Senior ML Engineer — Production ML & MLOps

Moonshot Factory; Mountain View (CA); Sur place; USD 174 000 - 261 000; Plein temps

Avantages offerts par ce poste

Bonus program

Equity

Benefits

Résumé du poste

X, the Moonshot Factory in Mountain View, CA is seeking a hands-on Senior Machine Learning Engineer to build and deploy AI applications. You will prototype to productionize ML models, instrument observability, and drive scalable MLOps in production environments.

You will work across ML pipelines, design architectures, and manage GCP-based infra, collaborating to steer future development with agile methodology and cross‑functional partners.

Qualifications

• BS/MS in Computer Science or equivalent practical experience.
• 5+ years across ML development pipeline, including production.
• Strong experience with ML frameworks and Python libraries.
• Experience with Git, Dataflow, GCE and Vertex AI.
• Strong Python skills and production mindset.
• Hands-on troubleshooting, debugging, testing, monitoring.
• Agile-driven team with iterative delivery.
• Deep experience in MLOps: distributed training and monitoring.

Responsabilités

• Architect and prototype ML models and pipelines for production.
• Develop observability and explainability for deployed systems.
• Design ML pipeline architecture balancing speed and longevity.
• Manage Google Cloud Platform-based ML infrastructure.
• Collaborate to present findings and set future direction.

Connaissances

ML Production Experience

PyTorch/TensorFlow/JAX

Python

Git & Cloud Tools

Production Monitoring

Agile Methodologies

MLOps & Data lineage

Distributed Training

Geospatial / EO (bonus)

Formation

BS/MS Computer Science

Outils

Git

Apache Beam / Dataflow

Google Compute Engine

Vertex AI

Python (NumPy/SciPy/Pandas)

Description du poste

X, the Moonshot Factory in Mountain View, CA is seeking a hands-on Senior Machine Learning Engineer to build and deploy AI applications. You will prototype to productionize ML models, instrument observability, and drive scalable MLOps in production environments.

You will work across ML pipelines, design architectures, and manage GCP-based infra, collaborating to steer future development with agile methodology and cross‑functional partners.