eightfold
Senior Backend Engineering Manager, Recommendations
Match Group
New York City, USA
Full-time
Senior · 8+ years experience
Onsite
USD 219000-263000 yearly / year
Discovered 1 weeks ago
GoKafkaSparkElasticSearchTensorFlowPyTorch
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GoKafkaSpark
Key Skills for This Role
GoKafkaSparkElasticSearchTensorFlowPyTorch
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- Lead, mentor, and grow a team of 6-8 engineers building recommendation services
- Partner with ML to productionize recommendation models and ensure low-latency, high-availability serving infrastructure
- Own the technical roadmap for the recommender platform, balancing new capabilities with reliability and performance improvements
- Drive architecture decisions for recommendation and search infrastructure
- Establish and maintain engineering standards for code quality, testing, observability, and incident response
- Collaborate with Product, Design, and cross-functional engineering teams to define and deliver product-facing recommendation features
- Manage hiring, performance reviews, career development, and team culture
- 8+ years of software engineering experience, with 4+ years in an engineering management role
- Strong backend systems expertise – you've built or operated large-scale distributed systems in production
- Experience with recommendation systems, search ranking, personalization, or adjacent ML-serving infrastructure
- Proficiency in one or more backend languages (ideally Go)
- Familiarity with data processing architectures, feature stores, and model-serving technologies (e.g., Kafka, Spark, ElasticSearch, etc)
- Track record of hiring, developing, and retaining high-performing engineering teams
- Ability to communicate technical trade-offs clearly to both engineers and non-technical stakeholders
- Experience with ML frameworks (TensorFlow, PyTorch) or MLOps tooling (MLflow, Kubeflow, Airflow)
- Hands-on experience with cloud infrastructure (AWS, GCP, or Azure) and container orchestration (Kubernetes)
- Background in A/B testing and experimentation platforms
- Prior work at scale (millions of daily active users or equivalent throughput)
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