Engine
Join us as a
Staff ML Ops Engineer
at
Engine
and help transform business travel with cutting‑edge AI.
About Engine Engine is a growth‑stage fintech focused on simplifying corporate travel and spend management. With 20,000+ companies and a billion‑dollar annual booking volume, we combine charge cards, travel solutions, and intelligent automation to deliver personalized, world‑class experiences.
Your Mission As a Staff ML Ops Engineer on the Anti‑Fraud & AI team, you will architect and scale the infrastructure that powers our AI systems while driving the development of intelligent features that help millions of travelers. You’ll bridge advanced ML research and production‑ready systems, ensuring our AI capabilities are innovative and reliably delivered at scale.
Responsibilities
Infrastructure & Platform Engineering:
Deploy and operate ML models optimized for low‑latency, high‑throughput inference in production. Build and maintain clean gRPC and REST interfaces. Design infrastructure for RAG pipelines, vector databases, and real‑time inference systems. Optimize performance, tackle cold‑start issues, and manage memory for LLM workloads.
AI/ML Feature Development:
Own LLM‑based systems, experiment with prompts, and optimize infrastructure. Engineer production‑ready RAG systems, data ingestion pipelines, and retrieval pathways. Lead new AI‑powered feature development from proof‑of‑concept to production and design evaluation frameworks.
Platform Operations & Scaling:
Implement observability with metrics, dashboards, and automated monitoring. Containerize ML workloads, automate model promotions across environments, and manage blue‑green deployments. Deploy via GitHub Actions and Terraform, ensuring reproducible, scalable infrastructure.
Cross‑Functional Leadership:
Collaborate with product, data science, and engineering to translate business requirements into scalable AI solutions. Research emerging technologies and keep Engine at the forefront of AI capabilities.
What You'll Bring
Experience:
6+ years building and scaling ML infrastructure; hands‑on experience deploying LLM‑powered applications to production.
ML Infrastructure Expertise:
Deep knowledge of TensorFlow Serving, TorchServe, Triton, and low‑latency inference pipelines.
LLM & RAG Systems:
Proven track record building production RAG systems, vector database management (Pinecone, Weaviate, Qdrant), embedding strategies, and retrieval optimization.
Technical Excellence:
Expert‑level Python, modern ML frameworks (PyTorch, TensorFlow), LLM tooling (LangChain, LlamaIndex).
Production Systems:
Experience with Docker, Kubernetes, and coordinating ML workloads at scale.
API Development:
Strong experience building production‑grade gRPC and REST APIs that handle millions of requests.
Cloud & DevOps:
Hands‑on experience with AWS/GCP/Azure, Terraform, and CI/CD pipelines.
Monitoring & Observability:
Experience with Datadog, Prometheus, OpenTelemetry, or similar tools for production monitoring.
Bonus Points
Argo CD, MLflow, or other ML lifecycle management tools.
Background in travel, e‑commerce, or marketplace platforms.
Experience with multi‑armed bandits or online learning systems.
Familiarity with feature stores and real‑time feature serving (Redis, Kafka).
Contributions to open‑source ML/LLM projects.
Publications or presentations in the ML/MLOps community.
Applications Applications for this role will be accepted through March 1, 2026 or until the role is filled.
Compensation The base pay range is $148,200 – $205,000 USD, plus equity and/or variable pay (OTE). Final compensation details will be shared during the interview process.
The Engine Edge: Perks & Compensation
Compensation:
Competitive base pay, bonuses, commissions, and equity.
Benefits:
Full benefits list available at
engine.com/culture .
Work Environment:
Hybrid‑hub model with options for office or fully remote, ensuring you have the right environment to succeed.
Ready to Build the Future of Work Travel? Join us on our mission to transform how work travel works—for businesses, for travelers, and for the industry. Apply now and help us make travel simpler, smarter, and more enjoyable—together.
#J-18808-Ljbffr
Staff ML Ops Engineer
at
Engine
and help transform business travel with cutting‑edge AI.
About Engine Engine is a growth‑stage fintech focused on simplifying corporate travel and spend management. With 20,000+ companies and a billion‑dollar annual booking volume, we combine charge cards, travel solutions, and intelligent automation to deliver personalized, world‑class experiences.
Your Mission As a Staff ML Ops Engineer on the Anti‑Fraud & AI team, you will architect and scale the infrastructure that powers our AI systems while driving the development of intelligent features that help millions of travelers. You’ll bridge advanced ML research and production‑ready systems, ensuring our AI capabilities are innovative and reliably delivered at scale.
Responsibilities
Infrastructure & Platform Engineering:
Deploy and operate ML models optimized for low‑latency, high‑throughput inference in production. Build and maintain clean gRPC and REST interfaces. Design infrastructure for RAG pipelines, vector databases, and real‑time inference systems. Optimize performance, tackle cold‑start issues, and manage memory for LLM workloads.
AI/ML Feature Development:
Own LLM‑based systems, experiment with prompts, and optimize infrastructure. Engineer production‑ready RAG systems, data ingestion pipelines, and retrieval pathways. Lead new AI‑powered feature development from proof‑of‑concept to production and design evaluation frameworks.
Platform Operations & Scaling:
Implement observability with metrics, dashboards, and automated monitoring. Containerize ML workloads, automate model promotions across environments, and manage blue‑green deployments. Deploy via GitHub Actions and Terraform, ensuring reproducible, scalable infrastructure.
Cross‑Functional Leadership:
Collaborate with product, data science, and engineering to translate business requirements into scalable AI solutions. Research emerging technologies and keep Engine at the forefront of AI capabilities.
What You'll Bring
Experience:
6+ years building and scaling ML infrastructure; hands‑on experience deploying LLM‑powered applications to production.
ML Infrastructure Expertise:
Deep knowledge of TensorFlow Serving, TorchServe, Triton, and low‑latency inference pipelines.
LLM & RAG Systems:
Proven track record building production RAG systems, vector database management (Pinecone, Weaviate, Qdrant), embedding strategies, and retrieval optimization.
Technical Excellence:
Expert‑level Python, modern ML frameworks (PyTorch, TensorFlow), LLM tooling (LangChain, LlamaIndex).
Production Systems:
Experience with Docker, Kubernetes, and coordinating ML workloads at scale.
API Development:
Strong experience building production‑grade gRPC and REST APIs that handle millions of requests.
Cloud & DevOps:
Hands‑on experience with AWS/GCP/Azure, Terraform, and CI/CD pipelines.
Monitoring & Observability:
Experience with Datadog, Prometheus, OpenTelemetry, or similar tools for production monitoring.
Bonus Points
Argo CD, MLflow, or other ML lifecycle management tools.
Background in travel, e‑commerce, or marketplace platforms.
Experience with multi‑armed bandits or online learning systems.
Familiarity with feature stores and real‑time feature serving (Redis, Kafka).
Contributions to open‑source ML/LLM projects.
Publications or presentations in the ML/MLOps community.
Applications Applications for this role will be accepted through March 1, 2026 or until the role is filled.
Compensation The base pay range is $148,200 – $205,000 USD, plus equity and/or variable pay (OTE). Final compensation details will be shared during the interview process.
The Engine Edge: Perks & Compensation
Compensation:
Competitive base pay, bonuses, commissions, and equity.
Benefits:
Full benefits list available at
engine.com/culture .
Work Environment:
Hybrid‑hub model with options for office or fully remote, ensuring you have the right environment to succeed.
Ready to Build the Future of Work Travel? Join us on our mission to transform how work travel works—for businesses, for travelers, and for the industry. Apply now and help us make travel simpler, smarter, and more enjoyable—together.
#J-18808-Ljbffr