Senior Backend Software Engineer, Video Engineering
New
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Remote US- CA, Remote US- OR, Remote US- WA, Pacific Time ZoneFull-TimeSenior
Salary150,000 - 210,000 USD per year
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Job Details
- Experience
- 5+ years
- Required Skills
- AWSDockerPythonGCPKubernetesGrafanaPrometheusCI/CDRESTful APIsMicroservicesMLOpsDistributed Systems
Requirements
- 5+ years building production backend systems and scalable APIs, based in Pacific Time Zone
- Strong Python proficiency for backend services and tooling; comfort making pragmatic tradeoffs in a fast-moving product environment
- Cloud-native development experience on AWS or GCP, including containerization (Docker, Kubernetes) and serverless patterns
- Deep experience with distributed systems, microservices, and distributed job orchestration (queues, workers, retries, prioritization)
- Hands-on experience with FFmpeg for transcoding, muxing, stream manipulation, and segment-based processing
- Strong understanding of video codecs (H.264, H.265/HEVC, AV1), containers (MP4, MKV, WebM), and adaptive bitrate formats (HLS, DASH)
- Experience building and operating scalable video transcoding and processing pipelines, including proxy generation and media normalization
- Experience with backend-driven video editing workflows including timeline-based rendering, clip segmentation, and incremental re-processing
- Experience with large-scale media storage and delivery (S3, blob storage, pre-signed URLs, range requests) and performance optimization techniques (parallel encoding, chunked processing, intermediate artifact caching)
- Background in media, entertainment, or video streaming platforms; exposure to cloud-based media services (AWS MediaConvert, GCP Transcoder API, or similar) is a plus
- Advanced API design skills (RESTful, streaming, async patterns)
- Familiarity with model serving platforms (TorchServe, Triton, SageMaker endpoints, or similar)
- Experience with MLOps practices — model deployment, monitoring, versioning
- Exposure to CI/CD pipelines and observability tools (Prometheus, Grafana) for production systems
- Experience with AI-powered product features or agentic application architectures
- Hands-on experience running inference on ML/CV models in production — not research, but engineering models into reliable services
Responsibilities
- Design and build backend services for video processing workflows — ingestion, transcoding, 4K export, metadata extraction, and timeline operations
- Architect scalable, high-availability systems to support enterprise-grade video workloads across cloud-native infrastructure (AWS, GCP)
- Build and optimize APIs that power real-time and async frontend workflows, including streaming data delivery and long-running job orchestration
- Own performance and reliability for distributed video processing pipelines with low latency and high throughput requirements
- Collaborate closely with frontend engineers on API design, data models, and streaming strategies
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