Job description

STLabs is an AI service management platform that resolves employee requests end-to-end, grounded in a living model of the enterprise. This matters because we're able to resolve requests with full context - the people, systems, services, and policies that define how an organization actually runs. Requests that used to take days of back-and-forth resolve in minutes, right where employees already work. About the Role Our team is currently seeking AI Engineers that will design, build, and deploy machine learning systems that form the intelligence layer of our ITSM platform. You will work on problems such as natural language understanding of IT tickets, dynamic knowledge extraction, intelligent workflow automation, and predictive insights from complex IT infrastructure data. This is a hands-on engineering role with the opportunity to define the AI foundation of a company from day one. Responsibilities - Research, prototype, and productionize machine learning models for ITSM use cases (ticket triage, incident prediction, workflow recommendations, CMDB inference). - Build scalable training and inference pipelines that integrate seamlessly into the core platform. - Experiment with LLMs, embeddings, and retrieval-augmented generation (RAG) for IT knowledge and workflow automation. - Partner with engineers and product managers to define AI-first features that differentiate our platform. - Evaluate performance, optimize models, and ensure reliability, scalability, and cost-efficiency of AI systems. - Stay current with advances in machine learning, LLMs, and AI infrastructure, and apply them pragmatically. Qualifications - Bachelor’s or Master’s in Computer Science, AI/ML, or related field; PhD is a plus. - Strong software engineering fundamentals (Python preferred) and experience with ML frameworks such as PyTorch or TensorFlow. - Experience with one or more of: natural language processing (NLP), large language models (LLMs), information retrieval, graph ML, or time-series forecasting. - Understanding of modern MLOps practices: model versioning, deployment, monitoring, and lifecycle management. - Comfort working in a fast-paced startup environment with end-to-end ownership. - Bonus: experience applying AI in enterprise software or ITSM contexts. What We Offer - Build foundational product features for an AI-first enterprise platform - The opportunity to take ownership of critical systems that scale to millions of users - A culture that values craftsmanship, autonomy, and technical excellence - Competitive compensation, equity, and benefits package - Work from our Midtown, Manhattan office, where you’ll be side-by-side with the founding team in a supportive, collaborative setting. Our team works on-site five days a week, growing and building together, and the location is easy to reach with plenty of public transportation options. As an equal opportunity employer, we don’t tolerate discrimination or harassment of any kind. Whether that’s based on race, ethnicity, age, gender identity, citizenship, religion, sexual orientation, disability, pregnancy, veteran status or any other protected characteristic as outlined by federal, state or local laws. The reasonably estimated yearly salary for this role at is: $160,000—$230,000 USD.

Requirements

Must-haves

Research, prototype, and productionize machine learning models for ITSM use cases (ticket triage, incident prediction, workflow recommendations, CMDB inference).
Build scalable training and inference pipelines that integrate seamlessly into the core platform.
Experiment with LLMs, embeddings, and retrieval-augmented generation (RAG) for IT knowledge and workflow automation.
Partner with engineers and product managers to define AI-first features that differentiate our platform.
Evaluate performance, optimize models, and ensure reliability, scalability, and cost-efficiency of AI systems.
Stay current with advances in machine learning, LLMs, and AI infrastructure, and apply them pragmatically.
Experience with one or more of: natural language processing (NLP), large language models (LLMs), information retrieval, graph ML, or time-series forecasting.
Understanding of modern MLOps practices: model versioning, deployment, monitoring, and lifecycle management.
Comfort working in a fast-paced startup environment with end-to-end ownership.

Nice-to-haves

Bachelor’s or Master’s in Computer Science, AI/ML, or related field; PhD is a plus.
Strong software engineering fundamentals (Python preferred) and experience with ML frameworks such as PyTorch or TensorFlow.
Bonus: experience applying AI in enterprise software or ITSM contexts.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimachine learningmlpython

Platform: ashby
Effort: quick