Amazon Sr Software Engineer ML Infra Amazon Search 

United States, California, Palo Alto 

929087065

Key job responsibilities
As a senior engineer in this team, you will:1. Evolve a sophisticated deep-learning ranking system and feature store deployed across thousands of machines in AWS, serving billions of queries at tens of millisecond latencies.
2. Immerse yourself in imagining and providing cutting-edge solutions to large-scale information retrieval and machine learning (ML/DL) problems.
3. Have a relentless focus on scalability, latency, performance robustness, and cost trade-offs -- especially those present in highly virtualized, elastic, cloud-based environments.
4. Conduct and automate performance testing of the model serving system to evaluate different hardware options (including GPUs and specialized accelerators such as AWS Inferentia2), model architectures and serving configurations.
5. Lead implementation and enhancement of a rapid experimentation framework to test ranking hypotheses.
6. Create mechanisms to ensure models work as expected in production.
7. Work closely with applied scientists to determine the requirements for deploying ranking models in production environments.

- 5+ years of non-internship professional software development experience
- 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- 5+ years of programming with at least one software programming language experience
- Experience as a mentor, tech lead or leading an engineering team
- 5+ years of object-oriented programming experience in C++, Java or Scala, as well as in Python, Perl, or related scripting languages.
- Experienced in large scale AI and ML infrastructure, and experience in machine learning technologies including or similar to PyTorch, TensorRT, AWS Inferentia, Triton Inference Server, etc.
- Experience writing production code for services that utilize Machine Learning or Information Retrieval algorithms.
- Ability to troubleshoot models, and work with scientists and ML engineers to develop ways to improve performance and monitoring of the system and models.

- 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Experience implementing large-scale low-latency distributed systems and working with scalable algorithms utilizing large amounts of data.
- Polished written and verbal communication skills, with the ability to communicate with confidence, clarity, and focus.
- Masters Degree or PhD in Computer Science, or related discipline.Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.