Senior Machine Learning Engineer at Bumble developing scalable AI systems for personalized user interactions. Leading machine learning model development and deployment from exploration to production.
About the role
- Staff Machine-Learning Infrastructure Engineer developing ML infrastructure for Voxel, enhancing workplace safety through AI and computer vision technology.
Responsibilities
- Own data & labeling pipelines – architect scalable labeling services (storage, query, retrieval), design ontologies, automate annotation workflows, and build quality-tiered datasets that stay within cost constraints.
- Build and operate training infrastructure – create multi-GPU / multi-node training frameworks (Ray, Spark, Kubernetes), optimize distributed jobs, and integrate accelerators (TensorRT, CUDA-graph, FP8, etc.).
- Manage the full model lifecycle – stand up model registries, version control, evaluation suites, and continuous-learning loops that push updates from dev → staging → prod with zero-downtime rollbacks.
- Provide technical leadership, mentorship, and lightweight project management to a small infra + research squad.
- Establish DevOps-for-ML best practices (IaC, CI/CD, observability, cost monitoring) so researchers can iterate quickly and safely.
- Partner with ML engineers on architecture decisions, from data schemas to inference optimizations, ensuring infra and research road-maps stay tightly aligned.
Requirements
- Bachelor’s (or higher) in Computer Science, EE, or related field.
- 5+ years building and operating large-scale infrastructure, with at least 3 years focused on ML or data-intensive systems.
- Proven record designing highly available, distributed systems on Kubernetes (EKS, GKE, or on-prem).
- Deep expertise with orchestration (K8s operators, Argo, Kubeflow), and cluster-scale storage / compute (S3, GCS, Ray, Spark, Dask).
- Hands-on experience automating data-labeling or ground-truth workflows and maintaining dataset versioning.
- Strong software-engineering fundamentals; familiar with best practices for testing, observability, and secure coding.
- Demonstrated DevOps mindset — IaC (Terraform/CDK), CI/CD (GitHub Actions, ArgoCD), metrics & alerting (Prometheus/Grafana).
Benefits
- Extensive / Generous health, dental, and vision insurance.
- Highly competitive paid parental leave and support system.
- Ownership in the business through an Equity Incentive Plan.
- Generous paid time off and / or flexible work arrangements.
- Daily meals in-office, vibrant company events, team-building.
- 401K retirement plan, HSA options, pre-tax Commuter Card.
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