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Machine Learning Engineer

Remote:

Full Remote

Contract:

Full time

Experience:

Mid-level (2-5 years)

Work from:

India

Offer summary

Qualifications:

Minimum 4 years experience in transformer-based models and NLP, preferably in healthcare, Proficiency in data science tools like Pandas, Notebooks, Numpy, Scipy, Experience with relational and non-relational databases, Strong track record in running large-scale training jobs and managing model servers, Familiarity with TensorFlow/PyTorch, HuggingFace, and model analysis frameworks.

Key responsabilities:

Develop and deploy production-ready ML models with a focus on scalability and monitoring
Write efficient Python code tailored to business needs
Build multi-tenant deployment architectures and model monitoring systems
Engage with stakeholders to refine ML-driven products
Uphold stringent security protocols in deployment and maintenance of ML models

Yo Hr Consultancy SME https://www.yohrconsultancy.com/

11 - 50 Employees

See more Yo Hr Consultancy offers

Job description

Senior Machine Learning Operations Engineer

Experience: 4 - 15 Years

Location: Permanent Remote

Must-Have:

Minimum 4 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.

Strong proficiency in spoken and written English language.

Budget: 25-30 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 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.