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Ml Infrastructure Engineer Jobs in Edison, NJ (NOW HIRING)

Meta

Software Engineer, Systems ML

New York, NY

$154K/yr

Develop and maintain high-performance ML infrastructure components in C++ and Python, ensuring ... Mentor other engineers on ML infrastructure best practices, debugging methodologies, and ...

Catalyst Labs

ML Engineer

Manhattan, NY · On-site

... the ML infrastructure and processes for scalability and performance. Qualifications : Required ... ML engineering. • Strong programming skills in Python (TypeScript experience is a plus). • ...

Catalyst Labs

ML Engineer

Manhattan, NY · On-site

... the ML infrastructure and processes for scalability and performance. Qualifications : Required ... ML engineering. • Strong programming skills in Python (TypeScript experience is a plus). • ...

vCluster Labs

AI Infrastructure Engineer

New York, NY · Remote

$140K - $165K/yr

As an AI Infrastructure Engineer, your role will include: * Lead Technical Deployments: Drive end ... AI/ML Familiarity: Experience with inference serving, GPU scheduling, and the tooling around LLM ...

Melotech

AI/ML Engineer

New York, NY · On-site

What you will do As our ML Engineer, you'll be the technical backbone powering our content platform ... Designing scalable ML infrastructure and pipelines that handle massive media datasets

Modal, Inc

Forward Deployed Engineer - ML

New York, NY · On-site

$180K - $250K/yr

AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new ... The Role: We're looking for Forward Deployed ML Engineers who want to work at the intersection of ...

SLR Search

Staff Backend Engineer

New York, NY · On-site

$200K - $250K/yr

Join an elite team as a Senior Backend Engineer architecting the high-performance data backbone and ML infrastructure that powers autonomous manufacturing. You will build the low-latency systems that ...

Sigma Computing

Senior AI/ML Engineer

New York, NY · On-site

$240K - $270K/yr

As an AI/ML Engineer, you'll join a growing team focused on building the AI foundation that will ... Develop and scale AI/ML infrastructure that powers both internal tooling and customer-facing ...

Apple

SRE Manager, ML Operations

New York, NY · On-site

$62.25 - $82.75/hr

... Engineering team, with a focus on ML Operations ... This team owns the reliability, performance, and scalability of the Ad Serving infrastructure that ...

Sigma Computing

Staff AI/ML Engineer

New York, NY

$240K - $270K/yr

As an AI/ML Engineer, you'll join a growing team focused on building the AI foundation that will ... Develop and scale AI/ML infrastructure that powers both internal tooling and customer-facing ...

Melotech

AI/ML Engineer Intern

New York, NY · On-site

$18.25 - $23.75/hr

Designing scalable ML infrastructure and pipelines that handle massive media datasets ... Hands-on ML engineering experience building production systems at Big Tech companies, high-growth ...

Espresso

Staff Infrastructure Engineer

New York, NY · On-site

$225K - $450K/yr

... engineering. Today, we help our customers reduce Snowflake and Databricks SQL compute costs by up ... Build infrastructure and data pipelines that support ML modeling and product features * Improve ...

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Showing results 21-40

All JobsMl Infrastructure Engineer JobsMl Infrastructure Engineer Jobs in Edison, NJ

Ml Infrastructure Engineer information

See Edison, NJ salary details

$47.2K

$128.9K

$184.6K

How much do ml infrastructure engineer jobs pay per year?

As of Aug 23, 2026, the average yearly pay for ml infrastructure engineer in Edison, NJ is $128,862.00, according to ZipRecruiter salary data. Most workers in this role earn between $109,000.00 and $143,000.00 per year, depending on experience, location, and employer.

What is the difference between Ml Infrastructure Engineer vs Data Engineer?

AspectML Infrastructure EngineerData Engineer
Required CredentialsBachelor's/Master's in CS, experience with cloud platforms, scripting, and ML toolsBachelor's/Master's in CS, experience with databases, ETL, and data pipelines
Work EnvironmentFocus on deploying and maintaining ML systems, cloud infrastructure, and automationDesigning and building data pipelines, managing large datasets, and data storage
Employer & Industry UsageTech companies, AI startups, research labsFinance, healthcare, e-commerce, and data-driven industries

The ML Infrastructure Engineer specializes in building and maintaining the infrastructure that supports machine learning models, focusing on deployment, scalability, and automation. In contrast, Data Engineers primarily develop data pipelines and manage large datasets to enable data analysis and business intelligence. Both roles require strong technical skills and often overlap, but their core focus areas differ significantly.

What are popular job titles related to Ml Infrastructure Engineer jobs in Edison, NJ?

For Ml Infrastructure Engineer jobs in Edison, NJ, the most frequently searched job titles are:

What job categories do people searching Ml Infrastructure Engineer jobs in Edison, NJ look for?

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Ml Infrastructure Engineer jobs near you
Infographic showing various Ml Infrastructure Engineer job openings in Edison, NJ as of August 2026, with employment types broken down into 86% Full Time, 7% Part Time, 3% Temporary, and 4% Contract. Highlights an 85% Physical, 6% Hybrid, and 9% Remote job distribution, with an average salary of $128,862 per year, or $62 per hour.

