About SubBase
SubBase is revolutionizing construction procurement by streamlining material management for subcontractors and self-performing general contractors. Our platform replaces fragmented workflows with a unified, user-friendly solution that enhances efficiency without disrupting existing processes. By connecting field teams, office staff, and vendors, we empower construction professionals to manage procurement seamlessly.
Role:
We are seeking an experienced Senior Applied Machine Learning Engineer to drive the development and integration of AI-driven solutions within our platform. This role involves leveraging existing AI models and creating custom algorithms to optimize procurement processes, enhance decision-making, and deliver actionable insights for our users.
Key Responsibilities:
- Design, develop, and deploy machine learning models tailored to solving challenges faced by many players within the construction industry.
- Work closely with cross-functional teams, including product managers, software engineers, and domain experts, to align AI solutions with business objectives.
- Implement monitoring systems to evaluate model performance, ensuring accuracy, reliability, and impact towards business objectives
- Utilize APIs from providers like OpenAI and Google Gemini to incorporate advanced AI capabilities into our platform.
- Build and maintain robust data pipelines to support model training and real-time analytics.
- Stay abreast of the latest developments in AI and machine learning to continuously enhance our platform’s capabilities.
- Own the full lifecycle of LLM prompt development — from dataset curation and test harness setup (e.g. Promptfoo) to model comparison and performance tuning.
Who you are:
- 6+ years in machine learning engineering, with a proven track record of building and deploying models in production environments.
- At least Master’s degree in Computer Science, Data Science, or a related field.
Key Skills:
- Proficiency in programming languages such as Python and Ruby.
- Strong understanding of data structures, data modeling, and software architecture.
- Experience building production level data pipelines that utilize internal and external data to support models in production.
- Experience leveraging LLM, computer vision, and other external models such as GPT, Gemini in building production level applications.
- Experience with machine learning frameworks like TensorFlow, PyTorch, or scikit-learn.
- Experience with deploying ML models in production environments, particularly within a Ruby on Rails stack.
- Familiarity with cloud platforms (AWS, GCP, Azure) for scalable AI/ML deployments.
- MVP centric mentality, focused on delivering impact with speed
- Excellent problem-solving abilities and analytical skills.
- Strong communication skills, with the ability to convey complex technical concepts to non-technical stakeholders.
- Customer-focused and highly collaborative - proactively tackle small and large responsibilities with a positive attitude and an open mindset to help lead and learn from partner teams.