Remote opportunity at
Reddit, Inc.Staff Machine Learning Engineer, Retrieval & Targeting
Reddit, Inc. operates a prominent online platform that connects over 130 million daily active unique visitors through more than 100,000 active communities built around shared interests…
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About This Role
Reddit, Inc. operates a prominent online platform that connects over 130 million daily active unique visitors through more than 100,000 active communities built around shared interests and authentic discussions. The organization is seeking a Staff Machine Learning Engineer to guide the technical direction of the Retrieval and Targeting Machine Learning team. This applied role focuses on building candidate-generation and retrieval models that determine ad eligibility before downstream ranking and auction…
Job Description
Reddit, Inc. operates a prominent online platform that connects over 130 million daily active unique visitors through more than 100,000 active communities built around shared interests and authentic discussions. The organization is seeking a Staff Machine Learning Engineer to guide the technical direction of the Retrieval and Targeting Machine Learning team. This applied role focuses on building candidate-generation and retrieval models that determine ad eligibility before downstream ranking and auction decisions across multiple placements and geographies.
The person in this position will shape multi-year roadmaps, design advanced deep learning architectures, optimize vector retrieval systems, and establish rigorous offline and online experimentation practices. This role suits technical leaders who can stay close to everyday implementation details while mentoring other engineers, collaborating with product and data science stakeholders, and connecting retrieval metrics directly to user and business outcomes.
Responsibilities
- Establish the multi-year technical roadmap and strategy for ads retrieval modeling alongside engineering, product, and data science partners
- Architect and launch candidate-generation and retrieval models across various advertising surfaces
- Utilize advanced deep learning frameworks such as representation learning, two-tower models, sequence networks, and graph-based approaches
- Refine the retrieval pipeline by optimizing objectives, negative sampling strategies, feature engineering, and filtering thresholds
- Handle approximate nearest-neighbor and vector retrieval systems while balancing recall, relevance, latency, coverage, and infrastructure costs
- Design and analyze offline evaluations and online experiments to drive subsequent modeling improvements
- Collaborate with downstream ranking, ads platform, auction, and product teams to integrate models into the broader ecosystem
- Produce design specifications, perform code and model reviews, and elevate production quality standards
- Provide mentorship to machine learning engineers to strengthen team expertise in recommendation and representation learning
Requirements
- Seven or more years of professional industry experience building and deploying applied machine learning products
- Substantial background in information retrieval, recommendation systems, candidate generation, or relevance ranking
- Proficiency with deep learning models, embeddings, dual-encoder structures, and approximate nearest-neighbor search methods
- Practical expertise training, debugging, and launching deep learning models via frameworks like TensorFlow or PyTorch
- Proven track record of taking machine learning projects from problem scoping through production release
- Familiarity with experimental design and connecting offline metrics to downstream business outcomes
- Experience handling large-scale behavioral, contextual, or content datasets and feature pipelines
- Solid software engineering capabilities to author reliable production code
- Demonstrated technical leadership in guiding complex projects and mentoring peers
- Effective written and verbal communication skills for technical and non-technical audiences
Qualifications
- Prior work in ads retrieval, ranking, targeting, serving, recommendation, or search relevance
- Background modeling user, content, or campaign interactions using sequential, multimodal, or graph signals
- Familiarity connecting retrieval updates to downstream auction, conversion, or revenue metrics
- Experience operating within ads marketplaces at peer companies
- Documented industry contributions, patents, or publications in applied machine learning or ranking
- Prior exposure to sequential modeling architectures including Transformers and RNNs
Core Skills
Benefits
- Comprehensive healthcare coverage and income replacement options
- Employer-matched 401(k) program
- Global lifestyle programs supporting workspaces, professional growth, and caregiving
- Family planning assistance and gender-affirming care
- Mental health resources and coaching programs
- Flexible vacation time and paid volunteer leave
- Extended paid parental leave
- Equity compensation in the form of restricted stock units
Frequently Asked Questions
Answers are based only on the employer’s listing; where it doesn’t say, neither do we.
What is the location and remote work policy for this role?
This position is 100 percent remote, though the employer maintains office locations in New York, San Francisco, Los Angeles, and Chicago for hybrid or on-site preferences.
What is the salary range for the Staff Machine Learning Engineer position?
The annual base salary ranges from $230,000 to $322,000, and the position is also eligible to receive equity in the form of restricted stock units.
What level of experience is required to apply?
Applicants must have 7 or more years of industry experience, including substantial hands-on work building and shipping applied machine learning products and technical leadership.
What employment type is this opening?
The posting specifies that this is a full-time employment opportunity.
Sample Interview Questions
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