Staff Machine Learning Engineer, Ads Foundational Representations

• →Providing technical leadership and mentorship to MLEs in the team: driving designs & their review, establishing best practices in analysis, modeling and engineering, keeping the bar high. 
• →Working closely with team/org leadership developing technical strategy for content-based embeddings & relevance for Ads.
• →Developing new or iterating on existing embedding models for advertising use cases, ranging from aggregation pipelines to two-tower architectures and sequence models.  
• →Working with local and 3rd-party LLMs/VLMs: extract representations, develop evaluation methodologies, prompt tune and fine-tune large models to build state-of-the-art embeddings. 
• →Building data processing and inference pipelines for the models we develop. 
• →Qualitative and quantitative evaluation of the various features we develop, end-to-end experimentation from internal benchmarks to downstream recommender system offline metrics to online experiments. 
• →Ensuring the reliability, scalability, and performance of the ML systems by writing automated tests, monitoring performance, and implementing best practices for model management.
• →Participating in modeling and coding reviews: You will review work by other team members and provide feedback to ensure that it meets the team's standards for quality and performance.
• →Collaborating with cross-functional teams to understand business requirements and translate them into technical solutions.

• 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: from requirements, design to cross-team/functional alignment and execution without direct people-management authority. 
• 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. 
• Established data-driven approach for ML system development. Excitement about working with data and readiness to look behind the metric numbers. 
• Familiarity with the Ads domain and/or Search/Recommender systems.
• Experience with mainstream DL frameworks: PyTorch or TensorFlow.

• Experience with our stack (Python, Pytorch, Airflow, BigQuery, Ray, k8s, kafka, GCP)
• Tech leadership experience: mentoring junior engineers and leading complex projects. 
• Hands-on experience with using/fine-tuning/building LLMs.

This job posting may span more than one career level.

In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/.

To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below.