MLops Engineer

Overview

$$Negotiable
Full Time

Skills

Python
Snowflake
Databricks
MLOps

Job Details

Position: MLOps Engineer
Location: Remote
Duration: Long Term
Role: FTE


Must Have Skills:
8+ years of experience in MLOps Engineering,
Strong hands-on experience with Amazon SageMaker, including model training, deployment, and monitoring.
Solid experience working with streaming platforms: Apache Kafka, AWS Kinesis, or Spark Streaming.
Proficiency in ML libraries like scikit-learn, TensorFlow, PyTorch.
Experience with containerization (Docker) and orchestration (Kubernetes/EKS).
Familiarity with AWS services: S3, Lambda, CloudWatch, Step Functions, Glue.
Experience building and maintaining CI/CD pipelines for ML using Git, CodePipeline, or Jenkins.
If you have 5+ years of experience in building production-grade AWS SageMaker pipelines and deploying real-time ML models (sub-100ms latency!) on massive datasets, this is the role for you.
Build and maintain scalable MLOps pipelines using AWS SageMaker
Support full ML lifecycle: ingestion training versioning deployment
Optimize models for real-time inference via APIs
Detect and address data/model drift, automate re-training workflows
Use feature stores and model registries effectively
Collaborate across data science, ML, and engineering teams
Architect end-to-end AI/ML solutions on Databricks

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About VDart, Inc.