Job Description

Epergne Solutions is looking for Senior ML Ops Engineer.Experience : 6+ yearsPayroll: Epergne SolutionsLocations: Chennai, Bengaluru, Pune, Hyderabad, Bhubaneshwar, Chandigarh, GurugramWhat will you need?\xef\x82\xb7 University Degree in Computer Science, Information Technology, or related field\xef\x82\xb7 6+ years of experience in the Machine Learning Operations role\xef\x82\xb7 Design the data pipelines and engineering infrastructure to support our clients enterprise machine learning systems at scale\xef\x82\xb7 Take offline models data scientists build and turn them into a real machine learning production system\xef\x82\xb7 Develop and deploy scalable tools and services for our clients to handle machine learning training and inference\xef\x82\xb7 Identify and evaluate new technologies to improve performance, maintainability, and reliability of our clients machine learning systems\xef\x82\xb7 Apply software engineering rigor and best practices to machine learning, including CI/CD, automation, etc.\xef\x82\xb7 Support model development, with an emphasis on auditability, versioning, and datasecurity\xef\x82\xb7 Facilitate the development and deployment of proof-of-concept machine learningsystems\xef\x82\xb7 Communicate with clients to build requirements and track progress\xef\x82\xb7 Strong analytic skills related to working with structured, semi structured and unstructureddatasets\xef\x82\xb7 Docker and Kubernetes\xef\x82\xb7 Experience in using popular ML Ops frameworks like Kubeflow, ML Flow, and Data Robot\xef\x82\xb7 Ability to build ML Ops pipelines\xef\x82\xb7 Strong Python programming knowledge\xef\x82\xb7 Kubeflow\xef\x82\xb7 Poetry for package management\xef\x82\xb7 Black, ruff, isort, flake8 for code clean up\xef\x82\xb7 GitHub Actions\xef\x82\xb7 Machine learning techniques: Decision Trees, Random Forest, Boosting Algorithm,Neural Networks, Deep Learning, Support Vector Machines, Clustering, BayesianNetworks, Reinforcement Learning, Feature Reduction / engineering, Anomalydeduction, Natural Language Processing (incl. sentiment analysis, Topic Modelling),Natural Language Generation\xef\x82\xb7 Ability to design and implement cloud solutions - Azure\xef\x82\xb7 Awareness of Agile / Scrum ways of working\xef\x82\xb7 Identify the right modelling approach(es) for given scenario and articulate why theapproach fits\xef\x82\xb7 Assess data availability and modelling feasibility\xef\x82\xb7 Review interpretation of models results\xef\x82\xb7 Experience in Logistic industry domain would be added advantageYou should have:\xef\x82\xb7 Certifications in some of the core technologies\xef\x82\xb7 Ability to collaborate across different teams/geographies/stakeholders/levels of seniority\xef\x82\xb7 Customer focus with an eye on continuous improvement;\xef\x82\xb7 Energetic, enthusiastic and results-oriented personality\xef\x82\xb7 Ability to coach other team members, you must be a team player!\xef\x82\xb7 Strong will to overcome the complexities involved in developing and supporting datapipelinesReady to embark on the journey? Heres 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-regioncollaboration with teams around the globe, thus being advanced in spoken and written English will be certainly useful.

Epergne Solutions