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Remote - MLOps Engineer – GCP (Vertex / Gemini / Greenfield)
Remote, Work from Home
Remote
Work from Home
00000
Date
: Nov-15-25
2025-11-15
2026-11-15
Remote - MLOps Engineer – GCP (Vertex / Gemini / Greenfield)
Remote, Work from Home
Nov-15-25
Work Authorization
US Citizen
GC
H1B
GC EAD, TN EAD, H4 EAD, L2 EAD, OPT EAD, CPT EAD
Preferred Employment
Corp-Corp
W2-Permanent
W2-Contract
1099-Contract
Contract to Hire
Job Details
Experience
:
Architect
Rate/Salary ($)
:
Market
Duration
:
6 to 12 Months
Sp. Area
:
Cloud
,
Salesforce
,
SaaS
Sp. Skills
:
[GCP] Google Cloud Platform
Consulting / Contract
CONTRACTOR
Remote Work from Home
Required Skills
:
GCP, AI/ML, Python, CI/CD,
IAM
Preferred Skills
:
Domain
:
IT/Software
Work Authorization
US Citizen
GC
GC EAD, TN EAD, H4 EAD, L2 EAD, OPT EAD, CPT EAD
H1B
Preferred Employment
Corp-Corp
W2-Permanent
W2-Contract
1099-Contract
Contract to Hire
Job Details
Experience
:
Architect
Rate/Salary ($)
:
Market
Duration
:
6 to 12 Months
Sp. Area
:
Cloud
,
Salesforce
,
SaaS
Sp. Skills
:
[GCP] Google Cloud Platform
Consulting / Contract
CONTRACTOR
Remote Work from Home
Required Skills
:
GCP, AI/ML, Python, CI/CD,
IAM
Preferred Skills
:
Domain
:
IT/Software
DMS Vision, Inc.
Frisco, TX
Post Resume to
View Contact Details &
Apply for Job
Job Description
:
Job Title : MLOps Engineer GCP (Vertex / Gemini / Greenfield) (W2 Only)
Location :Remote
Duration: 6-12 month project
Job Description:-
We are looking for an
experienced MLOps Engineer with strong hands-on expertise in
Google Cloud Platform
, Vertex AI, and GenAI (Gemini).
The consultant will be responsible for building and operationalizing end-to-end machine learning pipelines and integrating GenAI models into production environments. Prior experience working in
Greenfield GCP setup or
cloud
foundation environments is highly preferred.
Responsibilities:-
Design, build, and maintain end-to-end MLOps pipelines in GCP.
Deploy, fine-tune, and manage models using Vertex AI (Model Garden, AutoML, Pipelines).
Utilize Gemini / Generative AI APIs to build LLM-based applications and workflows.
Work with BigQuery,
Cloud
Storage, Pub/Sub, Dataflow, Dataproc for data pipeline integration.
Implement CI/CD pipelines for ML workflows using
Cloud
Build / GitLab / GitHub Actions.
Manage model versioning, monitoring, and drift detection.
Collaborate with Data Scientists,
Cloud
Engineers, and Application teams.
Ensure security, compliance,
IAM
, and cost governance aligned to GCP best practices.
Required Skills:-
Overall 10+ Years of IT Experience required.
Strong hands-on experience in
GCP (Compute, VPC,
IAM
, Networking).
Practical experience with
Vertex AI and ML model deployment.
Experience working with
Gemini / Generative AI models.
MLOps tools:
Vertex Pipelines, Kubeflow, MLflow, TFX (any is fine).
IaC with Terraform is a plus.
Strong proficiency in
Python and containerization (Docker, GKE/Kubernetes)
.
Experience with monitoring and logging (Stackdriver /
Cloud
Logging & Monitoring).
Nice to Have:-
Experience setting up Greenfield GCP Landing Zone.
Prior work in enterprise-scale AI / ML implementations.
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