The Core Machine Learning Team works on the cutting edge of technology employing Machine Learning to build highly scalable, accurate models which are consumed by many of our product teams. We seek a creative quality engineer to lead the quality initiatives of this team. The ideal candidate would evaluate and drive the testing approach for machine learning projects, develop automation at scale and collaborate with peer quality engineers, software developers, and research scientists.
How You’ll Find Success
Proficiency with a broad range of data structures, algorithms, and design patterns, and knowing when it’s appropriate to use them (and when it’s not).
Experience applying different software testing techniques, such as equivalence class partitioning, boundary value testing, pairwise testing, etc.
Experience with SOA (Service Oriented Architecture) and distributed systems.
Familiar with front-end technologies (including Selenium-based automation), REST web services and/or constructing database queries
Experience applying different software testing techniques, such as equivalence class partitioning, boundary value testing, pairwise testing, etc.
Ability to work both independently on ambiguous problems and in highly collaborative team environments
CI/CD deployment automation experience with scripting, Chef, Jenkins, Puppet, etc.
Strong critical thinking and root cause analysis
How You’ll Grow
Deep Technological Expertise: As you work alongside our team of experts, including machine learning engineers and data scientists, you’ll have the opportunity to deepen your expertise in advanced software testing within the realm of machine learning and artificial intelligence. You’ll gain hands-on experience with the latest ML tech stacks and methodologies that can elevate your skill set to the next level.
Leadership and Mentorship Skills: This role is designed not just for you to excel technically but also to grow as a leader. As you mentor peers and drive quality initiatives, you’ll develop valuable leadership and mentorship skills. These experiences will enable you to take on increasingly senior roles in the future, potentially leading teams or departments.
Cross-Disciplinary Collaboration: Through cross-functional collaboration with product managers, tech-ops, and other stakeholders, you’ll learn how to effectively communicate and drive product decisions from a quality perspective. This will help you to become an influencer in product development cycles and broaden your understanding of different areas of the business.
Automation and Process Innovation: With an emphasis on creating and improving test automation frameworks, you’ll be at the forefront of process innovation. You’ll learn to evaluate and implement cutting-edge tools and practices that can scale and improve efficiency, which is key for professional growth in any technology landscape.
Quality Strategy Development: In driving quality processes and defining acceptance criteria, you’ll learn to think strategically about product quality and customer satisfaction. This holistic view of the software development lifecycle will prepare you for roles that require both tactical execution and strategic planning, ensuring you’re well-placed for career advancement.
Things You’ll Do
Work in a multi-disciplinary team to implement, tune, and productize cutting-edge machine learning models to meet the demands of our rapidly growing business
Work closely with, and incorporate feedback from scientists, machine learning engineers, tech-ops, and product managers.
Develop and design test frameworks, test tools, and automation for complex, distributed SaaS systems and Machine Learning models.
Research, share, recommend, and drive adoption of new technologies, standard methodologies, and trends across the Machine Learning spectrum.
Help your team evolve by actively participating in the code review process, design discussions, planning, and post-mortems.
Define, implement, and analyze metrics to resolve test effectiveness and the overall quality of software.
Investigate test failures and customer reports using your technical understanding of the product and tools (such as logs) to narrow down repro issues steps and isolate the root problem
You ensure the product is tested at the appropriate level (unit vs integration vs end to end, API vs UI), reducing unnecessary test cases, intermittent failures, and decreasing execution time.
Drive quality processes like bug triage, release decisions, and feature completion criteria
Mentor and develop your other team members.
Iteratively test the AI models and verify that the incremental predictions are improving and meeting the benchmarks as set by the Development team.
Communicate with cross functional teams as to how the Machine Learning platform is consumed by other downstream teams. Based on this understanding, collaborate with them and make suggestions to their test plans and test strategies
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