Lead ML Engineer – Computer Vision

Benchmark Technology

Lead ML Engineer at Benchmark Construction expanding AI-enabled plan ingestion pipeline. Architecting, building, and deploying ML systems for document analysis, mentoring junior engineers, ensuring system reliability.

Posted 7/27/2026full-timeRemote • 🇮🇳 IndiaSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in Machine Learning Engineering with a focus on Computer Vision and Natural Language Processing, capable of architecting and deploying scalable ML systems. Proficient in Python, PyTorch, and building reliable MLops infrastructure for production environments.

Highest-signal resume keywords

Machine Learning EngineeringComputer VisionPython ProgrammingMLops InfrastructureObject Detection

ATS Keywords

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Hard Skills

Machine LearningComputer VisionPythonPyTorchFastAPISegmentation ModelsDetection FrameworksOCRImage ProcessingLinux

Soft Skills

Problem-SolvingMentoringDecision-Making

Tools & Technologies

OpenCVDockerClearMLMLflow

Industry Keywords

Document UnderstandingInformation ExtractionMulti-Modal ApproachesBuilding PlansAutomation

Tech Stack

Tools & technologies

DockerLinuxPythonPyTorch

About the role

Key responsibilities & impact

Own and expand our AI-enabled plan ingestion pipeline—from raw PDFs to clean, dependable outputs that power takeoff, design, and downstream automation
Architect, build, and deploy ML systems for object detection, segmentation, document understanding, and information extraction from complex building plans
Drive R&D across computer vision and/or NLP as applied to construction documents and related data
Develop multi-modal approaches that combine vision with language features for document analysis (LLMs/NLP)
Mentor junior engineers and help raise the bar on execution, code quality, and decision-making
Ensure systems are reliable, maintainable, testable, and observable in production

Requirements

What you’ll need

8+ years of experience in Machine Learning Engineering, with deep focus in computer vision
Expert Python skills, with strong experience in PyTorch and FastAPI
Proven work with segmentation models, detection frameworks, and OCR/document pipelines
Strong image processing fundamentals (OpenCV, geometric transforms, preprocessing, etc.)
Comfortable in Linux; hands-on with Docker/containerization for deployment
Experience building and maintaining MLops infrastructure (e.g., ClearML, MLflow)
Ability to design scalable, high-performance ML systems (not just prototypes)
Strong problem-solving ability and comfort operating independently in a fast-paced environment

Benefits

Comp & perks

Competitive salary + meaningful equity
Comprehensive benefits (health, dental, vision)
Professional development budget (courses, conferences, research exploration)
Real-world ML problems with direct impact
High growth potential