Senior Machine Learning Operations Engineer 76002

• Rapidly develop and deploy productionready ML models with a focus on scalability and monitoring across a broad range of applications within healthcare.
• Write efficient maintainable and scalable Python code tailored to our specific business needs.
• Build highperformance multitenant deployment architectures and sophisticated model monitoring systems.
• Directly engage with internal stakeholders to incorporate feedback and refine our MLdriven products through quick iteration cycles.
• Uphold stringent security protocols and processes in the deployment and maintenance of machine learning models.
• Drive the continuous advancement of MLOps practices within the healthcare industry by developing innovative solutions and advocating for best practices.
• Requirements:
• Minimum 3 years of experience with transformerbased models and NLP preferably in a healthcare context.
• Strong track record of finetuning running largescale training jobs and managing model servers like vLLM TGI or TorchServe.
• Proficiency in data science tools such as Pandas Notebooks Numpy Scipy.
• Experience with both relational and nonrelational databases.
• Extensive experience with TensorFlow or PyTorch and familiarity with HuggingFace.
• Knowledge of model analysis and experimentation frameworks such as MLFlow W&B
• and tfma is preferred.
• Comfortable with a Linux environment and stringent data security practices.
• Must pass a rigorous vetting process including extensive background checks to
• ensure the highest standards of data security and integrity.

pytorch,linux environment,nlp,python,healthcare,mlops,data security,machine learning,data science tools,scalability,huggingface,learning,transformer-based models,monitoring,operations,tensorflow