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Remote Machine Learning Compiler Engineer Jobs in Hoboken, NJ

Hang

Machine Learning Engineer

New York, NY · On-site +1

About the Role We are seeking a skilled and innovative Machine Learning Engineer to join our team. This person will implement and develop machine learning models to enhance our platform ...

Canals

Machine Learning Engineer

New York, NY · Remote

We're looking for a senior-level Machine Learning Engineer who can move quickly while maintaining ... We're remote-first, flexible, and distributed across North and South America, bringing together ...

Shaped

Senior Machine Learning Engineer

Brooklyn, NY · On-site +1

$130K - $200K/yr

We're remote but have an office in Brooklyn, New York. We are looking for a machine learning engineer to design, build, experiment and optimize Shaped's AI discovery engine. You will be a founding ...

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Remote Machine Learning Compiler Engineer information

See Hoboken, NJ salary details

$82.1K

$183.2K

$224.3K

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

As of Sep 8, 2026, the average yearly pay for remote machine learning compiler engineer in Hoboken, NJ is $183,191.00, according to ZipRecruiter salary data. Most workers in this role earn between $156,500.00 and $224,300.00 per year, depending on experience, location, and employer.

What is a remote machine learning compiler engineer?

A Remote Machine Learning Compiler Engineer is a software engineer who specializes in developing and optimizing compilers specifically for machine learning workloads, while working from a remote location. Their primary responsibilities include designing and implementing compiler features that translate machine learning models into efficient code for various hardware platforms, such as CPUs, GPUs, or specialized accelerators. They collaborate closely with machine learning researchers, hardware engineers, and software developers to ensure high performance and compatibility. In addition to strong programming skills, they typically require expertise in compiler theory, machine learning frameworks, and hardware architectures. This role allows for flexible, location-independent work while contributing to cutting-edge AI technologies.

How does a remote machine learning compiler engineer typically collaborate with cross-functional teams to optimize model deployment?

As a Remote Machine Learning Compiler Engineer, you will frequently collaborate with data scientists, hardware engineers, and software developers to ensure that machine learning models are efficiently compiled and deployed on target platforms. Communication often takes place through virtual meetings, code reviews, and shared documentation tools. You'll be responsible for translating research models into optimized code, troubleshooting performance bottlenecks, and integrating feedback from various stakeholders. Effective teamwork is crucial, as the success of deployments often depends on iterative feedback and close alignment with both the ML research and hardware teams.

What are the key skills and qualifications needed to thrive as a remote machine learning compiler engineer, and why are they important?

To thrive as a Remote Machine Learning Compiler Engineer, you need a strong background in computer science, proficiency in programming languages like C++ and Python, and expertise in compiler theory and machine learning frameworks. Familiarity with ML compilers such as TVM or XLA, and experience using version control and CI/CD systems are commonly required, along with a relevant bachelor's or master's degree. Outstanding problem-solving, collaboration, and communication skills are essential for working effectively in distributed teams and across technical domains. These skills and qualities enable the development of efficient, scalable ML solutions that bridge software and hardware, ensuring high performance and innovation.

What is the difference between Remote Machine Learning Compiler Engineer vs Remote Data Scientist?

AspectRemote Machine Learning Compiler EngineerRemote Data Scientist
Required CredentialsBachelor's or Master's in Computer Science, Software Engineering, or related fields; knowledge of compiler design and ML frameworksBachelor's or Master's in Data Science, Statistics, or related fields; proficiency in programming, statistics, and data analysis
Work EnvironmentPrimarily software development, compiler optimization, and ML model deploymentData analysis, model building, and interpretation of results
Industry UsageTech companies, AI startups, hardware firms focusing on ML hardware accelerationTech, finance, healthcare, and research organizations

While both roles involve working with machine learning, the Remote Machine Learning Compiler Engineer focuses on developing and optimizing compilers for ML models, whereas the Remote Data Scientist concentrates on analyzing data and building predictive models. The roles share some technical skills but differ in their core responsibilities and work environments.

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What cities near Hoboken, NJ are hiring for Remote Machine Learning Compiler Engineer jobs?

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Remote Machine Learning Compiler Engineer jobs near you

Machine Learning Engineer - Remote

YO AI Labs

New York, NY • Remote

Full-time

Posted 12 days ago

Job description

Machine Learning Engineer

Role Type: Contractor
Location: Remote

About the Role

We are looking for skilled Machine Learning Engineers to support AI training and evaluation projects. You'll use Python, machine learning, and data expertise to develop, evaluate, and improve ML solutions.

Key Responsibilities
  • Develop and refine machine learning models using Python.
  • Analyze and manage datasets using MongoDB.
  • Evaluate models, tune performance, and benchmark results.
  • Build data preprocessing and ML workflows.
  • Identify opportunities to improve model performance.
  • Document experiments, methodologies, and results.
Required Skills
  • Python
  • Machine Learning
  • MongoDB
  • Data Analysis & Preprocessing
  • Model Evaluation
  • Feature Engineering
Preferred Qualifications
  • Strong experience with Python and ML frameworks such as scikit-learn, TensorFlow, or PyTorch.
  • Hands-on MongoDB experience in ML or data projects.
  • Strong problem-solving and analytical skills.
  • Understanding of ML evaluation metrics and data modeling.
  • Experience deploying ML models in cloud or enterprise environments.
  • Strong technical documentation and communication skills.