Senior Machine Learning Operations Engineer

1 month ago

Anywhere in IndiaMultiple Locations Yo HR Consultancy Full time

Role : Senior Machine Learning Operations Engineer

Location : Remote

Contract Duration : 6 Months

Job Description :

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 production-ready 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 high-performance, multi-tenant deployment architectures and sophisticated model monitoring systems.

- Directly engage with internal stakeholders to incorporate feedback and refine our ML-driven 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 transformer-based models and NLP, preferably in a healthcare context.

- Strong track record of fine-tuning, running large-scale 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 non-relational 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.

(ref:hirist.tech)

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