[Hiring] Junior Lead ML Engineer - Computer Vision @Benchmark Construction Technology Corp

Role Description

You’ll work alongside experienced engineers to improve our AI-enabled plan ingestion pipeline—from raw PDFs to clean, dependable outputs that power takeoff, design, and downstream automation. You’ll begin by contributing to well-scoped projects and supporting senior engineers, with the opportunity to take on greater ownership as you grow.

What You’ll Do

• Support the development and improvement of machine learning systems for object detection, segmentation, document understanding, and information extraction from building plans
• Train, evaluate, and debug computer vision models using real-world construction data
• Help build and maintain datasets, labeling workflows, preprocessing pipelines, and evaluation tools
• Contribute to experiments involving computer vision, document understanding, and related machine learning techniques
• Assist with integrating models into production applications and APIs
• Write clean, testable, and maintainable Python code
• Investigate model failures and help identify opportunities to improve accuracy and reliability
• Collaborate with senior engineers to understand technical requirements and turn them into working solutions
• Document experiments, results, decisions, and lessons learned
• Learn and apply engineering practices for testing, deployment, observability, and maintainability

Qualifications

• 1–2 years of professional, internship, research, or equivalent project experience in machine learning, computer vision, or a closely related area
• A degree in computer science, engineering, mathematics, data science, or a related technical field, or equivalent practical experience
• Strong Python fundamentals and experience using PyTorch or a similar deep learning framework
• Familiarity with computer vision tasks such as object detection, image segmentation, classification, or OCR
• Basic understanding of image processing concepts and tools such as OpenCV
• Familiarity with Linux and Git
• Experience working with data, training models, evaluating results, and debugging failures
• Willingness to ask questions, receive feedback, and learn from more experienced engineers
• Clear communication skills and comfort working with a remote and cross-cultural team

What Makes You a Great Fit

• You have strong technical fundamentals and are excited to apply them to real-world problems
• You enjoy experimenting, debugging, and understanding why a model succeeds or fails
• You take responsibility for your work while knowing when to ask for help
• You care about writing clear, reliable code—not just producing promising model results
• You are curious, motivated to improve, and comfortable working on problems without obvious solutions
• You communicate clearly about your progress, questions, and blockers

Bonus Points

• Academic, internship, or personal project experience involving document understanding, OCR, or technical drawings
• Experience with detection or segmentation frameworks
• Familiarity with FastAPI, Docker, ClearML, or MLflow
• Interest in multi-modal models, language models, NLP, or retrieval-augmented generation
• Exposure to model deployment, inference optimization, or data-labeling workflows
• A portfolio, GitHub repository, research project, or other examples of technical work

What We Offer

• Competitive salary + meaningful equity
• Comprehensive benefits (health, dental, vision)
• Professional development budget (courses, conferences, research exploration)
• Mentorship from experienced engineers
• Real-world ML problems with direct impact
• Clear opportunities for increased ownership and career growth

Interview Process

• Screening call
• Online skills assessment
• 30-minute conversation with our CPO
• Technical interview with our CTO and engineering team