About the Company
HTC Global Services is a technology-driven firm focused on delivering innovative solutions through a combination of technical expertise and client collaboration. The company fosters a culture of continuous learning, offering long-term opportunities to engage with advanced technologies while contributing to impactful projects. Team members benefit from a competitive benefits package that includes paid time off, holidays, 401K matching, insurance options, and additional perks designed to support both personal and professional well-being.
About the Role
A position is open for a skilled Computer Vision / Machine Learning Engineer to drive the development, training, and deployment of advanced visual recognition models. This role requires a hands-on approach to deep learning, balanced with engineering expertise for deploying scalable, production-ready systems. The ideal candidate will thrive in a collaborative environment and contribute to robust machine learning pipelines supporting real-world applications.
Responsibilities
- Design, build, and deploy computer vision models using frameworks such as YOLO and OWL
- Develop scalable machine learning pipelines for training, evaluation, and deployment using Kubernetes and Docker
- Optimize deep learning models for performance and accuracy through parameter tuning
- Integrate models within production systems, ensuring automation, monitoring, and MLOps compliance
- Collaborate with engineers and data scientists to support end-to-end model lifecycle management
- Research emerging trends in computer vision and implement relevant advancements
Required Skills
- Strong programming skills in Python with a focus on deep learning using PyTorch
- Solid foundation in object detection and image classification techniques
- Hands-on experience with YOLO, OWL, or similar open-world detection frameworks
- Familiarity with cloud deployment platforms such as AWS SageMaker
- Proficiency in Kubernetes and Docker for containerized environments
- Experience working in Ubuntu/Linux environments for model development and deployment
- Demonstrated ability in hyperparameter tuning for large-scale models
- Working knowledge of MLOps tools like MLflow
Preferred Qualifications
- Master’s degree or PhD in Computer Science, Artificial Intelligence, or a related field
- Experience deploying models in enterprise environments
- Knowledge of CI/CD pipelines in machine learning contexts
- Familiarity with version control tools and collaborative development platforms