Supply Chain BD

Glint Tech Solutions; Los Angeles (CA); On-site; USD 90,000 - 130,000; Full time

Job summary

Glint Tech Solutions is seeking a passionate, execution-driven Supply Chain BD leader to expand data collection scenarios for embodied robotics. You will help build and operate a crowdsourcing model, manage a diverse data-collector network, and ensure high-quality multimodal data for AI model training in real-world environments.

The role focuses on expanding data acquisition opportunities across factories, households, retail, healthcare, and logistics, with an emphasis on scalable operations and

Qualifications

• Bachelor’s degree or above in CS, Communications, Automation, Data Science, Management or related fields.
• 3+ years in supply chain, BD, operations, project management, or data management, incl. at least 1 year of team management.
• Crowdsourcing models or sharing economy experience preferred; backgrounds in AI data sector valued.
• Hands-on crowdsourced operations in ride-hailing/local on-demand services are highly preferred.

Responsibilities

• Plan and execute expansion of data collection scenarios for embodied robots in real-world environments (factories, households, retail, healthcare, logistics).
• Build and operate a crowdsourcing data collection model and manage a diverse data-collector supply chain.
• Establish systems for recruitment, training, task dispatching, incentives, and retention to ensure a stable data supply.

Skills

Supply chain

Business development

Operations

Project management

Data management

Team management

Crowdsourcing

Sharing economy

Education

Bachelor's degree or above

Job description

Location: Bay Area/Los Angeles

Job Overview

We are seeking a passionate and execution-driven Supply Chain BD leader to spearhead data collection scenario expansion and crowdsourced operations for embodied robotics. You will participate in building and operating a crowdsourcing supply chain model for embodied robot data collection, expanding data acquisition opportunities in real-world scenarios, and ensuring the delivery of high-quality, multimodal data for embodied AI model training. If you are deeply interested in building a \"data production network\" and are willing to accumulate experience through frontline, hands-on operations to achieve rapid growth, this is an excellent opportunity to join a team in the cutting-edge field of AI infrastructure.

Core Responsibilities

Scenario Expansion & Supply Chain Ecosystem Building

• Assist in planning and executing the expansion of data collection scenarios for embodied robots, going deep into the frontline to uncover data collection opportunities in real-world environments such as factories, households, retail, healthcare, and logistics.


• Participate in building and operating the data collection \"crowdsourcing model\", assisting in the management of a diverse supply chain of data collectors (e.g., community residents, freelancers, part-time workers, etc.).


• Assist in establishing systems for collector recruitment, training, task dispatching, incentives, and retention to ensure a continuous and stable data supply chain.

Crowdsourcing Platform & Data Pipeline Management

• Take charge of the day-to-day operations of the entire data collection workflow, including task creation, collection execution, initial quality screening, and data delivery.


• Collaborate with product and technical teams to provide feedback on the user experience of crowdsourced collection tools, driving iterative optimization of these tools.


• Execute quality control processes to ensure the validity, accuracy, and compliance of the collected data.

Operational Empowerment & Scaled Growth

• Assist in formulating scaling strategies to cover more regions and scenarios, increasing the density and production capacity of the data network.


• Identify and resolve common issues in daily operations (such as capacity fluctuations, cost control, collection team activity rates, etc.) to continuously optimize operational efficiency.


• Collaborate with the Business Development (BD) team to translate crowdsourced collection capabilities into delivery support for commercialized data products.

Team & Vendor Management

• Responsible for building, training, and managing a small data operations team on a daily basis (including collection specialists, QA specialists, etc.).


• Manage and coordinate external crowdsourced collectors and third-party data service vendors, tracking key performance indicators (KPIs).

Cross-Functional Collaboration

• Work closely with hardware R&D, algorithm teams, product departments, and the broader BD department to co-define data collection specifications and standards.


• Act as the operational interface between clients and R&D teams, precisely understanding requirements to ensure datasets are delivered on time and with high quality.


• Assist in managing regional operational budgets, ensuring all data collection and processing activities strictly comply with US data privacy, security, and relevant regulations.

Job Requirements

• Educational Background: Bachelor’s degree or above. Majors in Computer Science, Communications, Automation, Data Science, Management, or related fields are preferred.


• Core Experience: 3+ years of experience in supply chain, BD, operations, project management, or data management, including at least 1 year of team management experience. Those with a certain understanding of or practical experience in crowdsourcing models or the sharing economy are preferred; backgrounds in crowdsourced operations within ride-hailing, local on-demand services, or the AI data sector are highly preferred.


• Crowdsourcing & Rollout Expertise: Hands-on experience in crowdsourcing models, the sharing economy, or managing large-scale localized rollouts and promotional campaigns is required. Backgrounds in crowdsourced operations within ride-hailing, local on-demand services, or the AI data sector are highly preferred.


• Scenario Expansion Capability: Possess awareness of supply chain and scenario expansion, and understand the operational characteristics of at least one real-world scenario (e.g., households, factories, retail, etc.).


• Technical Understanding: Ability to understand the basic technical requirements of embodied AI data collection. Familiarity with sensors, data formats, and collection specifications is preferred.


• Execution & Responsibility: Ability to go deep into the frontline to solve practical operational problems, possessing a strong sense of responsibility and determination to achieve goals.


• Communication & Collaboration: Excellent cross-departmental and cross-team communication and coordination skills, with the ability to effectively manage and motivate small teams.


• Language Skills: Excellent verbal and written communication skills in English. Proficiency in Spanish is a major plus for engaging with local communities and external teams.