Senior Applied Machine Learning Engineer

Job not on LinkedIn

November 4

🐊 Florida – Remote

Although this job is listed in Florida, this company may be open to hiring remote in other states.

⏰ Full Time

🟠 Senior

🤖 Machine Learning Engineer

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SubBase

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SubBase is a centralized technology platform simplifying outdated workflows in construction materials management. Say goodbye to the days of fumbling through manual, paper-based workflows and say hello to a streamlined procurement experience that gets you back in control without changing how it's always done. Crafted by the hands of construction veterans and sharpened by cutting-edge tech, SubBase is your go-to for a user-friendly interface that makes efficiency with the field, office, and vendors second nature.

11 - 50 employees

Founded 2022

📋 Description

• 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.

🎯 Requirements

• 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. • 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.