Reddit is hiring a Senior ML Engineer in Toronto!
Reddit is hiring a Senior Machine Learning Engineer for its Toronto office to build production ML systems at internet scale. The role sits within either the Consumer or Ads organisation, and the successful candidate will work end-to-end — from framing the problem and engineering features through training, evaluation, deployment and monitoring — on systems that shape how roughly 130 million daily visitors discover content, communities and advertising. Openings span a wide set of teams, including feed and notification relevance, search and answers relevance, ML understanding, and several ads-focused groups covering ranking, retrieval and targeting, measurement, marketplace quality, creative effectiveness and foundational representations. This is a hands-on engineering position with real influence over technical strategy and the long-term ML roadmap, suited to someone who enjoys complex applied ML problems and low-latency, high-throughput environments.
Key responsibilities
- Design, build and ship production-grade ML models and serving systems at scale
- Own the full model lifecycle, including problem definition, feature engineering, training, evaluation, deployment and monitoring
- Build reliable, observable data and model pipelines with automated retraining
- Apply large-scale datasets to improve ranking, recommendations, search relevance, prediction and user or advertiser understanding
- Partner with Product, Data Science, Infrastructure and Engineering teams to turn ambiguous business problems into ML solutions
- Tune latency, throughput and model quality metrics
- Research and apply current techniques such as deep learning, graph and transformer models, and LLM evaluation or alignment
- Contribute to architecture decisions, technical strategy and the ML roadmap
Key requirements
- 3-5+ years building, deploying and operating ML systems in production
- Strong programming in Python, Java, Go or similar, with solid software engineering fundamentals
- Grasp of classical statistical learning (XGBoost, random forests, regression) and deep learning architectures (transformers, CNNs, GNNs)
- Hands-on experience with PyTorch, TensorFlow or comparable frameworks
- Experience designing scalable ML pipelines, data processing and model serving infrastructure
- Ability to translate ambiguous product or business problems into technical solutions across teams
- Track record of improving measurable metrics through applied ML
- Preferred: recommender, search/ranking, advertising or auction systems experience; distributed data tooling such as Spark, Kafka, Ray, Airflow, BigQuery or Redis; real-time low-latency systems; LLM and generative AI work including fine-tuning, distillation, RAG or agentic systems; an advanced degree in computer science, ML or a related quantitative field
- Seniority: Senior
- Work mode: Not specified (Toronto-based role)
- Key skills: Python, Java, Go, PyTorch, TensorFlow, XGBoost, Transformers, GNNs, Spark, Kafka, Ray, Airflow, BigQuery, Redis, Recommender systems
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