We are looking for a Senior AI Software Research Engineer to turn cutting edge research ideas into high-performance, production-ready systems. You will bridge the gap between AI research and large-scale deployment, implementing algorithms that push the boundaries of efficiency, scalability, and capability in language and multimodal models. 

In this role, you will: 

• Translate experimental findings and research papers into optimized, measurable improvements in training and inference. 

• Design and optimize deep learning pipelines using frameworks like PyTorch, JAXvLLM, sg-lang.  

• Explore and implement novel approaches to attention variants, state space models and efficient distributed training 

•  Collaborate with research scientists, ML engineers, and infrastructure teams to move ideas from prototype to deployment with strong performance guarantees 

•  Profile, benchmark, and tune large-scale models for speed, stability, and cost efficiency. 

• You'll work in an environment that values scientific curiosity, engineering rigor, and a bias toward shipping value products, while exploring frontier AI concepts. 

Required: 
• M.Sc or PhD in Computer Science, Electrical Engineering, or equivalent.
• 5+ years of experience in software engineering or applied research, with deep expertise in Python and PyTorch. 
• Strong understanding of LLM and multimodal architectures, including transformers, state space Diffusion models. 
• Proven ability to implement ideas from AI/ML research papers into production-grade systems. 
• Hands-on experience with AI frameworks such as  vLLM, Megatron-LM, sg-lang 

• Demonstrated skill in profiling, optimization, and scalable distributed systems for training or inference. 
• Familiarity with algorithmic aspects of AI, especially efficiency and model compression. 

Preferred: 
• Contributions to open-source AI projects or published research. 
• Experience with model parallelism, memory-efficient attention 
• Knowledge of evaluation, and LLM fine-tuning pipelines. 

​Soft Skills: 
• Collaborative mindset that bridges research and product needs. 
• Mentorship orientation comfortable sharing knowledge with teammates of varied skill levels. 
• Strong communication and organizational skills, with a drive to deliver value iteratively while pursuing long-term innovation.