Staff Software Engineer, Machine Learning

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.

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.

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.

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.

 

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 eval), 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.

 

 

Basic Qualifications:

- Engineering degree in Computer Science or related field, or equivalent practical experience.

- 10+ years in ML/AI and data-intensive systems; 4+ years leading technical design and delivery of production ML systems.

- Hands-on experience in Java/Scala/Python and modern data/ML stacks (e.g., distributed systems, streaming, feature stores, online inference).

- Proven track record building low-latency services at scale with rigorous SRE/observability practices (metrics, tracing, alerting, SLIs/SLOs).

Preferred Qualifications:

- Experience with LLMs/GenAI (prompt design, evaluation, safety) and applying them to production trust/safety or relevance problems.

- Expertise in streaming frameworks (e.g., Flink/Samza) and large-scale storage/indexing; designing resilient caches and partition strategies.

- 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.

 

Suggested Skills:

- Machine Learning, GenAI/LLMs 

- Distributed Systems & System Design

- Streaming Data 

- Experimentation, Observability

- AdTech Domain Expertise

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.

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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

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