
Only 24h Left) MLOps Engineer
4 weeks ago
Experience: 4–8 Years
Apply Now: 𝐜𝐚𝐫𝐞𝐞𝐫𝐬@𝐬𝐢𝐝𝐢𝐧𝐟𝐨𝐫𝐦𝐚𝐭𝐢𝐨𝐧.𝐜𝐨𝐦
Preferred: Immediate Joiners
Domain Preference: Healthcare
About the Role:
We are seeking a highly skilled MLOps Engineer with a strong foundation in DevOps, AWS Cloud, and ML infrastructure. You'll be part of an agile team building scalable AI & Generative AI platforms, modernizing CI/CD pipelines, and managing the end-to-end ML lifecycle in real-world, production-grade environments.
Roles & Responsibilities:
- Design and implement scalable MLOps architectures and workflows on AWS
- Manage full ML model lifecycle: Build, Train, Deploy, Monitor, and Retrain
- Deploy and manage GenAI/LLM models (OpenAI, Bedrock, Hugging Face)
- Lead CI/CD pipeline modernization for ML and Data Science teams
- Build modular Terraform stacks for hybrid/multi-cloud environments
- Define and enforce model governance, versioning, access control, and observability
- Integrate tools like LangChain, OpenAI APIs, SageMaker, SHAP, LIME, CloudWatch
- Collaborate across teams (Data Science, DevOps, Security)
- Apply data privacy, compliance, and security best practices (especially in healthcare)
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Technical Skills Required
- 5–8 years experience in DevOps / ML Infrastructure, with 3+ years in MLOps
- Proficient in AWS Cloud: SageMaker, EKS, Lambda, CloudWatch, S3
- Expert in Python scripting for automation and ML pipeline orchestration
- Advanced skills in Terraform for IaC and modular provisioning
- Experience deploying LLMs / GenAI (OpenAI, Bedrock, Hugging Face)
- Familiar with LangChain, RAG pipelines, Vector Databases
- Hands-on with ML monitoring tools: SageMaker Model Monitor, MLflow, Prometheus
- Strong understanding of Docker, Kubernetes, GitOps, and CI/CD tools (Jenkins, GitHub Actions)
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