It starts with you – ML Engineering Team Lead responsible for leading a team delivering end-to-end ML systems. This role combines people management with ownership of model training, evaluation, deployment, and ML platform standards
If you want to grow your skills building AI products for mission-critical AI, join our companys mission – this role is for you.
The Responsibilities
Lead and mentor ML Engineers delivering production ML systems.
Own technical direction for model architectures, training pipelines, and evals.
Review designs and code; ensure scalability, reliability, and data quality.
Define standards for experimentation, reproducibility, and monitoring.
Partner with product and platform teams on roadmap and prioritization.
Balance hands-on technical contribution with people management.
Build a culture of measurement, rigor, and continuous improvement.
If you want to grow your skills building AI products for mission-critical AI, join our companys mission – this role is for you.
The Responsibilities
Lead and mentor ML Engineers delivering production ML systems.
Own technical direction for model architectures, training pipelines, and evals.
Review designs and code; ensure scalability, reliability, and data quality.
Define standards for experimentation, reproducibility, and monitoring.
Partner with product and platform teams on roadmap and prioritization.
Balance hands-on technical contribution with people management.
Build a culture of measurement, rigor, and continuous improvement.
Requirements:
6+ years software engineering experience with 4+ years applied ML.
Prior experience as a technical lead or engineering manager.
Deep understanding of ML training, evaluation, and deployment lifecycles.
Strong experience with ML frameworks and large-scale data pipelines.
Proven ownership of ML evals, monitoring, and drift detection in production.
Experience with distributed training and performance optimization.
Strong experience with feature stores, model registries, and experiment tracking.
Experience deploying and operating ML systems on Kubernetes or similar platforms.
Strong Python background and system architecture expertise.
Experience managing cross-functional ML initiatives and stakeholders.
6+ years software engineering experience with 4+ years applied ML.
Prior experience as a technical lead or engineering manager.
Deep understanding of ML training, evaluation, and deployment lifecycles.
Strong experience with ML frameworks and large-scale data pipelines.
Proven ownership of ML evals, monitoring, and drift detection in production.
Experience with distributed training and performance optimization.
Strong experience with feature stores, model registries, and experiment tracking.
Experience deploying and operating ML systems on Kubernetes or similar platforms.
Strong Python background and system architecture expertise.
Experience managing cross-functional ML initiatives and stakeholders.
This position is open to all candidates.
