Senior Machine Learning Engineer

Há 6 horas

são paulo, Brasil IT Cardinal Partners LLC Tempo inteiro

Machine Learning Engineer, AI Translation Location: REMOTE from Brazil (must) Duration: 12+ months About the Role: As a ML Engineer on the Translation AI team, you will play a critical role in accelerating the development and deployment of Translation AI. Machine Translation is critical to team objectives, as we operate on a global scale and in the travel domain it is critical to ensure our guests and hosts can communicate across languages effectively. A Typical Day: Collaborate closely with teams across the company—such as Customer Support to deliver powerful machine translation capabilities for the entire company. Partners with teams to help identify and prioritize translation-related challenges and opportunities. Design and implement scalable machine translation models to improve accuracy and reduce cost and latency for the global platform. Develop tooling, pipelines, and low-level infrastructure (in collaboration with the ML Infrastructure team) that ensures we have a flexible foundation for machine translation spanning data preparation, evaluation, model selection / training, and inference. Work with cutting-edge open-source models including Llama, as well as commercial Translation offerings. Must Have: 9+ years of industry experience in applied Machine Learning, inclusive MS or PhD in relevant fields. Strong programming (Scala / Python / Java / C++ or equivalent) and data engineering skills. Deep familiarity with machine learning development practices, especially for language modeling & NLP applications. Prior experience with deploying or supporting production ML systems at large scale - including operational experience on observability, continuous evaluation and improvement, progressive rollouts. Familiarity with OSS tools and technologies such as: PyTorch, LlamaFactory, HuggingFace, NVidia Triton / TRTLLM, Ray. Passionate about GenAI with a strong grasp of current trends in LLMs and related technologies. Deep understanding of GenAI models and their strengths/weaknesses, and ability to define the criteria for the right models/technologies to use to balance tradeoffs between quality, cost, performance, ease of operation and extensibility. Strong communication and cross-team collaboration skills. You may currently hold titles such as ML Engineer, Applied Scientist, or Data Scientist.

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