Software Development Engineer II
7 days ago
Description :
As an SDE II - Machine Learning, you will be a core contributor in designing, building, and scaling ML-driven systems that power our real-time ad platforms. You'll be responsible for full-stack ML development from data engineering and model development to scalable deployment, working closely with product, data science, and engineering teams.
Responsibilities :
- Build and deploy machine learning models for ranking, bid optimization, and click-through rate prediction.
- Design scalable and fault-tolerant data pipelines and services that serve real-time and batch ML workloads.
- Work with large volumes of structured and unstructured data to extract meaningful patterns.
- Collaborate with data scientists to convert prototypes into production-ready systems.
- Build systems to intelligently target ads and content by combining contextual and behavioral signals.
- Use LLM learning to improve ad relevance, page understanding, and user targeting.
- Continuously experiment and optimize models based on user feedback and system performance.
Some Interesting Challenges You'll Solve :
- Predicting CTRs and revenue across millions of unique URLs and topics in real-time.
- Solving cold-start problems with sparse data using explore-exploit frameworks.
- Matching contextual and behavioral data for enhanced user targeting.
- Designing real-time bidding systems that optimize for revenue and win rate.
- Leveraging LLMs/NLP to extract intent and context from web content.
Requirments :
years of hands-on experience in software development and ML engineering.
- Strong programming and debugging skills, preferably in Python and Java.
- Experience building and deploying ML models in production environments.
- Solid understanding of ML algorithms (e. g., decision trees, gradient boosting, deep learning).
- Hands-on experience with large-scale data processing tools (e. g., Spark, Hadoop).
- Ability to design low-latency, high-throughput systems.
- Strong problem-solving and analytical skills.
Tech Stack :
- Languages: Python, Java, .
- ML/Big Data: Apache Spark, Hadoop, TensorFlow/PyTorch, Kafka.
- Databases: SQL, MongoDB, Redis, and Elasticsearch.
- Cloud: GCP or similar.
Bonus Points :
- Prior experience with ad tech, recommender systems, or real-time bidding.
- Publications or contributions to ML research or open-source projects.
- Experience with NLP, LLMs, or Information Retrieval.
- Exposure to auction theory or game-theoretic modeling.
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