C
$210,000 – $300,000
Listed on Confido’s own careers site. You apply with them directly — we never stand between you and the employer.
What this role is
Own the ML infrastructure layer at Confido, building the pipelines, serving systems, and cloud foundation that turn AI models into reliable, cost-efficient production systems at scale. This role suits someone who thrives at the intersection of software engineering and infrastructure, ready to give an AI/ML team a smooth path from research to production in a fast-growing startup.
Our summary, not Confido’s wording. The full posting is on their site.
Skills this role names
- Amazon Web Services (AWS)
- Apache Airflow
- Apache Kafka
- BentoML
- CI/CD
- Docker
- GitHub Actions
- Infrastructure as Code
- Kubernetes
- MLflow
- Python
- Ruby
- Snowflake
- Terraform
- V-Ray
- Vector Databases
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What they ask for
Required
- 5+ years in MLOps, ML platform, AI infrastructure, or platform engineering on production systems
- Strong Python and production application experience
- Deep cloud infrastructure understanding and distributed data systems
- Infrastructure as Code and CI/CD expertise
- Ability to run containerized workloads in production
- Experience productionizing AI/ML research systems end to end
- High ownership mentality in a startup environment
Nice to have
- LLMOps tooling experience (tracing, prompt management, eval frameworks)
- Inference optimization knowledge (vLLM, ONNX, TensorRT)
- Familiarity with ML orchestration platforms (MLflow, BentoML, Ray, Airflow)
- Large-scale data systems experience (Snowflake, Kafka)
- Vector database experience
- Managed ML services experience (Bedrock, SageMaker, Vertex AI)
- Multimodal or generative AI production experience