Machine Learning Engineer (Computer Vision & Robotics / AI)

HIREBRIDGE
West Hartford, United States of America
15 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Intermediate
Compensation
$ 120K

Job location

West Hartford, United States of America

Tech stack

API
Artificial Intelligence
Amazon Web Services (AWS)
Artificial Neural Networks
Computer Vision
Azure
Communications Protocols
Python
Machine Learning
Message Queuing Telemetry Transport (MQTT)
TensorFlow
OPC Unified Architecture
Azure
Smart Devices
Visual Systems
3d Imaging
Digital Twin
Data Processing
Google Cloud Platform
PyTorch
Delivery Pipeline
Deep Learning
Keras
Build Management
Scikit Learn
Information Technology
Machine Learning Operations
REST
Software Version Control
Data Pipelines
Automation Anywhere
Microservices

Job description

A leading applied technology organization focused on advanced manufacturing and automation is seeking a Machine Learning Engineer (Computer Vision & Robotics) to develop and deploy AI-driven solutions in industrial environments.

This role focuses on building machine learning models, developing computer vision systems, and integrating AI into robotics, automation systems, and digital manufacturing workflows. The position collaborates with cross-functional engineering teams and external stakeholders to support smart factory and Industry 4.0 initiatives., * Develop, train, and optimize machine learning and deep learning models for applications such as computer vision, predictive maintenance, anomaly detection, and process optimization

  • Build and deploy neural networks using frameworks such as PyTorch, TensorFlow, Keras, or scikit-learn
  • Collect, clean, and process data from sensors, robotics systems, PLCs, and industrial equipment
  • Develop scalable data pipelines for model training and real-time inference
  • Integrate AI/ML models into robotics systems, automation workflows, and digital twin environments
  • Deploy models to edge devices (e.g., industrial PCs, embedded systems)
  • Develop Python-based tools, APIs, and microservices to support AI workflows
  • Implement MLOps practices including version control, testing, monitoring, and model lifecycle management
  • Support cloud-based machine learning workflows (AWS, Azure, or similar platforms)
  • Conduct experiments, analyze results, and translate findings into production-ready solutions
  • Prepare technical documentation, reports, and presentations
  • Collaborate with internal teams and external stakeholders on applied AI initiatives
  • Ensure adherence to safety and operational protocols
  • Perform additional duties as assigned

Requirements

  • Bachelor's degree in Computer Science, Data Science, Robotics, Electrical Engineering, or a related field (or equivalent experience), * 4+ years of experience developing machine learning or deep learning applications in industry or research
  • Strong proficiency in Python and ML frameworks (PyTorch, TensorFlow, scikit-learn)
  • Experience with computer vision, image processing, or sensor data analysis
  • Experience building, evaluating, and optimizing machine learning models
  • Familiarity with data pipelines, deployment workflows, or MLOps practices
  • Strong foundation in mathematics (linear algebra, probability, statistics)
  • Strong communication and technical documentation skills
  • U.S. citizenship required to meet regulatory compliance requirements, * Advanced degree in AI, Machine Learning, Robotics, or related field
  • Experience with robotics, automation, or manufacturing systems
  • Familiarity with digital twins or simulation environments
  • Experience deploying models to edge devices (e.g., NVIDIA Jetson)
  • Knowledge of industrial communication protocols (OPC UA, MQTT, REST APIs)
  • Experience with cloud ML platforms (AWS, Azure, GCP)
  • Experience with industrial vision systems, sensors, or 3D imaging
  • Experience in customer-facing or applied engineering environments

Work Environment

This is a full-time role in office and lab environments, with occasional interaction in industrial or production settings. The role involves extended computer-based work and collaboration with cross-functional teams.

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