Software Development Engineer II - Machine Learning Models

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 :

- 3-6 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, Node.js .

- 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.