Amazon Applied Science Manager Translation Services 

United States, Washington, Seattle 

14945075

Key job responsibilities
In this role, you will work closely with business partners, applied scientists, software development engineers, and product managers to accelerate building solutions to expand translation capabilities. You will have significant influence on our overall strategy by helping define science and engineering strategy, define product features, drive system architecture, and spearhead the best-practices that enable a quality product. You will also influence the development processes, and develop well-rounded skills such as leadership, and effective project management. Building a strong development team and developing career plans for the scientists and engineers reporting to you will be a key responsibility. Throughout, you should possess creativity, curiosity, and excellent judgment to thrive in an environment of ambiguity.A day in the life
You will spend your days collaborating with scientists, developers, customers, stakeholders, and converting the business needs into a data-driven solution. You will support a team to design and execute science products. You will dive deep into the data and balance technical execution with longer term strategy. You will grow and develop your team.

- 3+ years of scientists or machine learning engineers management experience
- PhD, or Master's degree
- Knowledge of ML, NLP, Information Retrieval and Analytics
- Experience hiring and growing top talent
- Experience programming in Java, C++, Python or related language

- 5+ years of building machine learning models or developing algorithms for business application experience
- Experience building complex software systems, especially involving deep learning, machine learning and computer vision, that have been successfully delivered to customers
- Experience communicating with users, other technical teams, and management to collect requirements, describe software product features, and technical designs
- 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