Senior Software Engineer - Platform

About us:

Calder is solving the data bottleneck for embodied AI and world models. Today's AI models lack the real-world, 4D data needed to reason on spatial problems and operate in physical environments. We capture, process, and deliver high-fidelity human-generated spatial data at scale, providing the substrate that trains the next generation of generalizable models for manipulation, navigation, and interaction.

About the Role:

You'll architect and scale the infrastructure that processes terabytes of 3D data daily, ensuring reliability, cost efficiency, and fast iteration for the engineering teams that depend on it.

- Engineer Calder's data processing infrastructure — compute orchestration, storage, scheduling, and monitoring

- Design and operate scalable GPU and CPU compute pipelines for 3D data processing workloads (SLAM, reconstruction, Gaussian Splatting training, dataset extraction)

- Assist in the development of pipeline orchestration systems, ensuring workloads run reliably, are observable, and recover gracefully from failures

- Manage and leverage cloud infrastructure (AWS) including ECS/Fargate, EC2 GPU instances, S3, and networking — balancing performance with cost

- Build and maintain data versioning and lineage infrastructure (e.g., LakeFS, data lake architecture)

- Contribute to SLAs for data processing throughput and reliability; instrument pipelines with metrics and alerting

- Utilize infrastructure-as-code practices (Terraform) and CI/CD for infrastructure changes

- Collaborate with 3DGS, SLAM, QA, and delivery teams to understand workload requirements and translate them into platform capabilities

- Mentor and grow yourself and others in a small infrastructure engineering team

About you:

- Large scale production experience in infrastructure engineering, platform engineering, or MLOps.

- Experience with AWS (ECS, EC2, S3, IAM, VPC, CloudWatch) or equivalent cloud platform

- Strong grasp of container orchestration (Docker, ECS, Kubernetes) and compute scheduling

- Experience managing GPU workloads at scale (training, inference, or batch processing)

- Proficiency with infrastructure-as-code (Terraform, Pulumi, or CloudFormation)

- Hands-on experience with pipeline orchestration frameworks (Dagster, Airflow, Prefect, or similar)

- Strong systems thinking — you understand how to design for reliability, observability, and cost at scale

- B.S. or M.S. in Computer Science, Software Engineering, or a related field

Even better:

- Experience with data versioning systems (LakeFS, DVC, Pachyderm)

- Background in 3D data processing, computer vision, or robotics infrastructure

- Familiarity with medallion / data lake architectures (bronze → silver → gold)

- Experience with Datadog, OpenTelemetry, or similar observability stacks

- Knowledge of cost optimization strategies for GPU compute (spot instances, right-sizing, scheduling)

- Experience with high-throughput data pipelines processing TB-scale sensor data

- Contributions to open-source infrastructure tooling

Calder is an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status. Learn more here. https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf

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