B
Blue River Technology
Senior Technical Program Manager (See & Spray)
Skills
Machine LearningAIGitHubJiraRisk Management
8 days ago
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Important information
Contract type:
Permanent
Salary:
$158,000 – $238,000 / year
Location:
United States
Work mode:
Hybrid
Published on:
14 October 2026
What they need
- We are seeking a Senior Technical Program Manager to own the processes, tools, and systems that enable our software releases and field deployments
- This is not a role where you manage a single product release — you will support Robotics development (RSW), Computer Vision Machine Learning (CVML) model development, and internal tooling infrastructure that all mission-based teams depend on
- You will help ensure our release pipeline runs on a predictable cadence and that our data-collection feedback loops are automated and reliable, delivering features to customers in a timely manner
- Program leadership:
- Own end-to-end delivery of complex robotics programs spanning perception and application software
- Develop and maintain program schedules that account for the inherent uncertainty of ML development, including experimentation, data collection cycles, and model evaluation
- Define program structure, milestones, definitions, and exit criteria in collaboration with engineering leads – including what “good enough to ship” means
- Technical risk management:
- Identify technical risks proactively, beyond status reports, from understanding what is being built and what can go wrong
- Distinguish between ML performance risks (model performance targets), hardware risks (camera development, sensor data and actuator reliability), system integration risks (latency, VPU timing), and data risks (managing shifts between training and deployment environments)
- Specific missions focus and cross-functional coordination:
- Support current Over-the-Air update infrastructure while helping identify/resolve issues to increase overall customer and dealer trust in the technology
- Manage data collection cycles spanning the data pipeline, hardware deployment, field engineering coordination, and simulation tools to deliver high-quality ML and robotics models
- Accelerate the model development loop by ensuring faster feedback loops to enable a self-sustaining pipeline- This role requires someone who can drive cross-organizational alignment across engineering, product, and field operations
- Experience managing cross-organizational dependencies without direct authority over the teams involved. Expert at finding the right escalation points
- BS or MS in Engineering, Computer Science, or a related technical field
- Strong systems thinking ability to understand how changes in one part of the stack (new sensor, model update, firmware/middleware change) ripple through the rest
- Demonstrated ability to deploy the right tools (Jira, GitHub, risk matrices, dashboards, AI agents) to match the program’s complexity
- Strong written and verbal communication skills with the ability to present to executive leadership
- 8+ years of experience in technical program management, systems engineering, or a related technical role. 2 years minimum in a robotics or ML-intensive product environment
- Track record of defining metrics, standing up dashboards, and using data to drive decisions
- Strong technical acumen—ability to read architectural diagrams, write specs and test plans, and go deep on engineering issues when needed
- If you’re excited about this role but your experience doesn’t align completely with the job description, we encourage you to apply anyway
- Experience in autonomous systems
- Familiarity with machine learning model development and deployment pipelines
- Experience with HIL/SIL/XIL test infrastructure or V and V processes for safety-critical systems
- Experience with OTA update systems, field deployment logistics, or dealer- and customer-facing technical programs
- Demonstrated ability to own and improve SDLC processes across multiple teams. Experience with CI/CD pipelines, test automation frameworks, and DevOps practices
- Knowledge of data collection pipelines, log management systems, and data governance
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