ML Data Operations Lead – Dataset Release and Delivery, Autonomous Vehicles

• Serve as the primary operational partner for ML engineers and other internal consumers of AV datasets
• Capture and clarify dataset release requirements, including intended use cases, required signals and labels, data volumes, release cadence, delivery timelines, storage destinations, and acceptance criteria
• Own the release calendar and coordinate priorities, dependencies, engineering readiness, and compute capacity across multiple concurrent dataset-release tracks
• Monitor production release workflows from launch through delivery
• Identify failures, stalled tasks, resource constraints, missing data, and other risks, then coordinate engineers and infrastructure owners to drive resolution
• Validate release results against expected volumes, signals, versions, and quality criteria before communicating availability to customers
• Maintain timely, accurate communication with customers regarding release status, risks, incidents, changing estimates, and recovery plans
• Produce release notes, delivery announcements, known-issue documentation, and handoff information enabling ML teams to understand and use each dataset confidently

Requirements

• Bachelor's degree in Computer Science, Engineering, Data Science, Information Systems, or a related field, or equivalent experience
• 6+ years of experience in ML data operations, technical service delivery, dataset operations, release operations, technical program execution, or another data-intensive operational role
• Solid understanding of the machine learning data lifecycle, including data collection, curation, labeling, validation, versioning, release, storage, and consumption by training or evaluation pipelines
• Ability to use SQL and data-analysis tools to investigate dataset contents, reconcile expected and delivered results, and identify quality or completeness issues
• Strong customer orientation and skill in translating between ML engineers, data specialists, infrastructure teams, and other technical collaborators
• Excellent written communication skills, including the ability to produce detailed requirements, release notes, status updates, incident summaries, and operating procedures
• Excellent judgment when balancing customer timelines, engineering capacity, system reliability, data quality, and competing release priorities
• Proven track record of influencing without direct authority and driving work to completion across a highly matrixed organization
• Comfort operating in a fast-moving environment where requirements, data availability, and technical constraints may change quickly
• Experience operating large-scale dataset generation, materialization, validation, or delivery workflows, especially for autonomous-driving, ADAS, robotics, or computer-vision systems
• Familiarity with automotive sensor and ground-truth data, including camera, lidar, radar, mapping, calibration, or multimodal datasets
• Hands-on experience with Python, notebooks, Databricks, dashboards, or lightweight automation used to investigate data and improve operational workflows
• Experience defining service-level objectives, operational metrics, alerting, incident-management practices, and root-cause corrective actions
• A track record of converting frequently repeated customer requests or operational problems into standardized, automated, and scalable services

Core Competencies

Demonstrates expertise in ML Data Operations, including dataset release management, validation, and communication with stakeholders. Proficient in SQL and Python for data analysis and operational workflow improvement.

Highest-signal resume keywords

• ML Data Operations
• Dataset Release Management
• SQL Proficiency
• Python Experience
• Customer Communication

Hard Skills

• Dataset Operations
• Data Validation
• Data Curation
• Data Labeling
• Data Quality Assessment
• Technical Program Execution
• Operational Metrics Definition
• Service-Level Objectives
• Incident Management
• Root-Cause Analysis

Soft Skills

• Customer Orientation
• Excellent Written Communication
• Judgment in Prioritization
• Influencing Without Authority
• Adaptability in Fast-Moving Environments

Industry Keywords

• Machine Learning Data Lifecycle
• Autonomous Driving
• ADAS
• Robotics
• Computer Vision
• Automotive Sensor Data
• Ground-Truth Data
• Lidar
• Radar
• Multimodal Datasets

Tools & Technologies

• SQL
• Python
• Databricks
• Dashboards
• Notebooks
• Lightweight Automation