Sdm, Traffic Quality Ml, Amazon Ads

7+ years of engineering experience
- 3+ years of engineering team management experience
- 8+ years of leading the definition and development of multi tier web services experience
- Knowledge of engineering practices and patterns for the full software/hardware/networks development life cycle, including coding standards, code reviews, source control management, build processes, testing, certification, and livesite operations
- Experience partnering with product or program management teams
- Experience designing or architecting (design patterns, reliability and scaling) of new and existing systems

Advertising at Amazon is a fast-growing multi-billion dollar business that spans across desktop, mobile and connected devices; encompasses ads on Amazon and a vast network of hundreds of thousands of third party publishers; and extends across US, EU and an increasing number of international geographies. The Ad Optimization group in Bangalore has the charter to build data-science focused products and platforms for Amazon Advertising. One of our key focus areas is Traffic Quality where we endeavor to identify non-human and invalid traffic within programmatic ad sources, and weed them out to ensure a high-quality advertising marketplace. We do this by building machine learning and optimization algorithms that operate at scale, and leverage nuanced features about user, context, and creative engagement to determine the validity of traffic. The challenge is to stay one step ahead by investing in deep analytics and developing new algorithms that address emergent attack vectors in a structured and scalable fashion. We are committed to building a long-term traffic quality solution that encompasses all Amazon advertising channels and provides state-of-the-art traffic filtering that preserves advertiser trust and saves them hundreds of millions of dollars of wasted spend.
Traffic quality systems process billions of ad-impressions and clicks per day by leveraging cutting-edge open source technologies like Hadoop, Spark, Redis and Amazon's cloud services like EC2, S3, EMR, DynamoDB and RedShift. We are looking for a dynamic and innovative engineering manager to lead the design, development and deployment of real-time and offline algorithms. You will own the machine learned model training pipelines, feature generation infrastructures, model inference libraries and systems to monitor the quality of detection across various dimensions. You will also own big data infrastructures that analyze terabyte scale data to identify sophisticated robotic activity after-the-fact.. As a leader on the team, you will have sound technical acumen, excellent project management skills, great communication skills, and hire, build, and develop your team. You will be responsible for fostering a culture of experimentation towards delivering cutting-edge machine learning techniques that materially improve customer experience
Key job responsibilities
- Provide technical expertise and leadership throughout product life cycles, influence software engineers best practices for your team and own operational metrics
- Work with business leaders and product managers to define product requirements.
- Prioritize, communicate, maintain, and execute roadmaps, project plans, and commitments
- Work with engineers to define technical requirements and architect and execute best-in-class implementations in agile manner
- Build and maintain world-class customer experience and operational excellence for your deliverables
- Hire, manage, mentor and grow a high performance team of Software Engineers
- Experience in communicating with users, other technical teams, and senior leadership to collect requirements, describe software product features, technical designs, and product strategy
- Experience in recruiting, hiring, mentoring/coaching and managing teams of Software Engineers to improve their skills, and make them more effective, product software engineers