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Senior ML Ops Engineer
Epergne Solutions
posted 1d ago
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Job Description
Epergne Solutions is looking for Senior ML Ops Engineer. Experience :6+ years
Payroll:Epergne Solutions
Locations:Chennai, Bengaluru, Pune, Hyderabad, Bhubaneshwar, Chandigarh, Gurugram
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 ML Ops frameworks like Kubeflow, ML Flow, and Data Robot
? Ability to build ML Ops pipelines
? Strong Python programming knowledge
? Kubeflow
? Poetry for package management
? Black, ruff, isort, flake8 for code clean up
? 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 Modelling),
Natural Language Generation
? Ability to design and implement cloud solutions Azure
? Awareness of Agile / Scrum ways of working
? Identify the right modelling approach(es) for given scenario and articulate why the
approach fits
? Assess data availability and modelling 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. Show more Show less
Payroll:Epergne Solutions
Locations:Chennai, Bengaluru, Pune, Hyderabad, Bhubaneshwar, Chandigarh, Gurugram
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.
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 ML Ops frameworks like Kubeflow, ML Flow, and Data Robot
? Ability to build ML Ops pipelines
? Strong Python programming knowledge
? Kubeflow
? Poetry for package management
? Black, ruff, isort, flake8 for code clean up
? 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 Modelling),
Natural Language Generation
? Ability to design and implement cloud solutions Azure
? Awareness of Agile / Scrum ways of working
? Identify the right modelling approach(es) for given scenario and articulate why the
approach fits
? Assess data availability and modelling 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.
workload pressure.
collaboration with teams around the globe, thus being advanced in spoken and written English will be certainly useful.
Employment Type: Full Time, Permanent
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