Careem - Senior AI Engineer II
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Requirements
• 4-6 years of experience in machine learning, software engineering, Big Data methodologies, transformation, and cleaning of both structured and unstructured data. • Advanced degree in a quantitative discipline such as Physics, Statistics, Mathematics, Engineerin,g or Computer Science. • Strong understanding of transformer architectures, attention mechanisms, and recent advancements in Large Language Models (LLMs) • Experience with advanced prompting techniques, including Chain of Thought (CoT) prompting, in-context learning, and few-shot learning. • Proficiency in using LangChain and LangChain Expression Language (LCEL) for building complex pipelines and workflows with LLMs. • Experience in developing observable LLM-powered compound systems through tracing to monitor performance and behavior in production environments. • Experience with one of the following machine learning frameworks: PyTorch or TensorFlow. • Knowledge of distributed training frameworks (e.g., DeepSpeed, Megatron-LM) and optimizing model performance using techniques like mixed-precision training, gradient checkpointing, and model parallelism would be advantageous. • Experience with sequence-to-sequence models, self-supervised learning techniques, and understanding NLP concepts such as tokenization, parsing, and semantic analysis. • Proficiency in creating scalable and maintainable APIs using FastAPI or similar frameworks. • Strong understanding of good software engineering practices, including code versioning (e.g., Git), CI/CD pipelines, and automated testing. • Experience with both SQL and NoSQL databases for managing training data and model artifacts. • Proficiency in Python, SQL, and familiarity with data processing frameworks like Spark and Hive. • Knowledge of classic ML and DL
Responsibilities
• Collaborate in building a long-term vision of how we can rethink GenAI at Careem • Drive exploratory analysis to understand the ecosystem and user behavior; identify new levers to help move metrics and build models of user behaviors for analysis and product enhancements using GenAI • Shape and influence models and instrumentation to optimize the product experience and generate insights on new areas of opportunity and new products. • Provide product leadership by sharing data-based recommendations to communicate the state of business, the root cause of change in metrics, and experimentation results, influencing product and business decisions • Implement a scalable machine learning GenAI solution that will be used in production on big data. • Design and run randomized controlled experiments, analyze the resulting data, and communicate results with other teams. • You will always challenge the status quo and continually investigate new data processing technologies and seek to ensure that we follow the industry best practices. • Build and deploy retrieval augmented generation systems and other applications of large language models. • Collaborate with cross-functional teams, including data scientists, product managers, and domain experts, to deliver AI-driven solutions.
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