Software Engineering Manager, LLM Training

This role will be based in Mountain View CA.

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.

As a Software Engineering Manager of the Post-Training Infra team you will architect the high-throughput systems required for Supervised Fine-Tuning (SFT) and RL Multi-Techer Distillation Reinforcement Learning from Human Feedback (RLHF) Agentic Performance Optimization and Agentic Research at scale. You wont just be running scripts; youll be optimizing the engine that makes rapid model alignment possible.

Responsibilities

• Distributed Training Enablement: Enable and support sophisticated parallelism strategies including data tensor pipeline context and expert parallelism for models exceeding 100B parameters. Provide optimized configurations reference examples and platform-level integration so that customer teams can effectively leverage these techniques

• Post-Training Expertise: Maintain deep expertise across the post-training landscape including Multi-Teacher Distillation RL-based alignment and optimization (RLHF GRPO) Pruning Quantization and Speculative Decoding. Build and maintain reusable platform components that enable customer teams to efficiently leverage these techniques in their workflows.

• Performance Engineering: Deep-dive into strategic customer workloads and drive workload-specific and platform-level optimizations including Liger Kernels FlashAttention low-precision training high-performance data I/O and inter-node latency reduction.

• Multi-Modal Strategy: Video and Audio Models Post Training strategy

• Framework & Ecosystem Mastery: Act as a bridge to the OSS community. You will contribute to and troubleshoot the Post-Training Stack including Liger PyTorch Hugging Face (Accelerate/Transformers) Megatron Ray VERL SGLang and vLLM.

• Observability & Profiling: Develop advanced telemetry for large-scale training runs. You will use profiling tools to debug hardware-level stalls (NCCL timeouts memory fragmentation) and provide internal teams with actionable insights into training stability.

• Containerized Lifecycle Management: Lead the development of the Golden Image environment. Maintain and distribute optimized containerized base images with compatible validated builds of PyTorch CUDA and the broader training stack to ensure seamless training on our clusters.

• Responsible AI & Compliance Partnership: Serve as the bridge between the training platform and Responsible AI teams collaborating on data compliance model evaluation and safety processes. Ensure the platform provides the tooling and integration points needed for RAI teams to effectively apply their frameworks throughout the training lifecycle.

• Agentic Strategy: Lead development of Agents for autonomous model research performance optimization

• Lead coach and manage core team of engineers working on building the infrastructure.

• Participate with senior management in developing a long-term technology roadmap for the team and company.

• Have the ability to dive deep into technical discussions to challenge the status quo and steer the team in the right direction/to push the envelope.

• Communicate and collaborate effectively with stakeholders across engineering and business leadership.

• Help the team realize their potential by setting clear expectations openly evaluating performance upholding accountability and providing challenges to stretch their skills.

• Drive a culture of operational excellence. Lead the team into defining performance goals metrics and building the infrastructure and tooling necessary to maintain a high quality bar and detect issues in real time.

• Create an inclusive work environment that fosters autonomy transparency innovation and learning while holding a high bar for quality.

Qualifications :

Basic Qualifications

• BA/BS Degree in Computer Science or related technical discipline or equivalent practical experience.

• 1 year(s) of management experience or 1 year(s) of staff level engineering experience with management training

• 5 years of industry experience in software design development and large-scale software engineering

• Experience in LLMs - Post Training and/or Inference for a year minimum

• Hands on experience developing distributed system
   

Preferred Qualifications

• MS or PhD in Computer Science or related technical discipline

• 2 years of hands-on software engineering/technical management and people management experience

• 7 years industry experience in software design development and algorithm related solutions.

• Experience in architecting building and running large-scale distributed systems

• Experience with industry opensource and/or academic research research papers published in the space

Suggested Skills

• Distributed systems

• LLM Training

• AI infrastructure

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. LinkedIn is committed to fair and equitable compensation practices.

The pay range for this role is $170000 - $277000 Actual compensation packages are based on several factors that are unique to each candidate including but not limited to skill set depth of experience certifications and specific work location. This may be different in other locations due to differences in the cost of labor.

The total compensation package for this position may also include annual performance bonus stock benefits and/or other applicable incentive compensation plans. For more information visit Information :

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No

Employment Type :

Full-time