Sr. ML Operations Engineer
About The Position
At Trunk Tools, we’re the leading AI company revolutionizing construction—the second-largest industry on earth. We recently raised a $40M Series B led by Insight Partners, bringing our total funding to $70M from top-tier investors including Redpoint and Innovation Endeavors. This new round is fueling our next phase of growth as we scale AI agents across the jobsite. Our mission is to build the future of construction through intelligent automation. Despite being a $13+ trillion industry, construction still runs largely on analog processes—we’re changing that by embedding AI directly into field operations. Founded by builders and technologists (Stanford, MIT), our team has delivered software used by over 140,000 field professionals, impacting millions of users and contributing to $10B+ in built projects. Many of us come from the field ourselves, giving us a deep understanding of the industry’s unique challenges. After years of building the “brain” of construction, we’re now launching production-ready AI agents—starting with intelligent document processing and Q&A, and rapidly expanding into core operational workflows. Our team has doubled in the past year, and with 65+ employees (25+ engineers), we’re scaling fast and entering a period of hypergrowth—this is a rare opportunity to join at an inflection point.
Requirements
- BS/MS in Computer Science, Data Science, or related technical discipline
- 5+ years experience in ML Operations, with at least 3 years focused on scalable AI/ML deployments
- Strong proficiency with cloud infrastructure (preferably AWS), container technologies (Docker, Kubernetes), and modern MLOps frameworks
- Extensive experience managing GPU and CPU resources for specialized AI workloads (Computer Vision, NLP, or LLM fine-tuning)
- Practical experience with data quality and performance monitoring in production ML environments
Nice To Haves
- Experience designing data architectures optimized for AI/ML (vector, graph databases)
- Familiarity with RAG systems and agentic applications
Responsibilities
- Develop and manage infrastructure for distributed model training (e.g., SageMaker, Ray, Kubernetes).
- Deploy ML models using containerization (Docker), orchestration tools (Kubernetes, ECS), and serving frameworks
- Integrate ML workflows seamlessly with CI/CD pipelines for efficient model building, testing, and deployment
- Create and maintain robust data and ML pipelines using Prefect, Airflow, or custom orchestration tools
- Implement comprehensive experiment tracking (MLflow, Weights & Biases) and observability systems (Arize, Evidently)
- Establish effective monitoring, logging, and governance practices for ML systems.
Benefits
- A close-knit and collaborative early-stage startup environment where every voice is heard and every opinion matters
- Competitive salary and stock option equity packages
- 3 Medical Plans to choose from including 100% covered option. Plus Dental and Vision Insurance!
- Learning & Growth stipend
- Flexible long-term work options (remote and hybrid)
- Free lunch provided in the office in NYC & Austin - you’ll never go hungry with us!
- Unlimited PTO; We truly believe in work-life balance and that hard work should be balanced with time for rest and rejuvenation
- IRL / In-Person retreats throughout the year
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Number of Employees
51-100 employees
