April 2026 monthly summary: Focused on reliability, scheduling efficiency, and cross-project integration. Key outcomes include a SLURM GPU job exclusivity fix in NeMo-Skills that prevents unintended GPU occupancy due to sbatch_kwargs mutation, improving resource allocation and throughput. In NVIDIA/NeMo, delivered vLLM-ready SpeechLM checkpoints and enhanced multimodal prompting, ensuring compatibility with Hugging Face transformers; added tokenization/config improvements and unit tests to safeguard backward compatibility. These updates reduce operational risk, accelerate deployment of multimodal SpeechLM workflows, and strengthen the foundation for vLLM-enabled inference. Technologies demonstrated include SLURM scheduling, HF transformers, NeMo's to_hf.py tooling, tokenizer/config handling, and test-driven development.