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Machine Learning Compiler Engineer Jobs in New York

exacare ai

Machine Learning Engineer

New York, NY · On-site

About the Role We are looking for a Machine Learning Engineer, MLOps to help operationalize and scale our machine learning systems. This is an engineering-focused role centered on building the ...

Capital One

Lead Machine Learning Engineer

New York, NY · On-site +1

$112K - $147K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

Arlo

Machine Learning Engineer

New York, NY · On-site

$180K - $230K/yr

Arlo's underwriting is the core of the business, and it runs on machine learning at serious scale. We're hiring ML Engineer to build and own the infrastructure that powers it - from training models ...

Arlo

Machine Learning Engineer

New York, NY · On-site

$180K - $230K/yr

Arlo's underwriting is the core of the business, and it runs on machine learning at serious scale. We're hiring ML Engineer to build and own the infrastructure that powers it -- from training models ...

Capital One

Lead Machine Learning Engineer

New York, NY · On-site +1

$112K - $147K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

WireScreen

Machine Learning Engineer

New York, NY · On-site

$150K - $195K/yr

As a Machine Learning Engineer at WireScreen, you will be working across our data systems to unlock the source of truth behind one of the world's economic powerhouses: China. This role is critical to ...

Capital One

Lead Machine Learning Engineer

New York, NY · On-site +1

$112K - $147K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

Capital One

Lead Machine Learning Engineer

New York, NY · On-site +1

$112K - $147K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

Good Inside

Machine Learning Engineer

New York, NY · On-site

$205K - $235K/yr

The Opportunity Good Inside is seeking a Machine Learning Engineer to join our Engineering team. This is not a research or data science role - we're looking for a strong backend engineer who has ...

PROPRIUS

Senior Machine Learning Engineer

New York, NY

$114K - $157K/yr

Sr. Machine Learning Engineer Location: New York, NY Sponsorship: Yes Relocation: Yes Industry: Machine Learning A leading provider of AI is looking for a Sr. ML Engineer. Our client is an industry ...

Attentive

Senior Machine Learning Engineer

New York, NY · On-site

$244K - $320K/yr

About the Role Our Machine Learning Engineering team powers personalized experiences for hundreds of millions of customers across thousands of brands. As a Senior Machine Learning Engineer, you will ...

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All JobsMachine Learning Compiler Engineer JobsMachine Learning Compiler Engineer Jobs in New York

Machine Learning Compiler Engineer information

See New York salary details

$34.5K

$140.9K

$211.7K

How much do machine learning compiler engineer jobs pay per year?

As of Sep 2, 2026, the average yearly pay for machine learning compiler engineer in New York is $140,878.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,000.00 and $169,600.00 per year, depending on experience, location, and employer.

What is a machine learning compiler engineer?

A Machine Learning Compiler Engineer focuses on optimizing and building compilers that translate high-level machine learning models into efficient code runnable on specialized hardware (e.g., GPUs, TPUs). They work on improving performance, memory usage, and execution efficiency of ML workloads by designing compiler optimizations, code generation techniques, and leveraging frameworks like LLVM or MLIR. Their role bridges the gap between ML researchers and hardware engineers, ensuring models run efficiently on target platforms.

What are the typical daily responsibilities of a machine learning compiler engineer?

As a Machine Learning Compiler Engineer, your daily responsibilities often include designing and implementing new compiler optimizations, collaborating with machine learning researchers to support model deployment, and debugging performance or correctness issues in compiled code. You may participate in code reviews, write technical documentation, and conduct benchmarking to evaluate how machine learning models perform on various hardware backends. Close collaboration with hardware engineers, software architects, and data scientists is common, ensuring end-to-end solutions meet both research and production requirements. Staying updated with the latest advancements in both compiler technology and machine learning frameworks is also a key aspect of the role.

What are the key skills and qualifications needed to thrive as a machine learning compiler engineer?

A Machine Learning Compiler Engineer needs a deep understanding of computer science fundamentals, compiler theory, and experience with machine learning frameworks, often supported by a relevant degree in computer science or engineering. Proficiency with tools such as LLVM, TVM, MLIR, and languages like C++, Python, and CUDA is typically required, and familiarity with hardware architectures is a plus. Strong problem-solving, teamwork, and communication skills are essential for collaborating with cross-functional teams and addressing complex system issues. These capabilities are important for designing and optimizing compilers that enable scalable and efficient deployment of machine learning models on diverse hardware platforms.

What are the most commonly searched types of Machine Learning Compiler Engineer jobs in New York?

The most popular types of Machine Learning Compiler Engineer jobs in New York are:

What are popular job titles related to Machine Learning Compiler Engineer jobs in New York?

