Staff Machine Learning Engineer - Ads Targeting

reddit; Canada; Hybrid; CAD 120,000 - 160,000; Full time

Job summary

A leading social media platform is seeking a Staff Machine Learning Engineer to join their Ads Targeting team. In this role, you will drive the end-to-end design and execution of machine learning-based targeting products and collaborate closely with cross-functional teams. The ideal candidate will have extensive experience in applied ML, particularly in ads retrieval modeling and deep learning frameworks like Tensorflow and PyTorch. Competitive benefits include comprehensive health coverage and flexible vacation policies.

Benefits

Comprehensive Health benefits

Retirement Savings plan

Workspace benefits for home office

Professional development funds

Family Planning Support

Flexible Vacation

Qualifications

• Tech lead experience in product ML team driving research direction.
• Experience with ads retrieval modeling and recommendation systems.
• End-to-end experience of training and deploying ML models.

Responsibilities

• Own end-to-end design of ML-based targeting products.
• Drive research direction for complex projects.
• Provide mentorship to junior ML engineers.

Skills

Applied ML

Deep learning

Tensorflow/Pytorch

Data processing

Cross-functional collaboration

Tools

Spark

Dataflow

Kubeflow

Airflow

BigQuery

Job description

Reddit is a community of communities. It’s built on shared interests, passion, and trust and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about.

Reddit has a flexible first workforce! If you happen to live close to one of our physical office locations our doors are open for you to come into the office as often as you'd like. Don't live near one of our offices? No worries: You can apply to work remotely from the United States or Canada.

Ads Targeting ML engineers are focused on designing and implementing ML systems and solutions for improving targeting products. The team’s projects involve building large‑scale offline & online retrieval systems across several dimensions to improve contextual & behavioral targeting for targeting products.

As a staff machine learning engineer in the ads targeting quality team, you will own and execute our mission to automate targeting and deliver the most relevant audiences to advertisers under the right context with ML‑driven solutions.

Your Responsibilities

• Own end-to-end design and execution of ML-based targeting products like auto targeting, user lookalikes, etc.
• Drive research direction and technical roadmap for complex projects, lead day‑to‑day project execution, and contribute meaningfully to team vision and strategy
• Be a thought leader for the team and collaborate closely with product managers and cross‑functional partners to develop and prioritize the roadmap based on data analysis, industry research and product research
• Research, implement, test, and launch new model architectures for retrieval using deep learning (GNNs, transformers, two‑tower models, LLMs) with a focus on improving advertiser outcomes
• Provide mentorship to junior MLEs
• Own offline & online experimentation of ML models for improving targeting products
• Work on large scale data systems, and product integration
• Collaborate closely with multiple stakeholders cross product, engineering, research and marketing

Required Qualifications

• Tech lead experience in a product ML team driving the research and technical direction to improve business outcomes using applied ML
• Experience with ads retrieval modeling, ranking or recommendation systems
• Experience with deep learning models for retrieval (two‑tower, GNNs, transformers, LLMs)
• + years of end-to-end experience of training, evaluating, testing, and deploying machine learning models
• + years of experience building machine learning models with Tensorflow/Pytorch
• Experience with large scale data processing & pipeline orchestration tools like Spark, Dataflow, Kubeflow, Airflow, BigQuery
• Experience working with nearest‑neighbor search systems is a big plus
• Experience working with cross functional stakeholders across research, product & infrastructure to productize ML research
• Experience with deep learning, representation learning or transfer learning is preferred
• Tech lead experience in a product team is strongly preferred

Benefits

• Comprehensive Health benefits
• Retirement Savings plan with matching contributions
• Workspace benefits for your home office
• Personal & Professional development funds
• Family Planning Support
• Flexible Vacation & Reddit Global Days Off