Staff ML Engineer: Ads Embeddings & Relevance Leader

Promptcube3; United Kingdom; Remote; GBP 110,000 - 170,000; Full time

Benefits offered by this job

Global Benefits Programs

Parental Leave

Private Pension plan

Flexible Vacation

Job summary

Reddit is hiring a Staff ML Engineer to lead cross-functional ML projects focused on content embeddings and relevance for Ads. You will manage end-to-end efforts from requirements to engineering execution, mentoring engineers and raising standards.

You will collaborate with product and data science to develop state-of-the-art embeddings, build data processing and inference pipelines, and ensure reliable, scalable ML systems with automated tests and monitoring.

Qualifications

• 7+ years of hands-on experience with the full lifecycle of designing, training, evaluating, testing, and deploying industry-level models.
• Demonstrated Staff-level technical leadership: mentoring engineers, driving standards and bar raising, leading complex cross-functional projects.
• Excellent communication skills, with the ability to translate complex technical concepts to different audiences, both verbally and in writing.
• Strong track record of working on content rich NLP/CV problems at scale, and using embeddings as a tool to solve them.
• Experience with data-driven ML system development and familiarity with Ads domains.

Responsibilities

• Provide technical leadership and mentorship to ML engineers and review designs, promoting best practices.
• Develop and iterate embedding models for advertising use cases, from pipelines to two-tower architectures and sequence models.
• Work with LLMs/VLMs: extract representations, evaluate methodologies, prompt tune and fine-tune large models.

Skills

Staff-level leadership

ML engineering

PyTorch

TensorFlow

NLP embeddings

Distributed systems

Communication skills

Tools

Python

Airflow

BigQuery

Ray

Kubernetes

Job description

Reddit is hiring a Staff ML Engineer to lead cross-functional ML projects focused on content embeddings and relevance for Ads. You will manage end-to-end efforts from requirements to engineering execution, mentoring engineers and raising standards.

You will collaborate with product and data science to develop state-of-the-art embeddings, build data processing and inference pipelines, and ensure reliable, scalable ML systems with automated tests and monitoring.