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Ml Infrastructure Engineer Jobs in Hackensack, NJ

Senior ML Infrastructure Engineer

New York, NY · On-site

$118K - $161K/yr

  • Medical

  • Dental

  • Vision

Senior ML Infrastructure Engineer Background Rebar is building the next-generation operating system for commercial HVAC, electrical, and plumbing suppliers and subcontractors. Over the past year, our ...

We're hiring a Senior ML Infrastructure Engineer to build and own the infrastructure that powers it -- from training models on tens of millions of patients and hundreds of millions of rows of claims ...

We're hiring a Senior ML Infrastructure Engineer to build and own the infrastructure that powers it - from training models on tens of millions of patients and hundreds of millions of rows of claims ...

Senior ML Infrastructure Engineer

Manhattan, NY · On-site

$119K - $162K/yr

As a Senior ML Infrastructure Engineer, you will own the data infrastructure that supports underwriting, claims, and operational workflows, ensuring reliable and scalable data pipelines for the ...

ML Infrastructure Engineer, Fauna

New York, NY · On-site

$117K - $154K/yr

We are seeking a Machine Learning Engineer to work directly alongside our research scientists to ... This is a hands-on ML role: you will train policies, debug convergence, run experiments in ...

ML Infrastructure Engineer, Fauna

New York, NY · On-site

$117K - $154K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

We are seeking a Machine Learning Engineer to work directly alongside our research scientists to ... This is a hands-on ML role: you will train policies, debug convergence, run experiments in ...

ML Infrastructure Engineer, Fauna

New York, NY · On-site

$117K - $154K/yr

We are seeking a Machine Learning Engineer to work directly alongside our research scientists to ... This is a hands-on ML role: you will train policies, debug convergence, run experiments in ...

ML Engineer, Infrastructure

New York, NY · On-site

$117K - $154K/yr

Build the developer productivity layer: CI pipelines, experiment tracking, model registry, data ... infrastructure or distributed training systems at scale. At a major AI lab, a well-funded ML ...

ML Engineer ## Key Responsibilities - Lead the end-to-end design, development, and deployment of ... ML infrastructure and data pipelines that support training, validation, and real-time inference ...

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

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

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Ml Infrastructure Engineer information

See Hackensack, NJ salary details

$50.7K

$138.6K

$198.5K

How much do ml infrastructure engineer jobs pay per year?

As of Aug 17, 2026, the average yearly pay for ml infrastructure engineer in Hackensack, NJ is $138,584.00, according to ZipRecruiter salary data. Most workers in this role earn between $117,200.00 and $153,800.00 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 Hackensack, NJ?

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

What cities near Hackensack, NJ are hiring for Ml Infrastructure Engineer jobs?

Cities near Hackensack, NJ with the most Ml Infrastructure Engineer job openings:

Infographic showing various Ml Infrastructure Engineer job openings in Hackensack, NJ as of June 2026, with employment types broken down into 96% Full Time, 2% Part Time, and 2% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $138,584 per year, or $66.6 per hour.

Senior ML Infrastructure Engineer

Rebar

New York, NY • On-site

$118K - $161K/yr

Full-time

Medical, Dental, Vision

Re-posted 20 days ago


Job description

Senior ML Infrastructure Engineer
Background
Rebar is building the next-generation operating system for commercial HVAC, electrical, and plumbing suppliers and subcontractors. Over the past year, our V1 quoting product has scaled to thousands of quotes completed weekly, doubled revenue in 2026, and gained adoption across many of the top suppliers in North America. Fresh off a $14M Series A backed by leading construction tech investors, we're entering our next phase of growth - with AI at the center of everything we build next.
We're looking for a Senior ML Infrastructure Engineer to build the platform our ML engineers depend on to rapidly iterate, experiment, and ship models - spanning feature pipelines, training infrastructure, evaluation, deployment, and monitoring. You'll be joining a small, highly capable team focused on delivering practical, production-ready ML systems in a fast-moving startup context.
This role is ideal for someone who enjoys designing clean abstractions, integrating disparate systems into coherent platforms, and obsessing over the developer experience of the engineers they support. Our work spans the full ML lifecycle, and we're building the platform that makes it all hang together.
Responsibilities
Platform & Developer Experience: Design and build the CLI, SDK, and services that serve as the single front door to our ML platform. Make launching a training job, tracking an experiment, or shipping a model feel like one coherent product.
Infrastructure Integration: Wire together our cloud and SaaS stack - compute providers, storage, experiment tracking, model serving - into a unified system, codified as version-controlled infrastructure-as-code. Own the abstractions for compute orchestration, feature store, model registry, and model deployment.
Observability & Operations: Build cost attribution, usage dashboards, and monitoring across the platform. Surface what's running where, catch problems early, and keep production model serving - across detection, segmentation, recognition, and LLM/VLM workloads - reliable and cost-efficient at scale.
Collaboration and Roadmap: Work closely with ML engineers to understand their workflows, turn one-off scripts into self-serve platform features, and participate in architecture and roadmap decisions.
What We're Looking For
You should feel confident designing developer-facing APIs and SDKs, integrating disparate cloud and SaaS services into coherent systems, and obsessing over the experience of the engineers who use what you build.
We're seeking someone with strong platform-engineering instincts who enjoys turning fragmented workflows into products teams actually want to use. This role is a great fit if you have taste in abstractions, opinions about developer experience, and a track record of making ML or data teams meaningfully more productive.
Required Qualifications
  • Bachelor's degree or higher in Computer Science, Electrical Engineering, or other relevant field - or equivalent industry experience.
  • 3+ years of experience building production backend systems, with significant time on internal developer platforms, ML platforms, or integration-heavy infrastructure work.
  • Expert-level Python; comfortable picking up other languages as the tooling demands.
  • 2+ years of experience with cloud infrastructure (AWS preferred), including IAM, networking, and cost management.
  • Proficiency with infrastructure-as-code (IaC) tooling such as Terraform, AWS CDK, or Pulumi for managing reproducible, version-controlled cloud environments.
  • Hands-on experience with managed ML inference and serving platforms such as AWS SageMaker and GCP Vertex AI.
  • A proven track record operating inference at large scale across a range of model types - detection, segmentation, recognition, and LLM/VLM workloads.
  • Experience managing a model zoo / model registry - versioning, promotion, and governance of models from experiment to production.
  • Proven ability to design clean, composable APIs and SDKs that internal users adopt willingly.
  • Deep understanding of ML related workflows and requirements.

Nice to Have
  • Experience integrating common ML tooling - experiment trackers (W&B, MLflow), feature stores, model serving frameworks - into broader platforms.
  • Experience with DAG / workflow orchestration frameworks such as Temporal, Prefect, or Apache Airflow.
  • Built a Backstage-style internal developer portal or comparable internal platform.
  • Familiarity with GPU compute providers (AWS, Lambda Labs, CoreWeave, RunPod).
  • Some ML practitioner background - you've trained or deployed models yourself and understand the workflow from the user's side.
  • Experience with deployment and monitoring pipelines for ML systems.

Compensation and Benefits
  • Salary: Competitive
  • Equity: Meaningful equity package, commensurate with experience
  • Benefits: Comprehensive medical, dental, and vision coverage
  • Perks: Free lunches and dinners provided

This is a salaried, onsite role located in New York City's beautiful Flatiron district, just minutes away from Madison Square Park and Union Square. Working onsite offers invaluable opportunities for real-time collaboration, creative problem-solving, and building strong connections within our talented and dynamic team. You'll be at the heart of our fast-paced operations, actively contributing to a culture that values engagement, growth, and teamwork.