Machine Learning - Computer Vision Engineer

We are seeking a highly skilled and motivated Machine Learning Engineer specializing in Computer Vision to join our team. The ideal candidate will have a strong background in developing and deploying machine learning models focused on image and video processing. You will work closely with cross-functional teams to design, implement, and optimize vision-based AI solutions to address real-world challenges.

Key Responsibilities:

• Design, develop, and deploy computer vision models for tasks such as object detection, object tracking, video segmentation, and facial recognition.
• Optimize and fine-tune deep learning algorithms for real-time performance.
• Work closely with the software engineers and product teams to identify opportunities for leveraging data.
• Collect, clean, and preprocess large datasets to prepare for model training and evaluation.
• Evaluate and optimize machine learning models for accuracy, performance, and scalability.
• Deploy models into production environments and monitor their performance to ensure reliability.
• Stay up-to-date with the latest advancements in computer vision and artificial intelligence.
• Collaborate with cross-functional teams to integrate machine learning solutions into business processes.
• Document processes, models, and implementations to ensure reproducibility and scalability.

Required Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
• Minimum of 4 years of professional experience in machine learning engineering or a closely related role.
• Proven experience with deep learning models, including training, evaluation, and hyperparameter tuning using libraries such as TensorFlow, PyTorch, and Transformers or other Huggingface tools.
• Hands-on experience with data manipulation tools such as Pandas, NumPy, and SQL.
• Strong programming skills in Python and C++.
• Solid understanding and practical experience with MLOps principles, including model deployment, monitoring, and instrumentation on cloud platforms such as AWS, Azure, or Google Cloud.
• Familiarity with efficient model serving tools such as ONNX, Triton Inference Server, and vLLM.
• Proficiency in working with image and video data, including preprocessing and augmentation techniques.
• In-depth understanding of machine learning algorithms, both supervised and unsupervised, as well as various deep learning techniques.
• Strong communication skills and a demonstrated ability to work collaboratively within cross-functional teams.

Great to have:

• Familiarity with containerization and orchestration tools like Docker and Kubernetes.
• Experience with version control systems such as Git.
• Understanding software engineering best practices, including code review, testing, and documentation.
• Experience with Large Language Models (LLMs) is a great plus.
• Experience with data annotation tools and processes.

Benefits:

• Competitive salary.
• Comprehensive health and wellness benefits.
• Professional development opportunities and continuous learning programs.
• Collaborative and inclusive work environment.