Deskripsi Pekerjaan
About the Role
We are seeking a Senior Machine Learning Engineer to join our core research team at Nexus Intelligence Labs. You will architect, train, and deploy state-of-the-art deep learning models that power our next-generation AI products. This is a high-impact role with end-to-end ownership from research to production.
Why Join Us?
- Work on frontier AI problems with real-world deployment at scale.
- Generous equity package and competitive compensation.
- Flexible hybrid work policy (3 days onsite in our SoMa office).
- Annual learning budget ($5,000) and conference sponsorship.
Tanggung Jawab
- Design and implement novel deep learning architectures for large-scale multimodal models.
- Lead the full ML lifecycle: data curation, model training, evaluation, optimization, and production deployment.
- Build and maintain robust MLOps pipelines using Kubernetes, Kubeflow, and MLflow.
- Collaborate with product and research teams to translate business requirements into technical specifications.
- Mentor junior engineers and establish best practices for code quality, reproducibility, and experimentation.
- Conduct rigorous A/B testing and statistical analysis to validate model improvements.
- Stay current with latest advancements in LLMs, diffusion models, and reinforcement learning.
Kualifikasi
- M.S. or Ph.D. in Computer Science, Machine Learning, Statistics, or related quantitative field.
- 5+ years of industry experience building and deploying production ML systems at scale.
- Expert proficiency in Python and deep learning frameworks (PyTorch preferred, TensorFlow/JAX a plus).
- Strong track record of publishing in top-tier venues (NeurIPS, ICML, ICLR, CVPR) or equivalent open-source contributions.
- Deep understanding of distributed training, GPU optimization, and model compression techniques (quantization, distillation).
- Experience with MLOps tooling: Docker, Kubernetes, Airflow, MLflow, Weights & Biases.
- Excellent communication skills with ability to present complex technical concepts to diverse audiences.