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Staff Machine Learning Engineer, Ads Foundational Representations
OtherMachine Learning EngineerStaff Machine Learning EngineerData
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Quick Summary
Key Responsibilities
driving designs & their review, establishing best practices in analysis, modeling and engineering, keeping the bar high.
Requirements Summary
7+ years of hands-on experience with the full lifecycle of designing, training, evaluating, testing, and deploying industry-level models.
Technical Tools
OtherMachine Learning EngineerStaff Machine Learning EngineerData
Responsibilities
~1 min read- →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.
Requirements
~1 min read- 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.
What We Offer
~2 min read✓Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
✓Family Planning Support
✓Gender-Affirming Care
✓Mental Health & Coaching Benefits
✓Group Personal Pension Scheme with Employer match
✓Private Medical and Dental Scheme
✓Income Replacement Programs
✓Bike to Work scheme
✓Flexible Vacation & Paid Volunteer Time Off
✓Generous Paid Parental Leave
Location & Eligibility
Where is the job
United Kingdom
Remote within one country
Who can apply
GB
Listing Details
- Posted
- June 19, 2026
- First seen
- June 20, 2026
- Last seen
- August 22, 2026
Posting Health
- Days active
- 0
- Repost count
- 0
- Trust Level
- 76%
- Scored at
- June 20, 2026
Signal breakdown
freshnesssource trustcontent trustemployer trust
Reddit
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"The front page of the internet,” Reddit brings over 430 million people together each month through their common interests, inviting them to share, vote, comment, and create across thousands of communities.
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