LinkedIn is hiring a Principal Staff Software Engineer, Machine Learning to lead the development of end-to-end ML systems and AI defenses. You'll protect our members and maximize advertiser ROI across LinkedIn Marketing Solutions by owning architecture and delivery from data pipelines to low-latency inference.
What You'll Do
- Design, build, and scale ML platforms and models for ads relevance, brand safety/suitability/viewability, and invalid traffic/fraud detection in pre-bid and post-bid workflows.
- Own real-time scoring and streaming pipelines with strict SLA/latency requirements; drive robust feature engineering, model serving, monitoring, and auto-remediation.
- Apply and productionize LLM/GenAI techniques for tasks like topicality classification, policy defenses, and safety prompts to achieve measurable precision/recall improvements.
- Lead experiment design, build high-signal metrics and dashboards, and partner with data science to quantify impact.
- Drive system design for reliability and scale, including caching strategies, partitioning, queue management, backpressure control, and failover.
- Collaborate with product, policy, and legal on trust/transparency and compliance requirements; influence design for customer-facing transparency.
- Mentor engineers and establish best practices for testing, code quality, observability, capacity planning, and safe ramps.
- Champion agentic/AI-native development to improve engineering velocity and reduce operational toil.
What We're Looking For
- Bachelor’s degree in Computer Science or related field, or equivalent practical experience.
- 18+ years of experience in ML/AI and data-intensive systems.
- 4+ years leading technical design and delivery of production ML systems.
- Experience with Java, Scala, or Python and modern data/ML stacks (distributed systems, streaming, feature stores, online inference).
- Experience with streaming frameworks (e.g., Flink or Samza) and large-scale storage/indexing; designing resilient caches and partition strategies.
Nice to Have
- Experience with LLMs/GenAI (prompt design, evaluation, safety) applied to production trust/safety or relevance problems.
- Background in ad tech (ads review, auction dynamics, measurement, viewability, brand safety/suitability, IVT) and working with external partners/signals.
- Familiarity with privacy, compliance, and transparency domains within digital advertising.
- Track record building low-latency services at scale with rigorous SRE/observability practices (metrics, tracing, alerting, SLIs/SLOs).
Technical Stack
- Languages: Java, Scala, Python
- Architectures: Distributed systems
- Streaming Frameworks: Flink, Samza
- ML Infrastructure: Feature stores, Online inference
Benefits & Compensation
- Generous health and wellness programs.
- Time away for employees of all levels.
Work Mode
This position operates on a hybrid work model.
LinkedIn is an equal employment opportunity employer offering opportunities to all job seekers, including individuals with disabilities.
