Senior Machine Learning Engineer

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About Aaizeltech

Senior MLOps Engineer

Role Overview

This role requires strong expertise and hands-on MLOps experience. You will architect and manage cloud infrastructure, CI/CD systems, Kubernetes clusters, and full ML pipelines—from data ingestion to deployment and drift monitoring.

Key Responsibilities

MLOps Responsibilities:

• Collaborate with data scientists to operationalize ML workflows.
• Build complete ML pipelines with

  Airflow

  ,

  Kubeflow Pipelines

  , or

  Metaflow

  .
• Deploy models using

  KServe

  ,

  Seldon Core

  ,

  BentoML

  ,

  TorchServe

  , or

  TF Serving

  .
• Package models into Docker containers using

  Flask

  or

  FastAPI

  or

  Django

  for APIs.
• Automated dataset versioning & model tracking via

  DVC

  and

  MLflow

  .
• Setup

  model registries

  and ensure

  reproducibility

  and

  audit trails

  .

• Implement model monitoring for:

Data drift

• Implement

  event-driven retraining workflows

  triggered by drift alerts or data freshness.
• Schedule

  GPU workloads

  on Kubernetes and manage

  resource utilization

  for ML jobs.
• Design and manage secure, scalable infrastructure using

  AWS

  ,

  GCP

  , or

  Azure

  .
• Build and maintain

  CI/CD pipelines

  using

  Jenkins

  ,

  GitLab CI

  ,

  GitHub Actions

  , or

  AWS DevOps

  .
• Write and manage

  Infrastructure as Code

  using

  Terraform

  ,

  Pulumi

  , or

  CloudFormation

  .
• Automated configuration management with

  Ansible

  ,

  Chef

  , or

  SaltStack

  .
• Manage

  Docker containers

  and advanced

  Kubernetes

  resources (Helm, StatefulSets, CRDs, DaemonSets).
• Implement robust monitoring and alerting stacks:

  Prometheus

  ,

  Grafana

  ,

  CloudWatch

  ,

  Datadog

  ,

  ELK

  , or

  Loki

  .

Must-Have Skills

• Advanced expertise in

  Linux administration

  , networking, and shell scripting.
• Strong knowledge of

  Docker

  ,

  Kubernetes

  , and container security.
• Hands-on experience with

  IaC tools

  like Terraform and configuration management like Ansible.
• Proficient in

  cloud-native services

  : IAM, EC2, EKS/GKE/AKS, S3, VPCs, Load Balancing, Secrets Manager.
• Mastery of

  CI/CD tools

  (e.g., Jenkins, GitLab, GitHub Actions).
• Familiarity with

  SaaS architecture

  , distributed systems, and multi-env deployments.
• Proficiency in

  Python

  for scripting and ML-related deployments.
• Experience integrating

  monitoring

  ,

  alerting

  , and

  incident management

  workflows.
• Strong understanding of

  DevSecOps

  , security scans (e.g.,

  Trivy

  ,

  SonarQube

  ,

  Snyk

  ) and

  secrets management

Vault

• Experience with

  GPU orchestration

  and hybrid on-prem + cloud environments.

Nice-to-Have Skills

• Knowledge of

  GitOps

  workflows (e.g., ArgoCD, FluxCD).
• Experience with

  Vertex AI

  ,

  SageMaker Pipelines

  , or

  Triton Inference Server

  .
• Familiarity with

  Knative

  ,

  Cloud Run

  , or

  serverless ML deployments

  .
• Exposure to

  cost estimation

  ,

  rightsizing

  , and

  usage-based autoscaling

  .
• Understanding of

  ISO 27001

  ,

  SOC2

  , or

  GDPR-compliant ML deployments

  .
• Knowledge of

  RBAC for Kubernetes and ML pipelines

  .

Who You'll Work With

• AI/ML Engineers, Backend Developers, Frontend Developers, QA Team
• Product Owners, Project Managers, and external Government or Enterprise Clients

How to Apply

to hr@aaizeltech.com or anju@aaizeltech.com