Senior ML Computer Vision Engineer
Actively Hiring
Full-time Posted about 1 month ago
Responsibilities
- check_circle Partner with the Computer Vision SME to drive R&D initiatives, exploring new applications for AI, CV, and traditional machine learning within heavy industry.
- check_circle Design, develop, and deploy Computer Vision models (e.g., object detection, image classification, segmentation) and traditional ML algorithms for predictive maintenance and asset monitoring.
- check_circle Translate business requirements and R&D concepts into scalable, production-ready machine learning pipelines.
- check_circle Collaborate with Data Engineers and Analytics Engineers to ensure seamless ingestion, transformation, and availability of visual, sensor, and operational data.
- check_circle Work alongside Integration Engineers to embed AI/ML capabilities and model outputs into existing enterprise applications and asset management systems.
- check_circle Implement MLOps best practices for model training, versioning, deployment, monitoring, and lifecycle management within an Azure-centric environment.
- check_circle Evaluate and select appropriate algorithms, frameworks, and cloud-native AI tools to meet evolving business and performance needs.
- check_circle Prepare comprehensive technical documentation, model architectures, and performance reports for technical and non-technical stakeholders.
Basic qualifications
- 5+ years of hands-on experience as a Machine Learning Engineer, Computer Vision Engineer, or AI Researcher in a software development environment.
- Strong proficiency in Python and deep learning frameworks such as PyTorch, TensorFlow, or Keras.
- Proven experience building and deploying Computer Vision solutions (e.g., using OpenCV, YOLO, ResNet) in real-world scenarios.
- Solid foundation in traditional machine learning techniques (e.g., scikit-learn, XGBoost) and statistical data analysis, particularly for predictive maintenance or time-series forecasting.
- Experience with cloud-based ML platforms and MLOps practices, preferably utilizing Azure Machine Learning, Databricks, or similar enterprise environments.
- Familiarity with data manipulation and analysis libraries (Pandas, NumPy) and working with large, diverse datasets (images, video streams, sensor data).
- Strong analytical and problem-solving skills, with a track record of transitioning models from R&D phases into production scale.
- Excellent communication skills, with the ability to collaborate effectively with SMEs, data engineering teams, and business leadership.
- Master's degree or PhD in Computer Science, Artificial Intelligence, Data Science, or a related highly quantitative field (or equivalent applied experience).
Preferred qualifications
- Background in mining, heavy industry, or manufacturing environments, particularly working with OT (Operational Technology) or IoT sensor data.
- Experience processing and analyzing geospatial data, drone imagery, or edge-computing AI deployments.
- Familiarity with Azure Data Factory, Azure Synapse, or Azure Integration Services to better align with the broader data platform team.
- Flexible working format - remote, office-based or flexible
- A competitive salary and good compensation package
- Personalized career growth
- Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more)
- Active tech communities with regular knowledge sharing
- Education reimbursement
- Memorable anniversary presents
- Corporate events and team buildings
- Other location-specific benefits
- not applicable for freelancers
Tags & Focus Areas
Remote Ai Machine Learning Computer Vision
About N-iX
Analyzing requirements, technical design, and implementing into new capabilities within the platform Upholding code standards and best practices through code reviews, refactoring efforts, and peer mentoring Engaging in the identification and remediation of issues related to code / solutions quality, functionality or other problems in the technical and business domains Providing technical support for existing functionalities in production environment Documenting new or updated functionality as...