Software Engineer 3
Builds and operates the systems, tooling, and deployment workflows that deliver Voyage embedding and reranking models across cloud marketplaces, third-party inference providers, and self-managed environments. The role requires backend or infrastructure experience, cloud and Kubernetes expertise, and familiarity with ML model serving.
About the job
Responsibilities
- Port and tune the model server that runs Voyage embedding and reranking models, improving inference performance, consistency, and runtime behavior across environments.
- Productionize new Voyage models for delivery beyond first-party Atlas, owning packaging, configuration, and deployment workflows across AWS, Azure, GCP, and other environments.
- Design correctness, correlation, and performance validation to verify that third-party deployments match first-party behavior.
- Build operability into every surface through structured logging, metrics, diagnostics, and health checks.
- Debug issues spanning model servers, containers, deployment configuration, and partner cloud environments.
- Collaborate with model-serving teams and partner with GTM, solutions architects, technical support engineers, and strategic customers on external deployments.
Requirements
- 4+ years building backend or infrastructure systems, CI, or build tooling.
- Strong software engineering skills in languages such as Python or Go, with an emphasis on performance and reliability.
- Experience with cloud environments such as AWS, Azure, or GCP; containers; and Kubernetes.
- Ability to debug across code, runtime, model servers, configuration, and external dependencies.
- Familiarity with ML model serving and inference runtimes.
- Clear communication and effectiveness in ambitious, cross-team work.
Nice to Have
- Experience productionizing or deploying ML model servers or inference runtimes, such as vLLM, Triton, or TGI.
- Experience with observability stacks such as Prometheus, Grafana, or OpenTelemetry.
- Experience shipping software through cloud marketplaces or partner/self-managed channels.
- Contributions to open-source infrastructure for ML serving or deployment.
Benefits
- High-visibility ownership of how Voyage’s AI models reach customers outside first-party Atlas.
- Varied engineering work across model-server inference, CI deployments, observability, and cloud integration.
- Collaboration with ML and platform teams bringing new models to market.
- A culture emphasizing ownership, pragmatism, technical judgment, and clarity in ambiguous situations.
Skills
Python, Go, AWS, Azure, GCP, Containers, Kubernetes, Prometheus, Grafana, OpenTelemetry, vLLM, Triton, Tgi, CI/CD, Ml Model Serving
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