Machine Learning QA Engineer

About the Role

What You Will Do

• Collaborate with AI development and product teams to understand product requirements and design effective test plans and test cases for AI-based products.
• Strategize evaluation methodologies, gathering data, and evaluation reporting to ensure comprehensive assessment of products.
• Perform data analytics on large datasets to monitor and track anomalies within product content and statistics.
• Train and deploy ML models to help boost product performance and efficiency.
• Create and maintain detailed documentation of test processes, methodologies, and findings for future reference and improvement.
• Keep up-to-date with advancements in the field to optimize internal processes and workflows, ensuring Derq remains at the forefront of AI and machine learning innovations.
• Interface and coordinate with the Engineering team to ensure seamless integration of QA processes with development cycles.
• Foster a collaborative, proactive team environment that values shared success, recognizing the importance of teamwork in achieving Derq's mission.

What We Are Looking For

• Bachelor's degree in an analytical domain such as Machine Learning, Computer Science, or a related discipline, reflecting a strong foundation in analytical and technical skills.
• Proficiency in Python, Javascript, and SQL, with a demonstrated ability to apply these skills in real-world problem-solving.
• Familiarity with classical Machine Learning Models such as Random Forest, SVM, Naive Bayes, indicating a solid understanding of machine learning principles.
• Core understanding of mathematical concepts for statistical inference, crucial for data analysis and interpretation.
• Hands-on experience with spreadsheet-based querying and analytics, specifically with Excel, to efficiently manage and analyze data.
• Excellent knowledge of word processing tools and spreadsheets (MS Office Word, Excel, etc.) for clear and effective communication.
• Good command of English, both oral and written, with strong reporting skills to convey complex technical information simply.
• Knowledge of basic statistical principles coupled with logical thinking, coherent reasoning, and a detail-oriented attitude, essential for meticulous testing and quality assurance.

Nice to Have

• Experience with annotation tools such as CVAT, which would be beneficial for labeling and preparing datasets for machine learning model training.
• Knowledge of additional programming languages or frameworks that could complement Derq's technology stack and contribute to innovation.
• Participation in open-source projects or personal initiatives related to AI, machine learning, or data science, demonstrating a proactive approach to staying updated with industry developments.

Benefits and Perks

• The opportunity to work on cutting-edge AI and machine learning projects that have a direct, positive impact on road safety and infrastructure.
• Collaborative and dynamic work environment that values shared success and encourages professional growth.
• Access to the latest technologies and tools in the industry, ensuring the ability to stay at the forefront of technical knowledge and skills.
• Flexible, remote work arrangement, allowing for a healthy work-life balance and the freedom to work from anywhere in the world.
• Competitive compensation package and benefits, acknowledging the value of each team member's contributions to Derq's mission.

• When applying, ensure your resume and cover letter highlight specific instances of collaborating with development teams and designing test strategies for AI-based products.
• Familiarize yourself with Derq's products and mission to demonstrate your genuine interest in the role and the company's impact on traffic safety.
• Prepare examples of how you've used data analytics tools, such as Excel, to solve problems or improve product performance in previous roles.
• Show a willingness to learn and adapt to new technologies and methodologies, as the field of AI and machine learning is constantly evolving.
• Consider reaching out to current or former Derq employees on professional networks to gain insights into the company culture and what makes a successful candidate.
• Be prepared to discuss your approach to ensuring the reliability, accuracy, and performance of machine learning models during the interview process.