ML Engineer

Must Have

• 4+ years of software or machine-learning engineering experience, including hands-on experience deploying models to production.
• Demonstrated track record operationalizing models developed by data scientists into reliable, scalable, and observable production systems.
• Production experience with classical machine-learning workloads — distinct from generative-AI application development.
• Strong collaboration skills across data science, software engineering, and platform teams.
• Commitment to building reliable, well-engineered, and maintainable systems.

Nice to Have

• Experience with feature stores and large-scale or streaming data pipelines.
• Knowledge of infrastructure-as-code (e.g., Terraform) and cloud cost optimization.
• Experience with workflow orchestration tools (e.g., Apache Airflow).
• Familiarity with model-serving frameworks and API design for inference.
• Light exposure to generative-AI or LLM deployment.
• Experience operating systems in a regulated or enterprise environment.
• Cloud or MLOps certifications.