Recro | MLOPS ENGINEER | bangalore

1 month ago

bangalore, India Recro Full time
Key skills: Python Programming, MLOps Frameworks Proficiency, Machine Learning Systems Design
Currently, we are looking for ML Ops Engineer. In this role, you will have the opportunity to design the data pipelines and engineering infrastructure to support our clients’ enterprise machine learning systems at scale and 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
Does that sound a bit like you? Let’s talk Even if you don’t tick all the boxes below, we’d love to hear from you; our new department is rapidly growing and we’re looking for many people with the can-do mindset to join us on our digitalization journey. Thank you for considering DHL as the next step in your career – we do believe we can make a difference together
What will you need?
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
Ready to embark on the journey? Here’s what we are looking for:
As a Senior ML Ops Engineer, having Machine Learning skill set is a huge plus. Very good knowledge of ML Model deployment will also be an integral part of this role.
You are a technology aficionado, therefore you have a good understanding of Python, CI/CD pipeline. You are able to work independently, prioritize and organize your tasks under time and workload pressure. Working in a multinational environment, you can expect cross-region collaboration with teams around the globe, thus being advanced in spoken and written English will be certainly useful.

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