Senior ML Engineer-HTHD

Key Skills

Docker, Keras software library, Kubernetes-K8s, Machine learning techniques, MLOps tools, Python Programming, PyTorch, TensorFlow

Job Description

The ideal candidate will have a proven track record of applying these skills in the fields of autonomous vehicles, ADAS (Advanced Driver Assistance Systems), and manufacturing. Join our team and be part of a dynamic and innovative company that is at the forefront of computer vision and deep learning technologies. If you have a passion for solving complex problems and a desire to make a meaningful impact, we would love to hear from you.

RESPONSIBILITIES

• Lead the design, development, and implementation of 2D and 3D computer vision algorithms and systems for classification, detection, segmentation, key point estimation, image and video generation with generative AI, image and video captioning, contrastive learning, embedding-based search, large language models, stable diffusion, visual question answering, and synthetic data generation.
• Utilize knowledge in MLOps, Kubernetes, Docker, and RESTful APIs, and experience with cloud platforms like GCP and AWS to deploy and maintain computer vision systems.
• Apply hands-on experience in the fields of autonomous vehicles, ADAS, and manufacturing to develop innovative solutions that address complex challenges in these domains.
• Research and stay up-to-date with the latest advancements in computer vision technologies and techniques.
• Collaborate with cross-functional teams to understand requirements and develop innovative solutions that meet the needs of the business.
• Mentor and provide technical guidance to team members.
• Collaborate with cross-functional teams in an agile environment to understand requirements and develop solutions that meet the needs of the business.

QUALIFICATIONS

• A Master's or Ph.D. in Computer Science, Computer Vision, Robotics, or a related field.
• 5+ years of professional experience in computer vision research and development with a focus on the mentioned areas.
• Strong programming skills in Python.
• Proficiency in deep learning frameworks such as TensorFlow, PyTorch, or Keras.
• Hands-on experience with MLOps, Kubernetes, Docker, and RESTful APIs, and knowledge of cloud platforms like GCP or AWS.
• Strong understanding of computer vision, image processing, and machine learning techniques.
• Excellent problem-solving and analytical skills.
• Experience collaborating with backend and frontend software engineers in an agile environment.