Senior Associate, Decision science
LinkedIn · Posted Oct 16
Professional networking, job search, recruiting, online learning, and B2B marketing services
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About the role
The AI team within LinkedIn's Tech COE organization is responsible for building a go-to-market engine that connects LinkedIn's solutions with customer needs at scale. The role focuses on building and deploying AI and GenAI solutions that turn complex data into actionable business insights, improve forecasting, and drive operational efficiency. As a Senior Associate Decision Science, you will lead end-to-end AI/ML initiatives, design and productionize machine learning, deep learning, and Generative AI models, and partner cross-functionally to scale data-driven processes and innovation.
What you will do
- Lead the end-to-end lifecycle of strategic AI/ML initiatives, from problem definition and solution design to production deployment and business adoption.
- Partner with Product, Engineering, Sales, and business stakeholders to identify high-impact opportunities and translate ambiguous business problems into scalable AI-driven solutions.
- Design, develop, evaluate, and productionize machine learning, deep learning, and Generative AI models, including agentic AI workflows where appropriate.
- Own technical solution architecture, model selection, experimentation strategy, and production deployment while ensuring scalability, reliability, and maintainability.
- Drive AI innovation by identifying opportunities to leverage LLMs, AI agents, recommendation systems, optimization techniques, and predictive modelling to improve business outcomes.
- Collaborate closely with Engineering and Infrastructure teams to build robust ML pipelines, automate model retraining, monitoring, and continuous evaluation.
- Define success metrics, conduct experiments, analyse outcomes, and communicate insights and recommendations to senior leadership.
- Mentor junior engineers through technical guidance, code reviews, and best practices in AI/ML development.
- Influence technical direction across multiple projects while driving engineering excellence and reusable AI platforms.
Skills used in this role
What the employer is looking for
- Master's or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative discipline.
- 7+ years of industry experience applying machine learning and statistical techniques to solve complex business problems.
- Programming skills in Python with experience building production-grade ML applications.
- Experience building scalable ML pipelines and integrating models into production systems.
- Experience working with large-scale structured and unstructured datasets using Spark, SQL, or distributed computing frameworks.
- Communication skills: ability to influence technical and non-technical stakeholders.
Preferred qualifications
- Experience building production-grade Generative AI applications using LLMs, Retrieval-Augmented Generation (RAG), AI agents and orchestration frameworks.
- Experience in deploying machine learning models in Azure cloud.
- Experience with distributed data systems such as Hadoop and related technologies (Spark, Presto, Pig, Hive, etc.)
- Background in any one of programming language (C#, Java, PHP, JavaScript)
- Experience designing multi-agent systems and autonomous AI workflows.
- Hands-on experience with modern AI frameworks such as LangGraph, LangChain, Semantic Kernel, AutoGen, CrewAI, or equivalent.
- Deep understanding of technical and functional designs for relational and MPP Databases.
- Familiarity with CI/CD, MLOps, model monitoring, observability, and production AI governance.
- Experience mentoring scientists and leading cross-functional technical initiatives.
- Publications, patents, or contributions to open-source AI projects are a plus.
Benefits and support
- Compensation and benefits are detailed in the job posting
About LinkedIn
LinkedIn is the world's largest professional network, connecting over a billion users globally to create economic opportunity. Owned by Microsoft, the platform provides tools for job searching, professional networking, B2B marketing, sales intelligence, and online learning. Through its data graph, it bridges the gap between global talent and enterprise organizations.
- Industry
- Professional Network
- Company size
- 10001+ employees
- Founded
- 2003-05-05
- Location
- Sunnyvale, California, USA
- Funding stage
- Public Company
Funding
Public Company · $103.5M raised
- 2003-11-01Seed$4.7M
- 2004-08-01Series A$10M
- 2007-01-15Series B$53M
- 2008-06-01Series C$22.7M
- 2014-05-15Post Ipo Debt$500M
Leadership
Chief Executive Officer
EVP of LinkedIn and Microsoft Office
President of Platforms and Digital Work
Senior Vice President & Chief Financial Officer
Senior Vice President & Chief Business Officer
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