DESCRIPTION

Job summary
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

Primary 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

BASIC QUALIFICATIONS

Bachelors/Masters degree in Computer Science or related field
10+ years professional experience in software development management
Proficiency in, at least, one modern programming language such as Java, Scala, C#, C++ etc
Ability to solve complex technical problems and design robust, scalable solutions
Ability to think critically and actively contribute to strategic choices.
5+ years experience in managing development teams working on multiple simultaneous projects.
5+ years experience in managing large scale software development teams following Agile development processes.
Strong skills in project planning & execution, problem solving. Ability to take a project from initial scoping requirements through actual launch and support of the project
Proven leadership and teamwork skills
Excellent verbal and written communication skills in both technical and non-technical discussions.

PREFERRED QUALIFICATIONS

Deep, hands-on technical expertise in high scale, service-oriented architectures
Exposure to Elastic Map Reduce and Machine Learning programs.
Ability to handle multiple competing priorities in a fast-paced environment
Knowledge of professional software engineering practices & best practices for the full software development life cycle including coding standards, code reviews, source control management, build processes, testing, and operations
Clear, professional communication skills able to contribute to team discussions, knowing when to contribute, when to listen, and when to ask questions
Proactively and continually improve their level of knowledge about Amazon’s business and relevant technologies, and use this knowledge to deliver high quality, accurate software deliverables
Strong business and technical vision
Good understanding of web services