[Remote] Automation Engineer - Computer Vision / Deep Learning Data Scientist

Note: The job is a remote job and is open to candidates in USA. Milestone Technologies, Inc. is seeking a Senior Data Scientist / ML Engineer specializing in Computer Vision. The role will develop, optimize, and deploy deep learning and machine vision solutions for automated visual inspection in manufacturing, while supporting data and model lifecycle management, cloud infrastructure, documentation, and collaboration with IT, OT, engineering, and manufacturing teams.

Responsibilities

• Design, develop, train, validate, and optimize deep learning models for industrial image inspection and anomaly detection
• Support the full machine learning lifecycle from dataset review through production-ready model evaluation
• Analyze image datasets and identify opportunities to improve data quality, coverage, and labeling consistency
• Implement image preprocessing, augmentation, ROI selection, masking, and feature engineering techniques
• Develop anomaly detection workflows using supervised and unsupervised learning approaches
• Evaluate model performance and optimize confidence thresholds to minimize false positives and false negatives in production environments
• Troubleshoot model performance issues and recommend corrective actions
• Work collaboratively with manufacturing, engineering, automation, and operational technology teams
• Develop an understanding of manufacturing workflows and production line operations
• Demonstrate familiarity with Operational Technology (OT) environments and the unique requirements associated with industrial systems
• Collaborate effectively with stakeholders across both IT and OT functions to ensure successful deployment and adoption of machine vision solutions
• Support image dataset development, curation, governance, and traceability
• Establish robust train, validation, and test methodologies
• Identify and mitigate data leakage and dataset bias risks
• Maintain reproducible training procedures and version-controlled model development practices
• Assist in ongoing performance monitoring and model improvement efforts
• Leverage AWS services including SageMaker, S3, CloudWatch, and EC2 to support model development and operational monitoring
• Work alongside engineering teams to support deployment and maintenance of machine learning workloads
• Create and maintain detailed technical documentation covering datasets, model configurations, training runs, validation results, and deployment procedures
• Document model decision-making processes and provide traceability for future audits and troubleshooting
• Support ongoing knowledge transfer and cross-functional training activities

Skills

• • 12+ years of professional experience in Data Science, Machine Learning, Artificial Intelligence, or related fields
• • 3+ years of hands-on experience developing Computer Vision and Deep Learning solutions
• • Proven experience delivering image-based machine learning solutions through the complete lifecycle: + Dataset assessment + Data preparation + Model training + Hyperparameter tuning + Model evaluation + Performance optimization
• • Experience troubleshooting machine learning models and interpreting training, validation, and inference results
• • Experience working directly with business and technical stakeholders to solve operational challenges
• • Strong Python development skills
• • Strong experience with PyTorch or equivalent deep learning frameworks
• • Experience utilizing modern AI-assisted development tools, including GitHub Copilot, Codex-based development workflows, or similar code-generation and productivity platforms
• • Ability to rapidly prototype, test, and iterate on machine learning solutions using AI-enhanced development practices
• • Image classification
• • Object detection
• • Segmentation
• • Feature extraction
• • Visual anomaly detection
• • Image preprocessing and augmentation
• • ROI selection and masking
• • Hyperparameter tuning
• • Threshold optimization
• • Sensitivity analysis
• • Model explainability and troubleshooting
• • Model evaluation using: + Precision + Recall + F1 Score + Confusion matrices + False Positive Analysis + False Negative Analysis
• • Amazon SageMaker
• • Amazon S3
• • Amazon CloudWatch
• • Strong accountability and ownership of deliverables
• • Excellent communication skills with both technical and non-technical audiences
• • Patience and adaptability while working through evolving datasets, new technologies, and operational constraints
• • High availability and responsiveness when supporting business-critical initiatives
• • Strong collaboration and relationship-building skills
• • Curiosity and willingness to learn a custom-developed platform and manufacturing processes
• • Ability to work independently while maintaining alignment with project stakeholders
• • Periodic travel to manufacturing facilities and project locations should be expected for onboarding, shadowing, knowledge transfer, testing, and deployment support
• • Experience with industrial machine vision or automated visual inspection systems
• • Experience developing anomaly detection solutions
• • Familiarity with manufacturing, pharmaceutical, life sciences, or regulated production environments
• • Familiarity with Operational Technology (OT) environments and industrial systems
• • Understanding of GxP-controlled environments and validation processes
• • EC2 familiarity preferred

Benefits

• Structured onboarding, shadowing, and knowledge transfer will be provided to support ramp-up.
• Remote work arrangement is acceptable.

Company Overview

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