Machine Learning Engineer

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.

• 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

• 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, Tensor Flow, 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