MLOps Engineer - Python (7-15 yrs)

Job Description :

- University Degree in Computer Science, Information Technology, or related field

- 6+ years of experience in the Machine Learning Operations role

- Design the data pipelines and engineering infrastructure to support our clients' enterprise machine learning systems at scale

- Take offline models data scientists build and turn them into a real machine learning production system

- Develop and deploy scalable tools and services for our clients to handle machine learning training and inference

- Identify and evaluate new technologies to improve performance, maintainability, and reliability of our clients' machine learning systems

- Apply software engineering rigor and best practices to machine learning, including CI/CD, automation, etc.

- Support model development, with an emphasis on auditability, versioning, and data security

- Facilitate the development and deployment of proof-of-concept machine learning systems

- Communicate with clients to build requirements and track progress

- Strong analytic skills related to working with structured, semi structured and unstructured datasets

- Docker and Kubernetes

- Experience in using popular MLOps frameworks like Kubeflow, MLFlow, and DataRobot

- Ability to build MLOps pipelines

- Strong Python programming knowledge

- Kubeflow

- Poetry for package management

- Black, ruff, isort, flake8 for code cleanup

- Github Actions

- Machine learning techniques : Decision Trees, Random Forest, Boosting Algorithm, Neural Networks, Deep Learning, Support Vector Machines, Clustering, Bayesian Networks, Reinforcement Learning, Feature Reduction / engineering, Anomaly deduction, Natural Language Processing (incl. sentiment analysis, Topic Modeling), Natural Language Generation

- Ability to design and implement cloud solutions - Azure

- Awareness of Agile / Scrum ways of working

- Identify the right modeling approach(es) for given scenario and articulate why the approach fits

- Assess data availability and modeling feasibility

- Review interpretation of models results

- Experience in Logistic industry domain would be added advantage

You should have :

- Certifications in some of the core technologies

- Ability to collaborate across different teams/geographies/stakeholders/levels of seniority

- Customer focus with an eye on continuous improvement;

- Energetic, enthusiastic and results-oriented personality

- Ability to coach other team members, you must be a team player!

- Strong will to overcome the complexities involved in developing and supporting data pipelines