Dxc-Mlops Data Manager
Dxc-Mlops Data Manager
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Job Description
Job Description:
Key Responsibilities
Develop and train machine learning models using Python scikit-learn and other ML frameworks.
Conduct data wrangling analysis and feature engineering using Pandas SQL and IPython/Jupyter Notebooks.
Architect and implement reproducible data pipelines with Kedro.
Build and integrate intelligent applications leveraging Langchain and LLM ecosystems.
Develop and deploy scalable ML services on AWS utilizing services like S3 EC2 Lambda SageMaker etc.
Containerize applications using Docker and orchestrate deployments with Kubernetes.
Manage infrastructure as code using Terraform for provisioning cloud resources.
Set up CI/CD pipelines for ML workflows using Jenkins or similar tools.
Collaborate using Git for version control and code reviews.
Monitor and optimize ML models in production for performance drift and reliability.
Document technical designs processes and results to ensure reproducibility and knowledge sharing.
Required Skills and Experience
10 years of experience in Machine Learning Engineering Data Engineering or a similar technical role.
Proficiency in Python and solid experience with libraries like scikit-learn Pandas and IPython/Jupyter Notebook for data analysis and modelling.
Experience developing and orchestrating ML pipelines using Kedro or similar tools.
Hands-on expertise deploying applications and ML services on AWS.
Strong understanding of Docker and container-based deployments.
Practical experience with Kubernetes for orchestration and scaling of ML workloads.
Knowledge of Terraform for managing infrastructure as code.
Experience setting up and managing CI/CD pipelines using Jenkins or equivalent tools.
Solid SQL skills for data extraction transformation and analysis.
Experience working with Langchain and LLM-based solutions is a significant plus.
Familiarity with Git-based development workflows.
Strong problem-solving skills and the ability to work independently and collaboratively.
Nice to Have
Experience with MLOps best practices (e.g. model versioning monitoring feature stores).
Exposure to additional cloud platforms (e.g. GCP Azure).
Familiarity with security and compliance considerations in ML deployments.
Experience working in Agile teams and collaborating closely with cross-functional stakeholders.
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Required Experience:
Manager
Employment Type
Full-Time
