Entry Level Machine Learning Engineer

This is a fully remote position, open to applicants in Canada.

📋 Description

• Construct end-to-end machine learning systems, transforming raw data into meaningful signals.

• Create data pipelines and train machine learning models.

• Implement machine learning models in a production environment.

• Launch generative AI applications.

• Tackle challenges such as ad personalization, search ranking, Voice AI, AI chatbots, advertiser retention and churn prevention, data-driven storytelling, clickstream analytics, content type classification, personalized business recommendations, and bot detection.

• Collaborate with software engineers, applied scientists, and product managers to identify and leverage relevant consumer and business data.

• Optimize for scale, latency, cost, and availability based on the problem at hand.

⛳️ Requirements

• Proven experience in developing and deploying machine learning models, including their associated data pipelines.

• Proficiency with machine learning frameworks such as TensorFlow, PyTorch, Spark MLlib, XGBoost, and Scikit-learn.

• Strong programming skills in Python or similar languages, including Java or C++.

• Familiarity with large language models (LLMs) such as Anthropic, OpenAI, and Google Gemini.

• Knowledge of agentic design concepts, such as LangGraph.

• Enthusiasm for designing large systems with scalable interfaces.

• Understanding of data pipelines for training and deploying machine learning models, as well as ETL pipelines for metrics, analytics, or product features.

• Experience with technologies like Apache Spark, AWS Redshift, AWS S3, Cassandra and other NoSQL databases, AWS Athena, Apache Kafka, Apache Flink, Java, AWS, and service-oriented architecture.

🏝️ Benefits

• Fully remote work option available throughout Canada.

• Yelp's five-star benefits package (specifics not detailed in the posting).

• Commitment to being an equal opportunity employer.

• Reasonable accommodations for individuals with disabilities during the job application process.