Machine Learning Data & Tools Lead engineer
Full Time
Onsite in San Jose, CA
R&D startup with a revolutionary cutting-edge product (HW & SW) with about 100 employees, is seeking a Data Quality & Tools Manager to lead company efforts in ensuring the integrity, accuracy & usability of our ML data. This role involves developing and implementing data quality strategies, overseeing data governance initiatives & managing the tools and technologies used for data quality management. The ideal candidate will have a strong understanding of machine learning, data analysis, quality assurance & leadership skills to drive the team towards excellence.
Responsibilities:
Develop, implement, and monitor data quality standards, policies, and procedures to ensure high-quality data
Evaluate, select, and manage data quality tools and technologies. Lead the integration of these tools into existing workflows
Manage a team of data analysts and quality assurance professionals, providing guidance, training, and support to enhance their skills and performance.
Conduct data quality assessments and analyses to identify trends, root causes of issues, and opportunities for improvement
Work closely with cross-functional teams to understand data needs and promote data quality initiatives across the organization
Develop and present regular reports on data quality metrics, project progress, and improvement plans to senior management
Drive a culture of continuous improvement by identifying opportunities to enhance data quality processes and tools
Qualifications:
BS degree in computer science, information technology, Statistics or related field. MS degree preferred
5+ years of experience in data management, data quality, or data governance roles.
Deep hands-on / technical experience of LLM's, machine learning concepts, algorithms, and model evaluation techniques
Strong communication and collaboration skills with the ability to work effectively in cross functional team environment
Strong analytical and problem-solving skills, with the ability to analyze complex ML models and identify potential issues
Proficient at balancing multiple efforts simultaneously and meeting strict deadlines
Persistent and inquisitive problem solver, committed to driving quality forward
Significant management experience as a Software Quality Assurance Manager in an ML-focused environment
Established pattern of building strong teams – attracting, hiring, motivating, and retaining the best engineers
Proven experience in designing and maintaining data collection tools and infrastructure.
Proficiency in programming languages such as Python, Java or JavaScript
Strong knowledge of database management systems and data modeling concept
