Senior Software Engineer, Platform Engineering

DS creates systems that power the next generation of radio spectrum intelligence. We collect radio data from all over the world, train neural networks to decipher it, and run them on the smallest chips we can. We’re solving a new, technically hard problem where nothing from other fields works out of the box, and along the way, we’ve built our own stack from scratch, including entirely new embedding model architectures, custom GPU kernels, and much more.

Joining DS means owning major parts of a fast-growing AI research organization, joining a collaborative, talent-dense team with decades of experience in probabilistic ML, accelerated computing, embedded systems, and signal theory, and growing your career in the areas that interest you. You’ll fit in if you want to come to work for the problem itself and don’t want to choose between technical rigor, business value, and real-world impact.

We work with high ownership and trust.

Everything DS ship; inference services, data pipelines, agents, and the UI, it all runs on infrastructure this role owns. We're hiring a Platform Engineer to build the foundation that lets a fast-moving team deploy many times a day, scale to meet unpredictable load, and do it all securely.

You'll own our CI/CD, infrastructure-as-code, and cloud deployment strategy, and you'll bring a DevSecOps mindset to how we build: security and compliance as part of the pipeline, not a gate at the end.

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  Design, build, and operate our cloud infrastructure across environments using infrastructure-as-code; make it reproducible, reviewable, and easy to evolve.

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  Own CI/CD end to end: build pipelines, artifact management, testing gates, progressive delivery, and rollback strategies for services, ML models, and data jobs.

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  Automate infrastructure scaling and deployments, autoscaling for GPU and CPU workloads, capacity planning, and cost controls that keep our cloud spend proportional to value.

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  Embed security into the platform: secrets management, IAM and least-privilege access, vulnerability scanning, dependency and container hardening, policy-as-code, and audit logging.

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  Build observability as a platform capability: metrics, logs, tracing, alerting, and SLOs that engineers can adopt with minimal friction.

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  Run large-scale cloud deployments reliably, including incident response and post-incident improvements.

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  Create developer tooling and paved paths so product engineers can ship safely without becoming infrastructure experts.
  

• 4+ years of experience in platform, infrastructure, DevOps, or SRE roles supporting production systems at meaningful scale.

• Hands-on DevSecOps experience and integrating security scanning, secrets handling, access control, and compliance checks directly into delivery pipelines.

• Deep experience with CI/CD tooling (GitHub Actions, GitLab CI, Buildkite, ArgoCD, Jenkins, etc.) and deployment strategies (blue/green, canary, feature flags).

• Strong experience with AWS (or GCP / Azure) at scale — compute, networking, storage, IAM, managed Kubernetes, and cost management.

• Expert-level infrastructure-as-code skills with Terraform, Pulumi, CloudFormation / CDK, or similar; plus configuration management or GitOps workflows.

• Experience with containers and orchestration (Docker, Kubernetes, Helm) in production, including autoscaling and multi-environment management.

• Solid programming ability in Python, Go, or Bash for automation and tooling.

• Strong operational instincts: you think about failure modes, blast radius, and recover-ability before they become incidents.
  

• Experience running GPU workloads and ML infrastructure in the cloud.

• Experience with compliance frameworks and secure or air-gapped deployments (e.g., FedRAMP, CMMC, IL environments).

• Familiarity with edge / hybrid deployments where cloud infrastructure coordinates with on-device or on-prem systems.

• Experience with observability stacks (Prometheus, Grafana, OpenTelemetry, Datadog).

• Fast learners over specific backgrounds – We care more about how quickly you can pick up new skills than where you’ve worked before.

• Intellectual honesty – The right answer matters more than being right. You challenge assumptions, test ideas, and pivot when needed.

• Adaptability – We’re organized, but sometimes things change quickly. You find a way to make it work and balance short-term deliverables with long-term goals.

• Ownership of outcomes – You optimize your own time, focus on what matters to deliver quickly, and cut out inefficiencies.

• Not building in a vacuum – You stay connected to the rest of our teams and our customers to make sure all the pieces fit together.