AI Engineer
Role details
Job location
Tech stack
Job description
We are seeking a 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., * 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.
Requirements
Do you have experience in SQL?, Do you have a Master's degree?, * Proven track record in developing image/video processing and computer vision solutions.
- 3+ 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 B.Sc. degree and equivalent industrial experience are also encouraged to apply., * A track record of publications in top-tier AI conferences or journals.
- Experience deploying machine learning/AI systems in production environments.
- Familiarity with containerization technologies (e.g., Docker).
- 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).