Junior Lead ML Engineer - Computer Vision

Benchmark Construction Technology Corp; United States; Remote; USD 85,000 - 110,000; Full time

Job summary

Benchmark Construction Technology Corp is seeking an entry-level machine learning engineer to join our AI-enabled plan ingestion pipeline team. You’ll work with experienced engineers to move from raw PDFs to clean outputs powering takeoff, design, and downstream automation.

You will contribute to CV models, datasets, labeling workflows, and production integration. Ideal candidate has 1–2 years in ML/CV, a CS/engineering/math degree, and strong Python with PyTorch/OpenCV; willingness to learn and

Qualifications

• 1–2 years of ML/CV experience or relevant internship
• Degree in CS/engineering/math/data science or equivalent
• Strong Python fundamentals and PyTorch/OpenCV familiarity
• Experience with data, training models, evaluating results

Responsibilities

• Support ML systems for object detection, segmentation, and information extraction from building plans
• Train, evaluate, and debug computer vision models using real-world construction data
• Build and maintain datasets, labeling workflows, preprocessing pipelines, and evaluation tools
• Contribute to experiments involving computer vision and related ML techniques
• Assist with integrating models into production apps and APIs
• Write clean, testable Python code
• Investigate model failures and improve accuracy and reliability
• Collaborate with senior engineers to translate requirements into solutions
• Document experiments, results, decisions, and lessons learned
• Learn and apply testing, deployment, observability, and maintainability practices

Skills

Python

Deep learning

Linux

Git

Data handling

Computer vision

Education

Bachelor's degree in CS or related field

Tools

OpenCV

PyTorch

FastAPI

Docker

Job description

About the Role

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

Who We’re Looking For

• 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

We do not expect junior candidates to have experience with every technology listed in this description. Strong fundamentals, curiosity, and evidence that you can learn quickly matter more than checking every box.

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