Video Platform Engineer - E3 in Bangalore, भारत

Responsibilities

• Design resilient ingest pipelines from capture rigs to cloud storage, including recovery from partial uploads, unreliable networks, and hardware failures.
• Build transcoding, normalization, synchronization, and quality-checking pipelines for multi-camera video, telemetry, and sensor data.
• Create dataset versioning, lineage, indexing, packaging, integrity verification, and access-control systems for delivery to robotics laboratories.
• Optimize storage tiering, lifecycle management, egress, encoding efficiency, GPU utilization, and cost per captured hour or delivered dataset.
• Improve monitoring, logging, tracing, throughput, failure metrics, latency, reliability, and incident recovery across the pipeline.
• Troubleshoot issues spanning media tooling, storage, networking, and application code, and participate in production on-call rotation.
• Own complex initiatives from problem definition through design, implementation, operation, and performance measurement.
• Participate in code reviews and provide practical technical feedback.

Requirements

• 5+ years of experience building and operating production video or media-processing systems at scale.
• Production experience with FFmpeg, GStreamer, or an equivalent media framework, including building and debugging pipelines under load.
• Fluency with H.264, HEVC, AV1, MP4, fMP4, and the tradeoffs among codecs and containers.
• Strong understanding of distributed systems, cloud infrastructure, object storage, and observability.
• Experience with durable workflow orchestration such as Temporal, Conductor, Step Functions, Airflow, or similar tools.
• Experience designing cost-efficient architectures for large media or data workloads, including storage tiering, egress, capacity planning, and GPU utilization.
• Experience with infrastructure as code, CI/CD, and production operations.
• Strong programming and problem-solving skills.
• Preferred: experience with multi-camera or time-synchronized capture systems and clock-drift or alignment problems.
• Preferred: familiarity with MCAP, rosbag, ROS, ROS2, Parquet, or similar robotics and sensor-data formats.
• Preferred: familiarity with machine learning on video or images, including classification, detection, tracking, segmentation, re-identification, super-resolution, quality scoring, auto-annotation, or redaction.
• Preferred: experience with perceptual quality measurement, VMAF, encoding-ladder design, HLS, DASH, CMAF, DRM integration, or annotation and review tooling.

Benefits

• Free snacks.
• Health insurance and personal insurance.
• Flexible hours.
• Maternity and paternity leave.
• Broadband reimbursement.
• The company states that teams work in person five days a week, with hubs in San Francisco, Bangalore, and Chicago and offices in New York, Phoenix, and Singapore.