AI ML Engineer

AI/ML Engineer

Remote

We are seeking an AI/ML Engineer to join us. This role is remote, collaborating with a major automotive client out of Detroit.

Duties and Responsibilities:

• The AI/MLOps Engineer (AMOE) is an applied solutions expert who combines working knowledge of software engineering, machine learning, and DevOps best practices.
• As part of a small team of dedicated AI problem solvers, an AMOE draws upon their practical skills to build CI/CD pipelines, deploy applications, promote security by design, and generally automate all the things.
• Our team creates production ML/AI applications spanning multiple business domains, from logistics and operations to sales and business optimization.
• Our work often involves collaboration with vendors, business stakeholders, etc., therefore communication skills and the ability to capture ideas in diagrams and documentation are equally important.
• To help everyone sleep soundly at night, we seek teammates who write code with an eye for maintainability and testability.
• We like integration tests, CI/CD, observability, and twelve-factor design.

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.
• Isn't 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.
• Works (UTC-5)-compatible hours.

Qualifications:

Education and Years of Experience:

• 8 years of experience.
• 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.).

Desired Skills/Certifications:

• Fluent in Python. Fluent candidates can comfortably read and write Python code; write method and class docstrings; manage package dependencies in a principled way.
• Comfortable with git. We use GitHub extensively to develop and deploy our code; candidates should be comfortable writing quality PRs, utilizing GitOps, etc.
• Strong command line skills in *nix environments. Our code is built in and deployed to Unix-like environments; candidates should feel at home on the command line.
• Excellent understanding of networking and security. Our work often extends across multiple networks and environments and deals with sensitive data.
• Understands containers and orchestration. The ideal candidate will be comfortable containerizing applications, working with Kubernetes, and running systems in production.
• Experienced in IaC and cloud deployment. We deploy applications to private and public cloud environments using cloud-native tooling and IaC principles (Terraform, Argo CD, Istio, etc.).
• Familiar with ML/AI concepts and practices. Candidates should be comfortable with concepts such as model development, training, and monitoring.

Bonus Qualifications:

• 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; 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.