AI Systems Engineer
1 day ago
The TRG team is seeking a highly skilled AI Systems Engineer to join our ranks. As an AI Systems Engineer, you will be responsible for designing, building, and deploying scalable and secure AI/ML systems.
Our ideal candidate will have a strong background in software engineering, machine learning, and DevOps best practices. They will be able to combine these skills to build CI/CD pipelines, deploy applications, and promote security by design.
We are looking for a team player who can collaborate with vendors, business stakeholders, and other team members to deliver high-quality solutions. The ideal candidate will have excellent communication skills and be able to capture ideas in diagrams and documentation.
We value maintainability and testability in our code, and we expect our engineers to write code with these principles in mind. We use integration tests, CI/CD, observability, and twelve-factor design to ensure our systems are reliable and efficient.
The ideal candidate:
- Enjoys learning across the tech stack, from new developments in DevSecOps and automation to machine learning and artificial intelligence
- Takes pride in their work and derives great satisfaction from building reliable and maintainable infrastructure to support our team
- Is not afraid to voice opinions, propose solutions, and receive constructive criticism in a collaborative design process
- Is a social coder who likes sharing and receiving code reviews and values pair programming where appropriate
- Thrives in a remote-first work environment and uses remote collaboration tools effectively
Requirements:
- Must be fluent in Python
Fluent candidates can comfortably:
- Read and write Python code; write method and class docstrings; manage package dependencies in a principled way
- Be comfortable with git; we use GitHub extensively to develop and deploy our code
- Have strong command line skills in Unix environments; our code is built in and deployed to Unix-like environments
- Have an excellent understanding of networking and security; our work often extends across multiple networks and environments and deals with sensitive data
- Understand containers and orchestration; the ideal candidate will be comfortable containerizing applications, working with Kubernetes, and running systems in production
- Be experienced in IaC and cloud deployment; we deploy applications to private and public cloud environments using cloud-native tooling and IaC principles
- Familiar with ML/AI concepts and practices; candidates should be comfortable with concepts such as model development, training, and monitoring
Preferred Requirements:
- Knowledge of standard ML/AI libraries; for example, Pandas, scikit-learn, TensorFlow/PyTorch/JAX, Kubeflow, etc.
- Fluency in other programming languages; much of the cloud-native ecosystem is built in Go, and many of our applications include JavaScript-based components
- Familiarity with software architecture; we are often tasked with building new systems and designing infrastructure for scale
- Proficiency in SQL; knowledge of SQL is occasionally required for data ingestion and analysis
- Proven engineering background; a technical degree in a field such as Computer Science or Data Analytics and/or equivalent work experience
- Relevant certifications; technical certifications, particularly ones related to DevOps (CKA, CKS, RHCSA, etc.)
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