About the opportunity
We are hiring on behalf of a global digital engineering company.
The team builds the developer tooling, platforms and systems that power a large Cloud AI Platform. You will partner directly with internal customers to understand their AI/ML use cases, prototype quickly, harden solutions for production and feed insights back to platform teams to influence the roadmap and improve the developer experience.
What you will do
- Partner with internal product teams to understand AI/ML use cases and translate requirements into technical solutions.
- Build production-ready services, integrations, workflows and developer tooling on top of the Cloud AI Platform.
- Prototype rapidly, validate approaches with customers and harden successful prototypes for production.
- Turn recurring customer needs into reusable platform capabilities and tooling.
- Work with platform teams to improve APIs, SDKs, workflows, documentation and developer experience.
What we are looking for
- 3+ years of hands-on engineering experience with Python as your main language (Go or Scala is a plus).
- Experience building and deploying services and ML pipelines with Docker and Kubernetes on AWS, Azure or GCP.
- Infrastructure as Code (Terraform, CloudFormation) and CI/CD (GitHub Actions, GitLab CI, Jenkins).
- Data pipeline orchestration (Airflow, Prefect, Dagster) and streaming (Kafka, Kinesis).
- Monitoring and observability (Prometheus, Grafana, ELK) for systems and ML models.
- Strong software engineering fundamentals, Git and DevOps practices.
- Clear communication with both technical and non-technical audiences.
- BS/MS in Computer Science or a related field, or equivalent experience.
Nice to have
- ML frameworks and tooling: PyTorch, TensorFlow, MLflow, Kubeflow, Weights & Biases, Feast.
- Security and data governance for ML systems.
- Automated testing for ML systems, including data validation and model testing.
What we offer
- Fully remote role within the US.
- Full benefits package.
- Work on a large-scale Cloud AI Platform with direct impact on its roadmap.
- Three-step interview process: technical, client-facing and non-technical.
Source: Wellfound.
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