Machine Learning Engineer

Designation : - ML / MLOPs Engineer

Location : - Noida (Sector- 132)

Key Responsibilities :

• Model Development & Algorithm Optimization : Design, implement, and optimize ML

models and algorithms using libraries and frameworks such as TensorFlow , PyTorch , and

scikit-learn to solve complex business problems.

scalability, and efficiency while fine-tuning hyperparameters.

format for model training and evaluation, applying industry best practices to ensure data

quality.

that enhance model performance and improve predictive capabilities.

machine learning models into production environments, leveraging Azure Machine

Learning and containerization technologies like Docker and Kubernetes .

environments, ensuring scalability and reliability using tools such as Azure Kubernetes

Service (AKS) .

lifecycle, including data ingestion, model training, deployment, and monitoring, ensuring

seamless operations and faster model iteration.

time processing requirements, ensuring efficient and scalable solutions.

Language Processing (NLP) , Computer Vision (CV) , and Generative AI (GenAI) ,

applying state-of-the-art techniques and frameworks to improve model performance.

integrate ML models into production workflows, building and maintaining continuous

integration / continuous deployment (CI / CD) pipelines using tools like Azure DevOps , Git ,

and Jenkins .

adjusting parameters and optimizing algorithms to improve accuracy and efficiency.

industry security standards and compliance protocols , such as GDPR and HIPAA .

ensure reproducibility and effective communication with stakeholders. Required Qualifications :

field.

similar roles.

PyTorch , scikit-learn , Pandas , and NumPy .

Azure Databricks , and Azure Kubernetes Service (AKS) .

automating the machine learning lifecycle.

learning models at scale.

Azure Blob Storage and Azure Data Lake .

these techniques to real-world business problems.

pipelines.

hyperparameter tuning