R
$230,000 – $322,000
Listed on Reddit’s own careers site. You apply with them directly — we never stand between you and the employer.
What this role is
Reddit is seeking a Staff Machine Learning Engineer to lead the development of large-scale ML systems powering recommendations, search, and content understanding across their consumer platform. This role suits experienced ML practitioners who enjoy building complex systems from research through production and want to influence product direction while mentoring other engineers.
Our summary, not Reddit’s wording. The full posting is on their site.
Skills this role names
- Apache Airflow
- Apache Kafka
- Google BigQuery
- Hugging Face Transformers
- Python
- PyTorch
- Redis
- SPARK
- TensorFlow
- V-Ray
Log in to see which of these are already on your profile.
What they ask for
Required
- 7+ years building, deploying, and operating production machine learning systems
- Deep knowledge of machine learning methods including classical approaches and modern deep learning (Transformers, GNNs, etc.)
- Expert-level experience productionizing models with TensorFlow, PyTorch, or Hugging Face Transformers
- Production-quality code skills in Python and Golang with testing, evaluation, and monitoring
- Experience designing and scaling ML systems including data pipelines, feature engineering, model training and serving, and production monitoring
- Strong communication and collaboration ability to discuss complex technical topics across teams and translate product needs into ML solutions
- Demonstrated track record of driving measurable impact through applied machine learning in real-world products
Nice to have
- Subject matter expertise in recommender systems, search systems (lexical and semantic retrieval and ranking), or content understanding (NLU/NLP/LLM, topic/taxonomy modeling, interest graphs, clustering, multimodal understanding)
- Familiarity with distributed systems and large-scale data processing frameworks (Spark, Kafka, Ray, Airflow, BigQuery, Redis)
- Experience with real-time systems and low-latency production environments
- LLM/GenAI experience including evaluation, alignment, fine-tuning, knowledge distillation, RAG/agentic systems, and productionizing LLM-powered products at scale
- Strong experimentation rigor with ability to formulate hypotheses, design learning plans, and build offline/online correlations
- Advanced degree in Computer Science, Machine Learning, or related quantitative field