Remote- und Homeoffice Jobs in bhubaneswar ∙ Seite 1
39 Remote- und Homeoffice-Jobs online
L4- CV DMS- BERHAMPUR- OR-BACL (Bhubaneshwar RO (BACL), India)
Bajaj Auto · Bhubaneswar, Indien · Onsite
Technician - Critical Care Medicine 20026
Apollo Hospitals Enterprise Limited · Bhubaneswar, Indien · Onsite
Customer Sales Executive - Two Wheeler Loans - Bhubaneshwar - Samantarapur - CSE
Tata Capital Limited · Bhubaneswar, Indien · Onsite
T&T- HC- HRT- Workday Integration- Sr Analyst- Bhubaneshwar (Bhubaneswar CEC, IN)
Deloitte US | Together Makes Progress · Bhubaneswar, Indien · Onsite
Territory Manager- Customer Experience (Bhubneshwar, OR, IN, 751010)
Hero MotoCorp - India's Leading Two-Wheeler Manufacturer · Bhubaneswar, Indien · Onsite
Associate Agency Development Manager (Bhubaneshwar, OR, IN)
Axis Max Life Insurance (Formerly Max Life Insurance) · Bhubaneswar, Indien · Onsite
Chat Customer Service Representative – Bhubaneswar, Odisha Recruitment Drive
TTEC · Bhubaneswar, Indien · Onsite
Sales Counsellor (Bhubaneswar, Odisha, India)
Word-Class Managed Learning and Training Services - MTS | NIIT · Bhubaneswar, Indien · Onsite
Technology & Transformation - Engineering - Senior Consultant - Azure Data Engineer (Bhubaneswar CEC, IN)
Deloitte US | Together Makes Progress · Bhubaneswar, Indien · Hybrid
Product Application Expert - Electrical Distribution
Schneider Electric · Bhubaneswar, Indien · Onsite
MLOPS Engineer - Bhubaneswar
None · Bhubaneswar, Indien · Onsite
- Professional
- Optionales Büro in Bhubaneswar
Role: MLOps Engineer
Location: Bhubaneswar
Key words -Skillset
- AWS SageMaker, Azure ML Studio, GCP Vertex AI
- PySpark, Azure Databricks
- MLFlow, KubeFlow, AirFlow, Github Actions, AWS CodePipeline
- Kubernetes, AKS, Terraform, Fast API
Responsibilities
- Model Deployment, Model Monitoring, Model Retraining
- Deployment pipeline, Inference pipeline, Monitoring pipeline, Retraining pipeline
- Drift Detection, Data Drift, Model Drift
- Experiment Tracking
- MLOps Architecture
- REST API publishing
Job Responsibilities:
· Research and implement MLOps tools, frameworks and platforms for our Data Science projects.
· Work on a backlog of activities to raise MLOps maturity in the organization.
· Proactively introduce a modern, agile and automated approach to Data Science.
· Conduct internal training and presentations about MLOps tools’ benefits and usage.
Required experience and qualifications:
· Wide experience with Kubernetes.
· Experience in operationalization of Data Science projects (MLOps) using at least one of the popular frameworks or platforms (e.g. Kubeflow, AWS Sagemaker, Google AI Platform, Azure Machine Learning, DataRobot, DKube).
· Good understanding of ML and AI concepts. Hands-on experience in ML model development.
· Proficiency in Python used both for ML and automation tasks. Good knowledge of Bash and Unix command line toolkit.
· Experience in CI/CD/CT pipelines implementation.
· Experience with cloud platforms - preferably AWS - would be an advantage.