Machine Learning Engineer

• 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.

• 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.

machine learning operations,experimentation frameworks,ml,data security practices,mlops,tensorflow,operations,models,deployment architectures,relational and non-relational databases,managing model servers,fine-tuning,model monitoring systems,scalability,model analysis,machine learning,mlflow,mlops practices,running large-scale training jobs,healthcare context,healthcare,notebooks,relational databases,numpy,w&b,pytorch,transformer-based models,linux environment,huggingface,scipy,python,non-relational databases,python code,pandas,data science tools,model monitoring,model servers,tfma,security protocols,nlp