[Hiring] Associate ML Engineer @Derq

Role Description

We are seeking a motivated Associate Machine Learning Engineer to join our team and contribute to building intelligent, data-driven solutions for real-world traffic and mobility challenges. You will work closely with a multidisciplinary team to design, develop, and deploy machine learning and computer vision systems using diverse sensor data from vehicles and road infrastructure.

Key Responsibilities

• Develop cutting-edge machine learning and deep learning solutions using multimodal sensor data from vehicles and road environments.
• Design and build scalable software pipelines for computer vision applications, including:
  • Data curation and preprocessing
  • Model training and evaluation
  • Testing and validation
  • Deployment and monitoring
• Create innovative solutions for complex traffic and mobility-related problems.
• Design and implement efficient, low-cost approaches for video-based inference.
• Train, fine-tune, and optimize machine learning and deep learning models for real-world performance and scalability.
• Collaborate with cross-functional teams to contribute to the development of advanced, production-ready systems.
• Stay up to date with emerging technologies, research, and open-source tools, and apply them to improve system performance and capabilities.

Qualifications

• Bachelor’s or Master’s degree in Computer Science or a related field.
• 2+ years of relevant experience in Machine Learning or Computer Vision.
• Strong understanding of machine learning and deep learning fundamentals.
• Experience with training and optimizing deep learning models, designing loss functions and hyperparameter tuning on real data.
• Solid foundation in mathematics including probability and statistics and linear algebra.
• Strong knowledge of data structures and algorithms.
• Proficiency in Python and C/C++.
• Experience writing modular, efficient, and testable code for production systems.
• Identify, leverage and develop expertise in emerging technologies, open source tools, and harness new techniques.