AI Engineer - Computer Vision

Aquaticode builds artificial intelligence solutions for aquaculture. Our core competency lies at the intersection of biology and artificial intelligence, utilizing specialized imaging technology to detect, identify, and predict traits of aquatic species. We value commitment and creativity in building real-world solutions that benefit humanity.

We are seeking an experienced, talented and ambitious AI Engineer with expertise in computer vision and strong development skills to join our team. You will play a key role in designing and implementing cutting-edge machine learning algorithms to solve challenging problems in aquaculture.

Requirements

• Proven track record in developing image/video processing and computer vision solutions.
• 8+ years of experience as a machine learning engineer/researcher or in a similar role.
• Proficiency with common Python machine learning frameworks (scikit-learn, SciPy, Matplotlib, PyTorch, etc.).
• Strong understanding of data structures, data modeling, and software architecture.
• Ability to write clean, robust, and efficient code.
• Excellent communication and presentation skills in English.
• MSc or PhD in Computer Science, Engineering, Mathematics, or a related field.
• Candidates with a BSc degree and equivalent industrial experience are also encouraged to apply.

Responsibilities:

• Design, adapt, and implement machine learning and classical algorithms from proof of concept (POC) to working prototypes.
• Plan and conduct experiments to address critical business questions.
• Develop and maintain model testing and statistical verification processes.
• Implement data processing and training pipelines.
• Extend existing machine learning and deep learning codebases and frameworks.
• Thoroughly document POCs and experiments.
• Plan and lead long-term research activities.
• Assist in recruiting talent in the field.
• Stay up-to-date with the latest developments in AI and machine learning.

Preferred Qualifications:

• A track record of publications in top-tier AI conferences or journals.
• Experience deploying machine learning/AI systems in production environments and tools.
• Familiarity with inference optimizations techniques using CUDA, ONNX, TensorRT etc.
• Familiarity with containerization technologies (e.g. Docker, Docker compose, K8s).
• Knowledge of databases (SQL, MongoDB) and basic networking or message-passing protocols.
• Experience with cloud platforms (Google Cloud Platform, AWS, Azure).
• Proficiency with MLOps frameworks (DVC, MLflow, Metaflow, Databricks).
• Familiarity with CI/CD tools (Jenkins, GitLab CI/CD, Screwdriver, Spinnaker, or similar).
• Ability to visit Aquaculture sites when needed.