Strategic Project Lead, Robotics
Listing checked October 7, 2026 · pay as published by Micro1
Overview
This role puts you in charge of robotics data pipelines from the first frame captured to the final handoff. You will work with multi-camera rigs, RGB/stereo/IMU sensors, and FPS constraints to keep quality high while scaling operations. The position sits at the intersection of engineering, operations, and finance, so expect to translate client needs into systems that actually run. It is a full-time, remote role with a national salary range of $120,000 to $160,000 plus equity and performance bonuses.
What You'll Do9
- 1Take full ownership of robotics data pipelines, from capture through delivery, with direct accountability for quality and timelines.
- 2Build and refine large-scale data collection and processing systems that handle high throughput.
- 3Balance cost, quality, and throughput as you scale operations.
- 4Set up and maintain hardware systems including multi-camera rigs and RGB, stereo, and IMU sensors.
- 5Lead data transformation work that matches strict client schemas and formats.
- 6Spot bottlenecks and create automation for validation, QA, and reporting.
- 7Write and enforce capture protocols, workflows, and operational standards.
- 8Turn client requirements into executable systems and processes.
- 9Partner with engineering, operations, and finance teams to drive execution on complex projects.
Requirements11
- 1Solid experience with robotics data pipelines or other high-throughput data systems.
- 2Hands-on work with sensor systems, FPS constraints, and multi-camera setups.
- 3Analytical mindset with the ability to weigh cost against speed and quality.
- 4Clear communication across technical and non-technical teams.
- 5Background in large-scale data processing, storage, and delivery.
- 6Proven track record defining schemas, protocols, and operational standards.
- 7Experience driving cross-functional execution and improving systems.
- 8High ownership and comfort operating in ambiguous environments.
- 9Preferred: experience scaling robotics data operations from pilot to production.
- 10Preferred: built internal tools for data validation, QA, or pipeline automation.
- 11Preferred: worked directly with clients on technical data requirements.
Who Should Apply
The ideal candidate has hands-on experience with robotics data pipelines, sensor systems, and multi-camera rigs, and can point to specific projects where they defined schemas or protocols. You should be comfortable balancing cost, quality, and throughput while working across engineering, operations, and finance. This role is less suited for someone who prefers a narrow, single-team focus or who has not worked with hardware and data at scale. A common reason candidates get rejected is lacking concrete examples of scaling data operations or building validation and QA automation. Another is failing to show how they translated client requirements into working systems.
Salary Insight
The national pay range for this full-time position is a base salary of $120,000 to $160,000. Employees are eligible for equity compensation and may receive performance-based bonuses depending on role and company policies. Benefits include up to 100% reimbursement for health-insurance premiums, paid time off, and a 401(K) plan with a company match.
Pay and demand for Data Engineering roles
AggregatedTypical pay
$80/hour
This role
$7–$8/hr
Most Data Engineering roles pay $50–$99 per hour. This role's pay sits below that range.
Based on 134 similar roles that publish pay · 22 publish only a top rate; those count at the rate they gave
Rates shown per hour. Yearly and monthly pay converted; one-time fees and non-USD pay are not included.
- Live similar roles
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Most requested skills · share of roles
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Compensation
$7–8/hr
Required Skills
Application Tip
In your application, highlight specific projects where you owned a robotics or high-throughput data pipeline end-to-end. Name the exact sensor types, FPS constraints, and schemas you worked with, and quantify the scale you handled, such as number of cameras, data volume, or throughput improvements. This directly matches the core requirements and helps your fit score.
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