As a Senior Machine Learning Engineer, you will play a central role in shaping the intelligence behind key platform experiences. You'll develop and maintain machine learning systems that directly influence how users discover content, interact with communities, and engage with AI-driven features at scale.
What You'll Do
- Lead the end-to-end development of machine learning models—from defining objectives and crafting features to training, evaluation, deployment, and ongoing monitoring.
- Design and implement scalable data and model pipelines with a focus on reliability, observability, and automated retraining cycles.
- Work with vast datasets to enhance search relevance, recommendation quality, user understanding, and content optimization.
- Collaborate with Product, Data Science, and Engineering teams to turn ambiguous business needs into effective technical solutions.
- Optimize systems for performance, balancing model accuracy with latency and throughput requirements.
- Explore and integrate cutting-edge techniques in deep learning, graph networks, transformers, and generative AI, including fine-tuning, retrieval-augmented generation, and alignment strategies.
- Help define the long-term technical direction for machine learning infrastructure and model strategy.
What We're Looking For
- 3-5+ years of hands-on experience deploying and maintaining ML systems in production environments.
- Strong programming background in Python, Java, Go, or similar languages, with solid software engineering practices.
- Deep understanding of machine learning fundamentals, including both classical algorithms (XGBoost, Random Forests) and modern deep learning architectures (Transformers, CNNs, GNNs).
- Proven experience with frameworks like PyTorch or TensorFlow and building scalable model pipelines.
- Ability to work across teams and convert high-level problems into actionable ML solutions.
- Track record of improving key metrics through applied machine learning.
Preferred Experience
- Background in recommender, search, ranking, or advertising systems.
- Familiarity with distributed computing and large-scale data tools such as Spark, Kafka, Ray, Airflow, or BigQuery.
- Experience with real-time, low-latency production systems.
- Work with feature engineering, model optimization, and monitoring in production.
- Hands-on work with LLMs, including evaluation, fine-tuning, knowledge distillation, or deploying generative AI products at scale.
- Advanced degree in Computer Science, Machine Learning, or a related quantitative field.
Technology Environment
Our stack includes Python, Java, Go, PyTorch, TensorFlow, Spark, Kafka, Ray, Airflow, BigQuery, Redis, XGBoost, Random Forests, and deep learning models including Transformers, CNNs, and GNNs.
Work Environment
This role supports remote work within the United States, offering flexibility while contributing to a globally connected team. We value diverse perspectives and are committed to building an inclusive workplace that reflects the communities we serve.
Benefits
- Comprehensive healthcare and income protection plans
- 401k with employer match
- Flexible vacation and paid time off for volunteering
- Generous parental leave
- Support for family planning and gender-affirming care
- Mental health resources and professional coaching
- Global benefits tailored to individual needs, including workspace setup and caregiving support
Compensation
Base salary range: $185,800 – $303,400 USD. Offers may include restricted stock units and, for certain roles, commission. Actual compensation is based on experience, location, and other factors.
Equal Opportunity
We are committed to a diverse, inclusive workplace and welcome applicants from all backgrounds. We provide reasonable accommodations for qualified individuals with disabilities throughout the hiring process.