For Machine Learning Compiler Engineer jobs in New York, the most frequently searched job titles are:

What job categories do people searching Machine Learning Compiler Engineer jobs in New York look for?

The top searched job categories for Machine Learning Compiler Engineer jobs in New York are:

Machine Learning Compiler Engineer jobs near you
Infographic showing various Machine Learning Compiler Engineer job openings in New York as of August 2026, with employment types broken down into 1% As Needed, 79% Full Time, 19% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $140,878 per year, or $67.7 per hour.

Machine Learning Engineer

exacare ai

New York, NY • On-site

Full-time

Medical, Dental, Vision, PTO

Re-posted 7 days ago

Job description

About the Role
We are looking for a Machine Learning Engineer, MLOps to help operationalize and scale our machine learning systems. This is an engineering-focused role centered on building the workflows, infrastructure, and processes that enable ML to move from research into reliable production systems.
You will partner closely with research-oriented ML teammates and help turn their work into scalable, maintainable, and cost-effective production systems. This includes building and improving data pipelines, training pipelines, deployment workflows, monitoring systems, and supporting infrastructure that allow the team to move faster and operate ML systems with confidence.
This is not a research-first role. It is best suited for someone who is excited by the systems, tooling, and operational side of machine learning.
What You'll Do
  • Build and maintain the workflows and infrastructure that support the end-to-end ML lifecycle
  • Partner with researchers and ML practitioners to productionize models and enable faster iteration
  • Design, build, and improve data pipelines and training pipelines
  • Improve data processing, annotation workflows, and ML system efficiency
  • Deploy and maintain the background systems that support model training and inference
  • Build tooling and processes for monitoring model performance, system reliability, and operational health
  • Improve the scalability, observability, and reproducibility of ML systems
  • Optimize ML infrastructure for speed, reliability, and cost-efficiency
  • Identify bottlenecks in the ML workflow and automate or streamline manual processes
  • Help establish best practices around ML operations, deployment, and system performance

What You'll Bring
  • Proven (3+ years) of experience in machine learning engineering, MLOps, ML infrastructure, data engineering, or backend/platform engineering in ML environments
  • Experience supporting ML systems end to end, from model handoff through deployment and monitoring
  • Strong experience building and owning data pipelines, training pipelines, or other production workflows that support ML
  • Experience working closely with researchers, data scientists, or ML practitioners to productionize models
  • Strong software engineering fundamentals and experience building production systems
  • Experience with monitoring, debugging, and improving production ML or data systems
  • A track record of improving reliability, scalability, speed, and/or cost efficiency in ML systems
  • Comfort operating in a fast-moving, startup-style environment with a high degree of ownership

Benefits + Perks
  • Competitive salary and equity in a high-growth startup
  • Flexible PTO, take what you need
  • Medical, dental, and vision coverage
  • Great startup culture, including company off-sites
  • High-achieving team, including ex-Amazon engineers and alumni of Bain, BCG, Goldman Sachs, and more

An insight into our Core Values
Only the best belong here
We are unapologetic about talent. This should be the best team you have ever been on. Protecting that standard is how we honor each other's time, ambition, and craft.
We work even harder to keep our partners than we did to earn them initially
The work does not stop when a customer first onboards to our platform. It deepens over time. We partner with operators, listening and learning about real problems, and translate that into solutions that help them succeed in practice. We earn trust through consistent delivery.
We keep the patient downstream of every decision
At the end of the day, this is about the patient. We get there by deeply respecting and reflecting on our purpose: to develop software that aids teams in delivering better care.
Raise the bar on ownership
We grow because people here go beyond the minimum. We invest extra effort, care, and ownership into what we build.
The world is moving fast. We move faster.
This is a race. We work hard, we move early, and we stay ahead of problems and competitors. If we slow down, someone else will pass us.
Radical candor, zero politics
We say what's true, early, and we keep communication direct and clean so the team can move.
Bring good vibes and win together
We win as a team. We bring energy, support each other, and make the workplace somewhere people are excited to show up.
If this sounds like you, we'd love to have a chat!
#LI-Hybrid
About exacare ai
exacare ai is a leading health tech company on a mission to build the AI operating system for post-acute care. Our platform turns messy, unstructured referral packets into clear clinical insights and next steps, so teams can make faster, safer placement decisions with less administrative burden. Today, exacare ai powers more than 2,000 facilities, and is growing rapidly.
We recently raised a $30M Series A led by Insight Partners, and are bringing world-class talent together to transform healthcare. If you like building, learning, and want to make a real impact, come join us!

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