Senior Machine Learning Engineer-19395
4 weeks ago
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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