Deskripsi Pekerjaan
At Nexus AI Labs, we are building the next generation of intelligent systems that redefine how businesses leverage data. We are seeking a Senior Machine Learning Engineer to join our core research and development team in San Francisco. In this high-impact role, you will architect, train, and deploy state-of-the-art models at scale, directly influencing product direction and business outcomes.
You will collaborate with a world-class team of researchers, engineers, and product leaders to solve complex, ambiguous problems in natural language processing, computer vision, and reinforcement learning. We value intellectual curiosity, engineering rigor, and a bias for action. If you are passionate about pushing the boundaries of ML in production environments, we want to hear from you.
What We Offer:
- Competitive base salary with significant equity upside (early-stage pre-IPO).
- Comprehensive health, dental, and vision benefits (100% employer-paid premiums).
- $3,000 annual learning & development stipend (conferences, courses, certifications).
- Flexible hybrid work policy (3 days onsite in our SoMa HQ, 2 days remote).
- Top-tier hardware budget (latest GPU workstations, cloud credits unlimited).
Tanggung Jawab
- Design, implement, and optimize end-to-end ML pipelines for large-scale training and low-latency inference.
- Lead the research and adoption of novel architectures (Transformers, Diffusion Models, LLMs) for production use cases.
- Collaborate with Product and Data Engineering to define feature stores, labeling strategies, and evaluation metrics.
- Build and maintain robust MLOps infrastructure (CI/CD for ML, model monitoring, automated retraining, A/B testing frameworks).
- Mentor junior engineers, conduct code reviews, and establish best practices for reproducible research and engineering excellence.
- Optimize model performance for latency, throughput, and cost-efficiency on GPU/TPU clusters (Kubernetes, Ray, Kubeflow).
- Publish findings internally and externally; represent Nexus AI at top-tier conferences (NeurIPS, ICML, CVPR).
- Drive cross-functional initiatives to democratize ML tooling across the organization.
Kualifikasi
- M.S. or Ph.D. in Computer Science, Machine Learning, Statistics, or equivalent practical experience.
- 5+ years of professional experience building and deploying ML models in production environments.
- Expert-level proficiency in Python and deep learning frameworks (PyTorch preferred, TensorFlow/JAX a plus).
- Proven track record of shipping large-scale models (Recommendation Systems, NLP/LLMs, Computer Vision, or Time Series).
- Deep understanding of MLOps tools: Docker, Kubernetes, Airflow/Prefect, MLflow/Weights & Biases, Feature Stores (Feast/Tecton).
- Strong software engineering fundamentals: data structures, algorithms, distributed systems, testing, and version control.
- Experience with cloud platforms (AWS/GCP/Azure) and distributed training (FSDP, DeepSpeed, Megatron-LM).
- Excellent communication skills; ability to translate complex technical concepts to non-technical stakeholders.