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ML OPS Engineer

Conch TechnologiesConcord, CA🇺🇸United StatesPosted 8 Sept 2026

Why This Role Stands Out

Advance your career with a mid-senior ML Ops Engineer role at Conch Technologies, where you'll contribute to innovative projects and experience significant professional growth. This position is ideal for skilled professionals eager to develop their expertise in a reputable company. Apply now to join a dynamic team and make a real impact.

Quick Overview

Seniority
Mid Senior
Work mode
On Site
Location
Concord, CA, United States
Posted
Yesterday
AWSMLOpsMachine LearningAnsibleAzureComplianceGoogle CloudKubernetesPythonStakeholder ManagementTerraform

Job Description

Hi
 
Greetings from the Conch technologies
 
Position: ML OPS Engineer
Location: Concord, CA ( 5 days a week onsite ) 
Duration: 12+ Months Contract 
 
Job Summary

We are seeking an experienced ML Ops Engineer to design, build, and support scalable, secure, and production-ready machine learning platforms across cloud and on-premises environments. The ideal candidate will have strong expertise in MLOps, Kubernetes, cloud platforms, automation, and reliability engineering.

Required Qualifications
  • 8+ years of experience in Platform Engineering, DevOps, MLOps, or related fields.
  • Strong experience with Google Cloud Platform (Google Cloud Platform) and cloud-native technologies.
  • Hands-on expertise in Kubernetes, including GKE and/or OpenShift .
  • Strong proficiency in Python for automation and platform development.
  • Experience building and managing MLOps platforms and ML lifecycle workflows.
  • Expertise in CI/CD pipelines and infrastructure automation.
  • Knowledge of security, data protection, and compliance best practices.
  • Experience with observability, monitoring, logging, and incident management.
  • Strong understanding of Site Reliability Engineering (SRE) principles.
  • Excellent communication and stakeholder management skills.
Preferred Skills
  • Experience designing enterprise-scale ML platform architectures.
  • Multi-cloud experience (AWS, Azure, and Google Cloud Platform).
  • Experience supporting AI/GenAI workloads in production environments.
  • Knowledge of Infrastructure as Code (Terraform, Ansible, etc.).
  • Familiarity with model serving, feature stores, and model monitoring.
  • Experience mentoring engineers and driving platform engineering best practices.
  • Background in highly regulated enterprise environments.
 
 
 
Thank you & Regards
  V S Durga Prasad | Sr.  I T Recruiter 
E:  | Desk Ph:  
Conch Technologies Inc | 

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