Senior Software Engineer

Principal Staff Software Engineer, Machine Learning

Company Description

LinkedIn is the world’s largest professional network, built to create economic opportunity for every member of the global workforce. Our products help people make powerful connections, discover exciting opportunities, build necessary skills, and gain valuable insights every day. We’re also committed to providing transformational opportunities for our own employees by investing in their growth. We aspire to create a culture that’s built on trust, care, inclusion, and fun – where everyone can succeed.

Join us to transform the way the world works.

Job Description

LinkedIn Marketing Solutions (LMS) helps B2B brands reach, engage, and convert professional audiences on a safe, trusted platform. The Ads Trust Engineering charter builds scalable AI systems that improve Ads auto-review, traffic quality, brand safety/suitability/viewability, and transparency for members and advertisers, while enabling partner-led growth.

At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team.

Role Overview

As a Staff AI Engineer, you will lead end-to-end ML systems and AI defenses that protect members and maximize advertiser ROI across LinkedIn Marketing Solutions. You’ll own architecture and delivery from data pipelines to low-latency inference, partner across product/infra/DS to set technical direction, and raise the bar on engineering craftsmanship and operational excellence.

Responsibilities

• Design, build, and scale ML platforms and models for ads relevance, brand safety/suitability/viewability, and invalid traffic (IVT) / fraud detection in both 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 (e.g., topicality classification, policy defenses, safety prompts) with measurable precision/recall improvements.

• Lead experiment design (A/B, backfills, offline/online evaluation), build high-signal metrics and dashboards, and partner with the data science team to quantify impact.

• Drive system design for reliability and scale (caching strategies, partitioning, queue management, backpressure control, failover).

• Collaborate with product, policy, and legal on trust/transparency and compliance requirements; influence design for customer-facing transparency (e.g., “Why am I seeing this ad?”).

• Mentor engineers; establish best practices for testing, code quality, observability, capacity planning, and safe ramps.

• Champion agentic/AI-native development to improve engineering velocity (tests, PR reviews, CI/CD automation) and reduce operational toil.

 

Qualifications

Basic Qualifications

• 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 of experience 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.

Preferred Qualifications

• Experience with LLMs/GenAI (prompt design, evaluation, safety) and applying them 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).

Suggested Skills

• Machine Learning

• GenAI/LLMs

• Distributed Systems & System Design

• Streaming Data

• Experimentation & Observability

Additional Information

You Will Benefit From Our Culture

We strongly believe in the well-being of our employees and their families. That is why we offer generous health and wellness programs and time away for employees of all levels.

India Disability Policy 

LinkedIn is an equal employment opportunity employer offering opportunities to all job seekers, including individuals with disabilities. For more information on our equal opportunity policy, please visit https://legal.linkedin.com/content/dam/legal/Policy_India_EqualOppPWD_9-12-2023.pdf

Global Data Privacy Notice for Job Candidates ​

Please follow this link to access the document that provides transparency around the way in which LinkedIn handles personal data of employees and job applicants: https://legal.linkedin.com/candidate-portal.

Experience Level

Executive Level