Senior Machine Learning Operations Engineer 20067

Introduction: 

As a Senior Machine Learning Operations (MLOps) Engineer, you will be instrumental in deploying robust, scalable machine learning solutions. You will ensure these are tailored to meet the expansive needs of a client in healthcare services. This role demands a high level of proficiency in machine learning technologies and programming, coupled with rigorous vetting processes to maintain the highest standards of data integrity and security.

Key Responsibilities:

1. Rapidly develop and deploy production-ready ML models, with a focus on scalability and monitoring
   across a broad range of applications within healthcare.
2. Write efficient, maintainable, and scalable Python code tailored to our specific business needs.
   Build high-performance, multi-tenant deployment architectures and sophisticated model monitoring
   systems.
3. Directly engage with internal stakeholders to incorporate feedback and refine our ML-driven products
   through quick iteration cycles.
4. Uphold stringent security protocols and processes in the deployment and maintenance of machine
   learning models.
5. Drive the continuous advancement of MLOps practices within the healthcare industry by developing
   innovative solutions and advocating for best practices.

Requirements:

1. Minimum 3 years of experience with transformer-based models and NLP, preferably in a healthcare context.
2. Strong track record of fine-tuning, running large-scale training jobs, and managing model servers like vLLM, TGI, or TorchServe.
3. Proficiency in data science tools such as Pandas, Notebooks, Numpy, Scipy.
4. Experience with both relational and non-relational databases.
5. Extensive experience with TensorFlow or PyTorch, and familiarity with HuggingFace.
6. Knowledge of model analysis and experimentation frameworks such as MLFlow, W&B, and tfma is preferred.
7. Comfortable with a Linux environment and stringent data security practices.
8. Must pass a rigorous vetting process, including extensive background checks to ensure the highest standards of data security and integrity.
9. Minimum 3 years of experience with transformer-based models and NLP, preferably in a healthcare context.
10. Strong track record of fine-tuning, running large-scale training jobs, and managing model servers like vLLM, TGI, or TorchServe.
11. Proficiency in data science tools such as Pandas, Notebooks, Numpy, Scipy.
12. Strong proficiency in spoken and written English language.

Notice Period: 2-4 weeks