# Senior Machine Learning Infrastructure Engineer, Embedding Platform

**Company:** [Reddit](https://hotfix.jobs/companies/reddit)
**Location:** Remote
**Role:** ML Engineering
**Salary:** $191k – $267k/yr
**Experience:** 5+ years
**Skills:** Python, PyTorch, TensorFlow, Deep Learning, sequence modeling, Foundation Models, machine learning platforms, Distributed Training, distributed inference, model parallelism, pipeline parallelism, A/B Testing, online inference, Model Evaluation
**Posted:** 2026-08-12

> Build and operate large-scale machine learning infrastructure and models for Reddit’s recommendation and personalization systems. The role requires 5+ years of ML engineering experience, expertise in deep learning and distributed systems, and proficiency with Python and modern ML frameworks.

## Job Description

## Responsibilities
- Design, train, and improve large-scale machine learning platforms for recommendation or personalization systems.
- Own and deliver major ML system components end to end, from problem framing through production rollout.
- Build and optimize end-to-end ML pipelines spanning data preparation, feature generation, training, evaluation, and deployment.
- Improve distributed training, model efficiency, and online inference performance.
- Apply modern modeling approaches, including sequence modeling and related foundation-model techniques, to Reddit use cases.
- Develop reliable serving and monitoring patterns for low-latency, high-throughput production ML systems.
- Work with cross-functional partners across product, relevance, ads, and core ML teams to deliver measurable improvements in user experience and business impact.
- Drive rigorous offline and online evaluation, including experimentation, model diagnostics, and feedback-loop improvement.
- Contribute to engineering quality through strong code, design reviews, documentation, and operational excellence.

## Requirements
- 5+ years of experience in machine learning engineering, with a strong focus on large-scale ML infrastructure and recommendation or personalization systems.
- Expertise in modern deep learning architectures, including sequence models and foundation models.
- Experience building or scaling ML platforms for large datasets and high-traffic production environments.
- Ability to independently scope and execute ambiguous technical work while owning high-quality implementation details.
- Strong understanding of distributed training and inference concepts, including data parallelism, model parallelism, and pipeline parallelism.
- Proficiency in Python and modern ML frameworks such as PyTorch or TensorFlow.
- Strong software engineering fundamentals, including system design, debugging, testing, and performance optimization.
- Experience with A/B testing, model evaluation frameworks, and real-time feedback loops in large-scale production systems.
- Excellent communication skills, with the ability to present complex ML concepts to technical and non-technical stakeholders.

## Compensation and Benefits
- Base salary range: **$190,800–$267,100 USD**.
- Eligible for equity in the form of restricted stock units; some positions may also be eligible for commission.
- Comprehensive healthcare benefits and income replacement programs.
- 401(k) with employer match.
- Global benefits supporting workspace, professional development, caregiving, and family planning.
- Gender-affirming care.
- Mental health and coaching benefits.
- Flexible vacation and paid volunteer time off.
- Generous paid parental leave.

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