Machine Learning Engineer (AI)

Location: Remote - United States

Salary: $216,700–$322,000 USD base salary per year, with potential equity and, depending on the position, commission.

Company

Reddit operates a large community platform where machine learning helps users discover and engage with conversations across more than 100,000 communities.

What you will do

• Build and improve large-scale machine learning systems for retrieval, ranking, embeddings, and LLM-powered features.
• Lead ML projects from concept through production and set technical direction with measurable user and business impact.
• Partner with Product, Data Science, Engineering, and other teams across recommendations, search, messaging, and AI systems.
• Evaluate new AI/ML approaches and support responsible LLM development, including retrieval and generation quality.
• Mentor engineers and contribute to long-term machine learning planning.

Requirements

• 4–12 years of experience building, deploying, and operating machine learning systems in production.
• Broad knowledge of machine learning fundamentals and experience applying them in production; expert-level modeling depth is not required.
• Experience developing and productionizing models with TensorFlow, PyTorch, or Hugging Face Transformers.
• Production-quality coding experience, including testing, evaluation, and monitoring; Python experience is required.
• Experience with data pipelines, feature engineering, model training and serving, and production monitoring.
• Strong communication and collaboration skills, with a record of delivering measurable product impact.

Nice to have

• Experience with recommendations, search, content understanding, or large-scale data and machine learning infrastructure.
• Experience with large-scale recommendation systems, foundational retriever models, RAG systems, retrieval methods, LLM evaluation, or production LLM features.
• Experience with agentic AI, including tool calls, MCPs, multi-agent systems, or orchestration.
• Experience with self-hosted open-weight models such as Qwen or Llama, prompt engineering, fine-tuning, post-training, or prompt optimization.
• Experience improving grounding and instruction following, reducing hallucinations, and evaluating retrieval and generation quality.
• Experience scaling LLM systems through latency optimization, caching, and cost management, with safety measures for prompt injection and unsafe inputs.
• Experience defining product success metrics, feedback loops, and evaluation approaches, including human review.
• Golang experience.

Culture & Benefits

• Comprehensive healthcare benefits and income replacement programs.
• 401(k) with employer match and global benefits supporting workspace, professional development, and caregiving.
• Family planning support, gender-affirming care, and mental health and coaching benefits.
• Flexible vacation, paid volunteer time off, and generous paid parental leave.
• Interviews may be recorded, transcribed, and summarized by AI; candidates can opt out before scheduled interviews.

Hiring process

• Depending on the role and location, interviews may be recorded, transcribed, and summarized by artificial intelligence.
• Recording, transcription, and summarization can be declined before the interview.