentic workflows and tool usage.
• Optimize real-time model inference and scoring microservices so responses arrive in under a second in high-concurrency, multi-tenant environments.
• Add telemetry and tracing with OpenTelemetry, LangChain, and LangSmith to ML pipelines to monitor model performance, prompt and response drift, and execution efficiency.
• Work with core backend engineers on big data platforms such as ClickHouse, Apache Iceberg, and Spark to support high-dimensional feature retrieval and analytics.
• Work closely with Product Managers, Data Engineering, SRE, and Legal/Compliance to turn business and governance needs into scalable ML solutions.

Requirements

• At least 8 years of machine learning development, including research, building, and deploying advanced models, with at least 4 years focused on operating production ML systems at scale.
• At least 5 years of deep learning, NLP, and GenAI/LLM orchestration experience using frameworks such as PyTorch, TensorFlow, Scikit-learn, LangChain, and LlamaIndex, plus proficiency in Java, Go, Scala, or C++ for high-performance backend systems.
• Experience with distributed processing (Spark, Flink, Kafka) and high-throughput columnar or vector storage (ClickHouse, Pinecone, Milvus) to build reliable ML data pipelines.
• Working knowledge of RAG architectures, LLM fine-tuning, intent classification, and recommendation engines, applying ML algorithms and model-based design, including MCP tooling, to multi-agent orchestration, contextual reasoning, and workflow optimization.
• Experience running exploratory data analysis on multi-tenant execution logs to check prompt and response accuracy and improve tool usage, plus strong feature engineering for vector embeddings, feature stores, and tenant data isolation.
• Experience leading model work such as foundation model adaptation, prompt engineering, fine-tuning, and low-latency inference, with a solid grasp of the model lifecycle and MLOps platforms (Kubeflow, MLflow, Airflow, SageMaker) for monitoring, latency tracking, and retraining at scale.
• Strong Python skills and experience with ML libraries (PyTorch, TensorFlow, NumPy, Pandas, Scikit-learn, LangChain, LangSmith, DSPy), including deploying scalable cloud-native systems with Docker, Kubernetes, gRPC or REST APIs, and CI/CD, meeting 99.9% uptime and low-latency SLAs.
• Ability to mentor team members, align technical direction across functions, write system design specs and model cards, and explain technical and governance decisions clearly.
• A bachelor's degree in Computer Science, Data Science, Machine Learning, Applied Mathematics, Statistics, or Engineering is required; a master's or PhD is preferred.

Conditions

Primary location is Pleasanton, California, USA.

Flex work: you spend at least 50% of your time each quarter in the office or in the field with customers, prospects, and partners, depending on your role, with no fixed number of office days.

Remote home-office roles can still join in-office gatherings for important moments.

Equal opportunity employer, including individuals with disabilities and protected veterans, and the company considers applicants with arrest and conviction records under applicable Fair Chance law.

Benefits

• Base pay ranges are $192,000 to $288,000 USD in Pleasanton, and $163,000 to $288,000 USD in other US locations, with final offers based on geography, experience, skills, duties, and business need.
• The role may be eligible for the company Bonus Plan or a role-specific commission or bonus.
• The role may also be eligible for annual refresh stock grants.