3 days ago

Physical AI Ops Tech Lead

Qualcomm

On Site
Full Time
$198,000
Santa Clara, CA

Job Overview

Job TitlePhysical AI Ops Tech Lead
Job TypeFull Time
CategoryCommerce
Experience5 Years
DegreeMaster
Offered Salary$198,000
LocationSanta Clara, CA

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Job Description

About Qualcomm Robotics

Qualcomm Advanced Robotics Team is building the AI first stack and platform for the next generation general purpose robots — from AMRs and cobots to emerging humanoids. This involves pairing heterogeneous compute (CPU/GPU/DSP/NPU) with a full Robotics SDK and developer tooling for manipulation, perception, navigation, and fleet workflows. We leverage our success in automated driving product portfolio, advanced AI end-to-end development and tools, and safety architecture to accelerate growth in this emerging market.

About The Role

We are seeking a Tech Lead to lead the technical design and implementation of AI Ops for a next-generation robotics platform. This role combines deep technical leadership and team management, centered on building robust data pipelines, training and evaluation orchestration, and model operations (MLOps/LLMOps) to support continuous learning and safe, scalable deployment across distributed robotic systems.

As the Physical AI Ops Tech Lead, you will design and oversee AI-driven operational capabilities—telemetry ingestion, observability, anomaly detection signals, and automated remediation—by building the pipelines and infrastructure that produce, validate, deploy, and monitor models. Your primary focus will be on developing systems that enable model development and iteration at scale.

What You’ll Do

  • Lead the technical design of end-to-end data and ML pipelines spanning high-throughput telemetry ingestion, streaming/batch processing, curated training/eval datasets, and reliable lineage and data quality.
  • Build the platform for reproducible ML at scale: training orchestration, distributed jobs, experiment tracking, model registry, and gated promotion flows that enable continuous learning.
  • Operate real-time inference safely with robust serving, progressive rollouts (canary/blue-green/shadow), A/B experiments, automated rollback, and strict SLOs.
  • Own CI/CD pipelines and release processes for ML and robotics software, including automated builds, testing, deployment orchestration, and integration with observability and rollback mechanisms.
  • Establish comprehensive ML observability—data/feature drift, performance monitoring, and incident automation with playbooks—integrated with robotics safety guardrails, auditability, and fail-safe design.
  • Partner cross-functionally with robotics software/hardware, ML research, product, and operations to align interfaces, feature contracts, compliance needs, and reliability KPIs across cloud/edge.
  • Mentor and grow senior engineers across core platform services, data and model lifecycle tools, and externally facing SDKs setting crisp technical direction, code quality bars, and review culture.
  • Engage customers & partners as the senior technical face of the platform clarify requirements, guide integrations, and translate learnings into the roadmap.

How You’ll Lead

  • Set the technical bar for platform correctness, reliability, and developer experience.
  • Coach senior ICs and tech leads, building a strong review culture and CI/CD discipline for robotics AI Ops pipelines.
  • Partner with product and silicon teams to align software roadmaps with SoC capabilities and internal and external customer needs.

Why Qualcomm

  • Shape the core platform that powers intelligent, safe, and scalable robotic operations.
  • Lead a high-impact team at the intersection of data engineering, MLOps, and robotics.
  • Build on a mature developer ecosystem (RBx/QRB platforms, on‑device AI toolchains) and ship at the edge, globally.

Minimum Qualifications

  • Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 4+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.

OR

  • Master's degree in Computer Science, Engineering, Information Systems, or related field and 3+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.

OR

  • PhD in Computer Science, Engineering, Information Systems, or related field and 2+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.

Preferred Qualifications

  • MS in Computer Science, Robotics, Electrical Engineering, or related field; PhD a plus.
  • 5+ years in software/platform engineering, including 3+ years in technical leadership or staff-plus roles.
  • Proven experience building large-scale data pipelines and MLOps platforms; strong background in distributed systems, SRE/DevOps, and safety-critical environments.
  • Expertise in data streaming (PubSub, ETL), ML workflow tools (MLflow/W&B, Argo, model registries, feature stores), and infrastructure (Kubernetes, IaC, cloud platforms, edge computing).
  • Proficiency in Python, Go, and C++ with solid systems design and reliability engineering; familiarity with observability tools (Prometheus, OpenTelemetry) and incident automation.
  • Strong architectural decision-making, communication, and stakeholder management skills across engineering, research, and operations.
  • Experience with continuous learning systems (automated data curation, drift/bias monitoring, gated promotions).
  • Knowledge of functional safety and compliance frameworks relevant to robotics (e.g., ISO 26262-like principles, IEC 61508-inspired practices).
  • Prior delivery of AI Ops/MLOps platforms supporting multiple teams and models at scale.

Why Join Us?

  • Shape the core platform that powers intelligent, safe, and scalable robotic operations.
  • Lead a high-impact team at the intersection of data engineering, MLOps, and robotics.
  • Competitive compensation, benefits, and opportunities for technical leadership growth.

Key skills/competency

  • MLOps
  • Robotics AI
  • Data Engineering
  • Distributed Systems
  • Kubernetes
  • CI/CD
  • Python
  • Go
  • C++
  • Functional Safety

Tags:

Physical AI Ops Tech Lead
MLOps
AI Operations
Data Pipelines
Robotics
Distributed Systems
Observability
CI/CD
Technical Leadership
Experimentation
Functional Safety
Python
Go
C++
Kubernetes
MLflow
Argo
Prometheus
OpenTelemetry
Cloud Platforms
Edge Computing

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How to Get Hired at Qualcomm

  • Research Qualcomm's culture: Study their mission, values, recent news, and employee testimonials on LinkedIn and Glassdoor.
  • Tailor your resume for AI Ops: Highlight experience in MLOps, data pipelines, distributed systems, and robotics for maximum impact.
  • Showcase technical leadership: Emphasize projects where you've led AI operations, platform development, and mentored senior engineers.
  • Prepare for technical deep dives: Expect questions on MLOps, Kubernetes, Python, Go, C++, and systems design for large-scale, safety-critical environments.
  • Demonstrate collaboration: Discuss instances of successful cross-functional partnership and stakeholder management across engineering, research, and product teams.

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