Senior Machine Learning Engineer , AGI Structured Information Retrieval

- 5+ years of non-internship professional software development experience
- 5+ years of programming with at least one software programming language experience
- 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- Experience as a mentor, tech lead or leading an engineering team
- 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Bachelor's degree in computer science or equivalent

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The AGI Structured Information Retrieval team develops the services required to query the Amazon Knowledge Graph (AKG), an LLM-optimized, foundational component in the AGI tech stack, using Natural Language.

As our Sr. MLE, you'll have the power to lead the charge in developing algorithms and modeling techniques to push the boundaries of model training and deployment at scale.

Key job responsibilities
* Ability to quickly learn cutting-edge technologies and algorithms in the field of ML to participate in our journey to build the best NL to Structured retrieval service.

* Responsible for the development and maintenance of key platforms needed for developing, evaluating and deploying ML models for real-world applications.

* Work with other team members to investigate design approaches, prototype new technology and evaluate technical feasibility.

* Work closely with Applied scientists to develop and scale machine learning models.

A day in the life
As a Senior MLE, you will be working with a strong team of engineers and collaborating with applied scientists to develop novel processes for constructing and enhancing structured information retrieval systems; and enable high precision/recall & low latency access to knowledge in AKG.

For this role we expect:
- 5+ years of professional software development experience in distributed systems with emphasis on ML infrastructure
- 5+ years of current programming experience building ML infrastructure using languages such as Python, C++ or Rust
- Hands-on experience with parallel computing platforms such as CUDA, OpenMP, etc
- Deep understanding of AI frameworks such as PyTorch, TensorFlow, and JAX, and their demands on underlying compute infrastructure, memory bandwidth, network interconnect, and storage as scale goes up
- Knowledge of emerging AI hardware accelerators and architectures
- Experience with containerization and orchestration technologies (Docker, Kubernetes)