Machine Learning Engineer (AI)

Location: Remote - Ontario, Canada

Company

Reddit operates a large-scale platform built around communities, personalized content discovery, advertising, and user engagement.

What you will do

• Design, build, deploy, and operate production machine learning models and systems at scale.
• Own the full ML lifecycle, including problem definition, feature engineering, training, evaluation, deployment, monitoring, and automated retraining.
• Build scalable data pipelines, model-serving infrastructure, and real-time decision systems with strong reliability and observability.
• Improve recommendations, search and ranking relevance, advertising optimization, content and user understanding, and prediction systems.
• Collaborate with Product, Data Science, Infrastructure, and Engineering teams to translate complex problems into technical solutions.
• Contribute to ML architecture, technical strategy, and the long-term roadmap while applying deep learning, graph models, transformers, and LLM techniques.

Requirements

• 3–5+ years of experience building, deploying, and operating machine learning systems in production.
• Strong programming skills in Python, Java, Go, or similar languages, with solid software engineering fundamentals.
• Strong knowledge of statistical learning and deep learning architectures, including XGBoost, Random Forests, regressions, Transformers, CNNs, and GNNs.
• Hands-on experience with modern ML frameworks such as PyTorch or TensorFlow.
• Experience designing scalable ML pipelines, data processing systems, and model-serving infrastructure.
• Ability to work cross-functionally and improve measurable product or business metrics through applied machine learning.

Nice to have

• Experience with recommender systems, search and ranking, advertising or auction systems, representation learning, or multimodal embeddings.
• Familiarity with distributed systems and large-scale data processing tools such as Spark, Kafka, Ray, Airflow, BigQuery, or Redis.
• Experience with real-time, low-latency systems, feature engineering, model optimization, and production monitoring.
• Experience with LLM and generative AI techniques, including evaluation, alignment, fine-tuning, knowledge distillation, RAG, agentic systems, and production LLM applications.
• Advanced degree in Computer Science, Machine Learning, or a related quantitative field.

Culture & Benefits

• Comprehensive healthcare benefits and income replacement programs.
• 401(k) with employer match.
• Global benefits supporting workspace needs, professional development, caregiving, and family planning.
• Gender-affirming care and mental health and coaching benefits.
• Flexible vacation, paid volunteer time off, and generous paid parental leave.

Hiring process

• In select roles and locations, interviews may be recorded, transcribed, and summarized by AI.
• Candidates can opt out of interview recording, transcription, and summarization before scheduled interviews.