Staff Machine Learning Engineer, Ads Foundational Representations
New
R
RedditSocial Media Advertising
You can work remotely from anywhere in the UK or the Netherlands.Full-TimeStaff
Salary not disclosed
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Job Details
- Experience
- 7+ years
- Required Skills
- Machine LearningPyTorchTensorflowDeep LearningNLPComputer Vision
Requirements
- 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, including mentoring engineers and driving standards.
- Proven experience leading complex cross-functional projects from requirements through execution without direct people-management authority.
- Strong track record working on content-rich NLP/CV problems at scale using embeddings.
- Established data-driven approach for ML system development.
- Familiarity with the Ads domain, Search, or Recommender systems.
- Expertise in mainstream deep learning frameworks such as PyTorch or TensorFlow.
- Excellent verbal and written communication skills for translating technical concepts.
- Experience with Python, Airflow, BigQuery, Ray, Kubernetes, Kafka, and GCP (preferred).
- Hands-on experience with using, fine-tuning, or building LLMs (preferred).
Responsibilities
- Provide technical leadership and mentorship to MLEs in the team by driving designs, reviews, and best practices.
- Develop technical strategy for content-based embeddings and relevance for Ads in collaboration with leadership.
- Build and iterate on embedding models including aggregation pipelines, two-tower architectures, and sequence models.
- Leverage local and 3rd-party LLMs/VLMs to develop and fine-tune state-of-the-art embeddings.
- Build and maintain data processing and inference pipelines for developed models.
- Conduct qualitative and quantitative evaluations and lead end-to-end experimentation.
- Ensure system reliability, scalability, and performance through automated testing and monitoring.
- Collaborate with cross-functional teams to translate business requirements into technical solutions.
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