Senior AI Engineer

ServiceTitan•US CA Remote, CA

2d•$168,200 - $269,900•Remote

About The Position

In this position, you will design and implement cutting-edge machine learning systems that power our next generation of customer experiences. You will engage with multiple internal teams, including engineering, infrastructure, data science, and growth. We build for perfection, use Python and the most modern tools on Azure Cloud, have an amazing culture, and love to solve complex, real-time problems.

Requirements

5+ years of experience writing production-level code in Python.
2+ years of experience deploying machine learning models — such as NLP, speech, forecasting, or recommendation systems — to production at scale.
Experience with designing, building, and deploying scalable ML inference services to support real-time or high-throughput applications.
Advanced knowledge of machine learning methods and algorithms across traditional ML methods and deep learning theory and techniques.
Experience with reinforcement learning (RL) techniques and implementing continuous learning/online optimization systems for production.
Strong understanding of the machine learning project lifecycle, from experimentation to production deployment.
Experience with databases/data warehouses such as SQL Server, PostgreSQL, Redshift, Snowflake.
Experience with public cloud environments such as Azure or AWS.
Experience with microservices and asynchronous messaging technologies like Kafka, Azure Service Bus, etc. (critical for high-volume, real-time systems).
Experience with serverless architecture (Azure Functions, AWS Lambda, etc.).
Experience with Git, unit testing, debugging, profiling, JIRA, and other tools typically used by developers.
Comfortable working in a fast-paced environment with a globally distributed team.

Nice To Haves

Familiarity with AIOps and MLOps practices.
Experience with Azure Cognitive Services or similar cloud-based AI offerings is a plus.

Responsibilities

Design and implement scalable, low-latency ML systems and services, including model training, inference, and deployment infrastructure.
Collaborate with product teams to integrate and operationalize machine learning models — including foundational models (like LLMs), traditional ML models, and specialized models for domains such as speech, NLP, and forecasting — into production.
Optimize the performance and real-time responsiveness of ML pipelines to ensure superior customer experience and minimal latency.
Communicate effectively with other engineers, product managers, customers, and partners.

Benefits

Flexible time off
Learning and development opportunities
Comprehensive onboarding program
Leadership training
Peer-nominated awards
Company-paid medical, dental, and vision (with 100% employer paid options and 90% coverage for dependents)
FSA and HSA
401k match
Telehealth options including memberships to One Medical
Parental leave and support
Up to $20k in fertility services (i.e. IUI and IVF)
Surrogacy and adoption reimbursement
On demand maternity support through Maven Maternity
Free breast milk shipping through Maven Milk
Pet insurance
Legal advisory services
Financial planning tools