Senior Applied Machine Learning Engineer

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.