Senior Machine Learning Operations Engineer
Experience: 6 18 Years
Location: Permanent Remote
MustHave:
Minimum 4 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.
Strong proficiency in spoken and written English language.
Budget: 2540 LPA
Type of employment: FTE
Job Summary:
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:
- 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.
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