Machine Learning Engineer

ERAGON

San Francisco, California, United States

San Francisco, California, United States

Über

Job Description We’re looking for a Machine Learning Engineer to build and deploy production-grade AI systems. In this role, you’ll take models from research to real-world applications, designing, optimizing, and scaling systems that power critical workflows across the enterprise.
You’ll work closely with research, product, and engineering teams to turn cutting‑edge capabilities into reliable, high‑performance systems in production.
Key Responsibilities
Model Development & Deployment: Build, fine‑tune, and deploy machine learning models into production environments
Systems Engineering: Design scalable pipelines for training, inference, evaluation, and monitoring
Performance Optimization: Improve latency, throughput, cost efficiency, and reliability of ML systems
Data & Infrastructure: Work with large‑scale datasets and integrate models with internal systems and APIs
Cross‑Functional Collaboration: Partner with product and engineering teams to deliver end‑to‑end AI features
Evaluation & Monitoring: Implement robust evaluation frameworks, observability, and feedback loops
Minimum Qualifications
Education: Bachelor’s or Master’s in Computer Science, Engineering, or related field (PhD optional, not required)
Technical Skills: Strong proficiency in Python and modern ML frameworks (e.g., PyTorch, TensorFlow, JAX)
Production Experience: Experience deploying and maintaining ML systems in production environments
Systems Knowledge: Familiarity with distributed systems, data pipelines, and cloud infrastructure (e.g., AWS, GCP)
Practical ML Expertise: Experience with model training, fine‑tuning, evaluation, and iteration at scale
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San Francisco, California, United States

Sprachkenntnisse

English

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