Senior Machine Learning Engineer Platform Data Services

Job Location:

Dublin - Ireland

Monthly Salary: Not Disclosed

Posted on: 9 hours ago

Vacancies: 1 Vacancy

Department:

Engineering

Job Summary

This role will be based in Dublin Ireland. 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.

We are seeking a Senior Machine Learning Engineer to help build the next generation of AI-powered systems that understand reason over and act on complex user intent. You will work on foundational capabilities that enable agentic experiences semantic understanding and large-scale AI-driven decision systems. These systems translate natural language into structured representations power intelligent workflows and continuously evolve as new concepts emerge.

This role sits at the intersection of Generative AI retrieval systems and large-scale distributed infrastructure. You will help define the architecture and direction for how AI systems operate at scale balancing flexibility accuracy and trust.

Youll work on problems such as:

Enabling AI systems to reason retrieve and act across large evolving data spaces
Building platforms that support multiple AI-driven applications and agents
Translating ambiguous natural language into precise structured representations
Designing systems that combine symbolic structure with learned representations

This is a highly cross-functional role with the opportunity to shape how AI systems are built evaluated and deployed across a wide range of products and experiences. A successful candidate will be comfortable operating at the intersection of AI research and engineering. You will collaborate with a world-class team of researchers and engineers to develop and advance the next generation of AI models to push the boundaries of AI at scale.

Responsibilities:

Research design and develop large-scale foundation AI models with a focus on LLMs transformer architectures.
Develop retrieval and ranking systems (e.g. embedding-based retrieval reranking hybrid approaches) to support high-quality low-latency AI experiences
Build shared infrastructure and platforms that enable multiple AI-driven applications and agentic workflows
Design and implement evaluation frameworks to measure quality relevance consistency and grounding of AI system outputs
Develop and maintain scalable AI pipelines optimizing training and inference workflows to handle vast amounts of data.
Collaborate with cross-functional teams of machine learning engineers infrastructure engineers and product teams to deliver impactful AI innovations across LinkedIns products.

Qualifications :

Basic Qualifications

BA/BS Degree in Computer Science Machine Learning or related technical discipline or related practical experience.
2 years experience in machine learning or AI engineering.
2 years experience in design and development of algorithmic solutions
2 years experience with programming languages such as Java Python etc.

Preferred Qualifications

4 years of hands-on experience in large-scale model training model-system co-design or large AI systems.
PhD in Computer Science Machine Learning or related technical discipline with a focus on advanced AI/ML techniques
Proven experience in building and optimizing large-scale AI/ML models using frameworks such as PyTorch PySpark and CUDA.
Several recent publications in top AI conferences on relevant areas including but not limited to Large Scale Model Training and LLM Algorithm Optimization deep learning reinforcement learning foundation models etc.
Expertise in distributed training model parallelism and hardware acceleration for AI workloads including GPUs and TPUs.
Demonstrated ability to solve complex AI challenges in large-scale environments optimizing models for efficiency and scalability.
Strong proficiency in AI system design model optimization and the development of production-quality AI pipelines.
Published work in AI research or a significant contribution to industry-leading AI technologies.

Suggested Skills

Large Language Models (LLM)
Generative AI (GAI)
Agentic systems
AI Research and Development
Distributed AI Systems and Model Parallelism

Additional Information :

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: Work :

Employment Type :

Full-time

Youll work on problems such as:

Enabling AI systems to reason retrieve and act across large evolving data spaces
Building platforms that support multiple AI-driven applications and agents
Translating ambiguous natural language into precise structured representations
Designing systems that combine symbolic structure with learned representations

Responsibilities:

Research design and develop large-scale foundation AI models with a focus on LLMs transformer architectures.
Develop retrieval and ranking systems (e.g. embedding-based retrieval reranking hybrid approaches) to support high-quality low-latency AI experiences
Build shared infrastructure and platforms that enable multiple AI-driven applications and agentic workflows
Design and implement evaluation frameworks to measure quality relevance consistency and grounding of AI system outputs
Develop and maintain scalable AI pipelines optimizing training and inference workflows to handle vast amounts of data.
Collaborate with cross-functional teams of machine learning engineers infrastructure engineers and product teams to deliver impactful AI innovations across LinkedIns products.

Qualifications :

Basic Qualifications

BA/BS Degree in Computer Science Machine Learning or related technical discipline or related practical experience.
2 years experience in machine learning or AI engineering.
2 years experience in design and development of algorithmic solutions
2 years experience with programming languages such as Java Python etc.

Preferred Qualifications

4 years of hands-on experience in large-scale model training model-system co-design or large AI systems.
PhD in Computer Science Machine Learning or related technical discipline with a focus on advanced AI/ML techniques
Proven experience in building and optimizing large-scale AI/ML models using frameworks such as PyTorch PySpark and CUDA.
Several recent publications in top AI conferences on relevant areas including but not limited to Large Scale Model Training and LLM Algorithm Optimization deep learning reinforcement learning foundation models etc.
Expertise in distributed training model parallelism and hardware acceleration for AI workloads including GPUs and TPUs.
Demonstrated ability to solve complex AI challenges in large-scale environments optimizing models for efficiency and scalability.
Strong proficiency in AI system design model optimization and the development of production-quality AI pipelines.
Published work in AI research or a significant contribution to industry-leading AI technologies.

Suggested Skills

Large Language Models (LLM)
Generative AI (GAI)
Agentic systems
AI Research and Development
Distributed AI Systems and Model Parallelism

Additional Information :

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: Work :

Employment Type :

Full-time

Key Skills

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