Senior Software Engineer, Data Platform

NxT Level•Torrance, CA

4d•Onsite

About The Position

Our client is hiring a Senior Software Engineer, Data Platform to help build the real-time ML data platform behind autonomous and semi-autonomous marine systems. This is a high-impact role for an engineer who is passionate about autonomy, maritime sensing, defense technology, and large-scale data infrastructure. You’ll help define how raw maritime signals become clean, consistent, labeled datasets that power perception models, foundation models, evaluation systems, and AI-driven analytics. The core challenge is building a platform that can ingest, process, store, reprocess, and analyze data from thousands of marine systems across a wide range of sensors, hardware interfaces, and data sources — all with a high bar for security, reliability, reproducibility, and performance.

Requirements

Strong experience building data platforms, ML infrastructure, or large-scale data processing systems
Experience owning dataset quality, reproducibility, lineage, and evaluation fidelity
Strong Python experience and comfort with modern data tooling
Experience with tools such as PyArrow, Polars, Pandas, NumPy, SciPy, or similar libraries
Experience working with audio, vision, telemetry, sensor, or time-series data
Strong understanding of data pipelines, dataset versioning, metadata, and quality monitoring
Experience building APIs, SDKs, or access layers for data discovery and consumption
Ability to design systems that support both real-time and historical reprocessing workflows
Comfort working closely with ML, perception, hardware, and product teams
Strong ownership, technical judgment, and ability to operate in a fast-moving startup environment

Nice To Haves

Experience owning “dataset-as-a-product” systems used across multiple model families
Experience building curated corpora with strong lineage, documentation, and reproducibility
Experience designing dataset splitting or sampling strategies by time, platform, geography, class, signal quality, or similar dimensions
Experience preventing data leakage and improving model generalization through thoughtful dataset design
Hands-on experience with labeling workflows, ontologies, consensus systems, QA, or label-store integrations
Experience with Go, Rust, or TypeScript for services
Experience with orchestration tools such as Airflow or Prefect
Experience with metadata and lineage tools such as MLflow or Weights & Biases
Exposure to edge or sensor data, including audio, sonar, video, telemetry, time synchronization, or geospatial context
Experience in defense, maritime, autonomy, robotics, aerospace, or national security technology

Responsibilities

Build and operate a real-time ML data platform for autonomous and semi-autonomous marine systems
Define how raw maritime signals become clean, consistent, labeled datasets for perception and foundation models
Build post-processing pipelines that align, resample, and calibrate multi-sensor data
Create robust backfill and reprocessing frameworks for historical data
Apply new filters, synchronizations, label corrections, and metadata enrichments across large datasets
Establish lineage, versioning, and reproducibility standards for ML experiments
Build dataset discovery and access APIs/SDKs for downstream users
Enable teams to query datasets by time, region, modality, labels, and quality flags
Instrument data quality metrics across completeness, corruption, drift, label density, class balance, and regional coverage
Build dashboards, alerts, and canary dataset builds to improve data reliability
Optimize storage layouts for fast reads, parallelization, compression, chunking, sharding, locality, and prefetching
Partner closely with ML, perception, hardware, and product teams to map data contracts to model needs