NVIDIA AI Infrastructure & Kubernetes Platform Engineer (DGX Systems)

Catapult Solutions Group

New York, NY • On-site

$125/hr

Contractor

Medical, Retirement, PTO

Posted 11 days ago

Job description

NVIDIA AI Infrastructure & Kubernetes Platform Engineer (DGX Systems)
Department: Infrastructure Engineering
Location / Remote Policy: Remote
Role Type: Contract - 6-month initial engagement
About Our Client
Our client is a technology and professional services firm founded in 2015 on the strength of its founders' 30 years of industry experience. They set out to bridge a gap in professional services - to be a true partner rather than just a vendor - delivering expert guidance, innovative solutions, and personalized service at a cost-effective rate. Their mission is to empower businesses to succeed in the digital era, harnessing technology to drive transformation, innovation, and growth. Guided by a "make a customer, not a sale" philosophy, they lead with a customer-first approach and a team of senior-level engineers sourced from the world's leading OEMs, including AWS, Palo Alto Networks, Cisco, and Microsoft.
Job Description
Our client is seeking a highly skilled AI Infrastructure & Kubernetes Platform Engineer with a proven track record deploying and managing NVIDIA DGX-based AI clusters, orchestrating containerized AI workloads on Kubernetes, and ensuring secure, high-throughput operations across InfiniBand-powered networks. You'll bring a strong certification foundation across both Kubernetes (CKA, CKAD, CKS) and NVIDIA's AI infrastructure stack, paired with hands-on experience across DGX, BlueField, and high-speed networking.
This role is central to supporting AI/ML infrastructure at scale - enabling efficient training and inference for complex models and integrating NVIDIA's compute, storage, and fabric solutions with modern DevOps practices. Day to day, you'll own DGX cluster operations, architect GPU-accelerated Kubernetes platforms, tune InfiniBand fabric for throughput, and harden the environment through DPU-enhanced security.
You'll work at the intersection of infrastructure, DevOps, and AI/ML, keeping the platform reliable and cost-efficient for the teams that depend on it. The ideal candidate is deeply hands-on, obsessed with performance and security, and energized by operating some of the most advanced AI compute available.
Duties and Responsibilities
AI Infrastructure Operations
  • Deploy and manage NVIDIA DGX BasePODs and SuperPODs for high-performance AI workloads.
  • Oversee DGX system lifecycle operations, including provisioning, monitoring, firmware upgrades, and capacity planning.
  • Operate Base Command Manager to manage GPU clusters, schedule workloads, and integrate with MLOps tools.
  • Perform DGX node health validation, NCCL interconnect testing, and NVLink topology verification after deployments or hardware changes.

Kubernetes Platform Engineering
  • Architect secure, scalable Kubernetes clusters optimized for GPU-accelerated workloads using the NVIDIA GPU Operator.
  • Apply CKA/CKAD/CKS expertise to develop, deploy, and secure AI applications on Kubernetes.
  • Implement CI/CD pipelines and GitOps methodologies for deploying and managing ML workflows.

High-Performance Networking & DPUs
  • Administer InfiniBand networks and BlueField DPUs using Unified Fabric Manager (UFM).
  • Enable NVLink/NVSwitch performance across GPU nodes and tune fabric configurations for minimal latency and maximum throughput.
  • Use BlueField to offload storage, firewalling, and telemetry, strengthening AI workload security and performance.

Security & Compliance
  • Apply CKS best practices to secure containerized AI environments.
  • Configure runtime security, secrets management, network segmentation, and auditing across DPU-enhanced Kubernetes deployments.
  • Support zero-trust initiatives by enforcing workload identity, RBAC policies, and supply-chain integrity across AI container images and model artifacts.

Monitoring, Telemetry & Optimization
  • Monitor GPU, CPU, and I/O performance using NVIDIA DCGM, Prometheus, Grafana, and Base Command APIs.
  • Tune system performance and model-training pipelines for cost-efficiency and throughput.
  • Build and maintain operational runbooks, incident-response playbooks, and SLA dashboards covering GPU utilization, thermal thresholds, and fabric health.

Required Experience/Skills
Certifications
  • Certified Kubernetes Administrator (CKA)
  • Certified Kubernetes Application Developer (CKAD)
  • Certified Kubernetes Security Specialist (CKS)
  • NVIDIA Certified Associate: AI Infrastructure & Operations (NCA-AIIO)
  • NVIDIA Certified Professional: AI Infrastructure (NCP-AII)
  • NVIDIA Certified Professional: AI Operations (NCP-AIO)
  • NVIDIA Certified Professional: AI Networking (NCP-AIN)

Hands-On Expertise
  • DGX System, BasePOD, and SuperPOD administration
  • BlueField DPU configuration and operations
  • InfiniBand fabric and UFM management
  • Base Command Manager for workload orchestration

Technical Skills
  • Kubernetes, Helm, and the NVIDIA GPU Operator
  • DevOps tooling: Ansible, Terraform, GitOps, CI/CD pipelines
  • Programming/scripting: Python, YAML, Bash

Nice-to-Haves
  • Kubeflow and broader MLOps pipeline experience.
  • Parallel/HPC storage: NFS, BeeGFS, Lustre.
  • Advanced networking: RoCE, RDMA, gRPC, and DPU offload tuning.

Education
Bachelor's degree in Computer Science, Engineering, or a related field - or equivalent hands-on experience.
Pay & Benefits Summary
  • Pay Rate: $125/hr
  • Benefits: Eligible for a comprehensive benefits package, including medical/health coverage, paid time off, and 401(k) retirement savings.

Call-to-Action
Operate the cutting edge of AI compute. Apply today and put your DGX, Kubernetes, and NVIDIA expertise to work.
Keywords: NVIDIA DGX | SuperPOD | Kubernetes | CKA / CKAD / CKS | NCA-AIIO | NCP-AII | NCP-AIO | NCP-AIN | InfiniBand | BlueField DPU | UFM | GPU Operator | Kubeflow | RDMA | RoCE | MLOps

Apply