Machine Learning Engineer

1 week ago

Hyderabad, India EverestDX Inc Full time
About EverestDXEverest DX – We are a Digital Platform Services company, headquartered in Stamford. Our Platform/Solution includes Orchestration, Intelligent operations with BOTs’, AI-powered analytics for Enterprise IT. Our vision is to enable Digital Transformation for enterprises to deliver seamless customer experience, business efficiency and actionable insights through an integrated set of futuristic digital technologies.Digital Transformation Services - Specialized in Design, Build, Develop, Integrate, and Manage cloud solutions and modernize Data centers, build a Cloud-native application, and migrate existing applications into secure, multi-cloud environments to support digital transformation.Our Digital Platform Services enable organizations to reduce IT resource requirements and improve productivity, in addition to lowering costs and speed digital transformation. For more information, please visit

.

Job Title : ML Ops EngineerLocation : RemoteJob Type : Full-TimExperience : 6-8 Years of Relevant Work ExperienceJob OverviewWe are seeking a skilled and experienced

ML Ops Enginee r to join our dynamic team. The ideal candidate will have a strong background in

ML Ops/DevOp s, with expertise in configuring

CICD pipeline s and working with

ADF Pipeline s on

Databrick s. You will be responsible for the seamless deployment, integration, and management of machine learning models into production environments. If you have hands-on experience in

ML-Flo w and

Pytho n, we encourage you to apply and be part of a fast-growing team working on cutting-edge technologies

Key ResponsibilitiesConfigure, manage, and maintai n CI/CD pipelin es for deploying machine learning models and applications in productionWork wit h Azure Data Factory (AD F) pipelines integrated wit h Databric ks to manage data workflows for machine learning projectsDevelop, deploy, and monito r machine learning mode ls and ensure seamless integration into production environmentsLeverag e ML-Fl ow to manage machine learning lifecycle, including tracking experiments, model training, and deploymentCollaborate with data scientists and engineers to optimize data processing and model deployment workflowsEnsure the scalability, performance, and reliability of production-level ML models and systemsImplement automated testing strategies for ML models and pipelinesTroubleshoot and resolve production issues related to machine learning models, data pipelines, and infrastructureParticipate in the design and development of infrastructure for ML model training and deployment

Required Skills & Qualifications6-8 years of experie nce

in ML

Op s, Dev OpsStrong hands-on experience in configuri ng CI/CD pipeli nes for machine learning workflowsProven experience working wi th Azure Data Factory (A DF) pipelines a nd Databri cksIn-depth knowledge

of ML-F low for model tracking and versioningProficiency

in Pyt hon for model development, deployment, and automation tasksExperience with containerization technologies li ke Doc ker and orchestration tools such

as Kuberne tesSolid understanding of cloud platforms (preferab ly Az ure)Strong problem-solving skills and ability to troubleshoot complex issues related to machine learning pipelines and modelsExcellent communication and collaboration skills, with the ability to work in cross-functional teamsPreferred SkillsFamiliarity with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-Learn).Experience w ith version control sys tems l ike GitKnowledge of infrastructure-as-code tools l ike Terra form

or ARM templ atesFamiliarity w ith monitoring and log ging tools (e.g., Prometheus, Grafana)

Educational QualificationsBachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field.

Why Join UsContinuous Learning: The company invests in skills development through training, certifications, and access to cutting-edge projects in digital transformation.Dynamic, Collaborative Culture: Unlike a large, rigid structure, Everest DX promotes a culture of open communication, creativity, and innovation.Agile Work Environment: The company operates with a startup mindset, adapting quickly to changes, which can be more stimulating than rigid corporate processes.Innovative Solutions: Working at a boutique company like Everest DX provides exposure to cutting-edge technologies, creative problem-solving, and innovative product development.Competitive Salaries: Despite being a boutique company, Everest DX ensures competitive compensation packages that are comparable to industry standards.

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