Google Cloud Platform
4 days ago
About the Company
Our client is a trusted global innovator of IT and business services, present in 50+ countries. They specialize in digital & IT modernization, consulting, managed services, and industry-specific solutions. With a commitment to long-term success, they empower clients and society to move confidently into the digital future.
Job Description Important Note (Please Read Before Applying)
Do NOT apply if:
You have less than 5 years in GCP.
You do not have hands-on
PyTorch
,
TensorFlow
.
You are on a notice period longer than 15 days.
Apply ONLY if you meet ALL criteria above. Random / irrelevant applications will not be processed.
Job Title:
Google Cloud Platform
Location:
Remote (Global) | Preferred: US / EU Time Zones
Job Type:
Full-Time
Experience Required:
8+ Years
About the Role:
We're looking for a
Senior ML Inference Engineer
with deep expertise in
containerized ML workflows
,
large model inference
, and
cloud-native deployment
. You'll work at the intersection of
MLOps
,
deep learning
, and
cloud infrastructure
, helping productionize some of the most powerful language models available today.
Key Responsibilities:
- Deploy and optimize
large-scale models
(e.g., Mixtral, Gemma) for
inference performance
and
latency
. - Build and maintain
highly optimized Docker containers
, using multi-stage builds and best practices for performance and security. - Work with
high-performance inference servers
such as
vLLM
for efficient GPU utilization in production. - Manage and automate deployment on
Google Cloud Platform (GCP)
using tools like
GKE
,
Cloud Run
, and
Artifact Registry
. - Support model deployment pipelines for Google Cloud's
Model Garden
, handling complex dependency resolution. - Write and maintain
clear, reproducible documentation
for container builds, deployment processes, and system management.
Requirements:
- 8+ years
of experience in software/ML engineering roles. - Advanced knowledge of
PyTorch
and
TensorFlow
. - Strong hands-on experience with
Docker
and container-based deployment workflows. - Proven experience with
ML inference optimization
, especially in GPU-accelerated environments. - Familiarity with
LLMs and open-weight models
(e.g., Mixtral, Gemma, LLaMA, Falcon). - Solid grasp of
Google Cloud services
for container orchestration. - Excellent communication skills and a passion for clean, scalable infrastructure.
Nice to Have:
- Experience with other inference frameworks (e.g., TensorRT, ONNX Runtime, DeepSpeed).
- Familiarity with
CI/CD pipelines
and
infrastructure as code
.
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