Senior Machine Learning Engineer-19395

4 weeks ago


India Gemraj Technologies Ltd Full time

Senior Machine Learning Operations Engineer-19395

Engagement type: Full-Time

Engagement length: 6- 12 Months

Max. notice period: 2 weeks

Location: India

Project location: United States (US)

Project timezone: UTC-8:00 America/Los_Angeles- NIGHT SHIFT

Overlap hours: 4 hrs/day


Requirements -Skillset:

Natural Language Processing (NLP) - 3 Years,

Tensorflow - 1 Year,

PyTorch - 1 Year,

Pandas - 1 Year,

Scipy - 1 Year,

Numpy - 1Year


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.



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