Data and Machine Learning Engineer

Job Responsibilities

• Take Complete Ownership of Data Projects: You'll have the opportunity to oversee projects from start to finish. From conceptualization to deployment, your input will be vital in shaping the development of high-quality, scalable data systems that align with business needs.
• Develop and Manage Efficient Data Labelling Processes: Your primary responsibility will be to create and maintain robust data labelling systems. This is crucial for training accurate and reliable AI models. You'll be expected to understand the nuances of the data and computer vision model pipelines, ensuring labels are accurate and consistent.
• Ensure High-Quality Data Management: You will be responsible for managing the data lifecycle, ensuring data is collected, stored, and maintained effectively. This includes implementing strategies for data quality assurance and integrity.
• Optimize Data for Model Training: Utilize your skills to prepare and optimize data for training AI models. Your role will be pivotal in ensuring the data fed into our models is of the highest quality, directly impacting the performance and reliability of our AI solutions.
• Collaborate Across Teams for Data Integration: Work closely with engineering, operations, and business teams to integrate our data solutions with external systems and third-party vendors. Your role in these dynamic partnerships will be to ensure seamless integration and management, supporting a diverse industry landscape.
• Contribute to Continuous Improvement: Regularly review and refine our existing data systems. Your role will involve troubleshooting, fixing bugs, and enhancing the stability and quality of our data processes. You'll also play a key role in functional testing to ensure ongoing efficiency and effectiveness of our AI systems.

Job Requirements

• Python Skills: Proficiency in Python programming is essential, as it is a key tool in data management and processing.
• Knowledge of Machine Learning and Deep Learning: A good understanding of how machine learning and deep learning algorithm’s function is crucial. Candidates should have practical experience in applying these techniques.
• Experience in Data-Related Technologies: Candidates should have hands-on experience with data management and labelling and be familiar with the tools and practices involved in these processes.
• Desirable Soft Skills: In addition to technical expertise, candidates should demonstrate a can-do attitude, strong collaboration skills, and the ability to work effectively in a team. Leadership qualities and a keenness to continually learn and adapt are also highly valued.