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Senior Embedded Machine Learning Jobs in New York

ExaCare AI

Senior Machine Learning Engineer

Manhattan, NY · On-site

$100 - $140/hr

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

DailyPay

Senior Machine Learning Engineer

Manhattan, NY · On-site

$115K - $158K/yr

They are seeking a Senior Machine Learning Engineer to enhance their machine learning infrastructure and collaborate with cross-functional teams to deliver impactful ML solutions. Responsibilities ...

AvePoint

Senior Machine Learning Engineer

New York, NY · On-site

$190K - $220K/yr

We are seeking an analytical and innovative Senior Machine Learning Engineer to join our Data & AI team. You will play a key role in developing and deploying advanced machine learning models to solve ...

Clearview AI

Senior Machine Learning Engineer

Manhattan, NY · On-site

$115K - $158K/yr

Senior Machine Learning Engineer Department: Engineering Employment Type: Full Time Location: New York, NY Description Clearview AI is the leading provider of facial recognition technologies to US ...

AvePoint

Senior Machine Learning Engineer

New York, NY · On-site

$190K - $220K/yr

We are seeking an analytical and innovative Senior Machine Learning Engineer to join our Data & AI team. You will play a key role in developing and deploying advanced machine learning models to solve ...

Capital One

Sr. Lead Machine Learning Engineer

New York, NY · On-site +1

$112K - $147K/yr

Sr. 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.

Affinity

Senior Machine Learning Engineer

New York, NY · On-site

$114K - $157K/yr

As a Senior Machine Learning Engineer , you will collaborate with data engineers, software engineers, and product managers to shape the future of private capital's leading CRM platform. You will ...

Attentive

Senior Machine Learning Engineer

New York, NY · On-site

$244K - $320K/yr

As a Senior Machine Learning Engineer, you will play a critical role in building, scaling, and operating production-grade ML systems that drive real-time personalization across the Attentive platform.

DailyPay

Senior Machine Learning Engineer

New York, NY · On-site

$190K - $250K/yr

We are seeking a Senior Machine Learning Engineer to join our AI & ML team in New York City. You will play a key role in maturing and scaling our machine learning infrastructure, ensuring the ...

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Senior Embedded Machine Learning information

What does a senior embedded machine learning engineer do?

A Senior Embedded Machine Learning engineer designs, develops, and optimizes machine learning models to run efficiently on resource-constrained embedded devices such as microcontrollers, IoT devices, and edge hardware. They are responsible for integrating ML algorithms with embedded systems, ensuring low latency and minimal power consumption. Their work often involves collaborating with hardware engineers and software developers to deploy intelligent features in products like smart sensors, wearables, and autonomous systems.

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

To thrive as a Senior Embedded Machine Learning Engineer, you need expertise in embedded systems, machine learning algorithms, and programming languages like C/C++ and Python, often backed by an advanced degree in computer science or electrical engineering. Familiarity with tools such as TensorFlow Lite, ONNX, and embedded hardware platforms (e.g., ARM Cortex-M, NVIDIA Jetson) is typically required. Strong problem-solving, project management, and communication skills distinguish top performers in this role. These capabilities are crucial for efficiently deploying optimized machine learning models on resource-constrained devices and effectively collaborating across multidisciplinary teams.

What are some common challenges faced by senior embedded machine learning engineers when deploying models on edge devices?

Senior Embedded Machine Learning Engineers often encounter challenges such as optimizing model size and inference speed to fit within the limited computational resources and memory of edge devices. Balancing accuracy and performance while minimizing power consumption is critical, especially for battery-operated products. Additionally, integrating models with existing embedded software and ensuring reliable, real-time operation can require close collaboration with hardware and firmware teams. Staying current with advancements in model compression and hardware acceleration is also essential for success in this role.

What is the difference between Senior Embedded Machine Learning vs Embedded Software Engineer?

AspectSenior Embedded Machine LearningEmbedded Software Engineer
Required CredentialsBachelor's/Master's in CS, EE, or related; experience in ML and embedded systemsBachelor's in CS, EE, or related; strong programming skills in C/C++
Work EnvironmentDeveloping ML models for embedded devices, hardware integrationDesigning and implementing embedded software for devices
Industry UsageAI/ML-focused companies, IoT, consumer electronicsAutomotive, industrial, consumer electronics

While both roles involve embedded systems, Senior Embedded Machine Learning focuses on integrating ML models into hardware, requiring knowledge of AI and data science. Embedded Software Engineers primarily develop software for embedded devices, emphasizing firmware and system-level programming. The roles overlap in embedded environment skills but differ in their core focus on AI versus traditional software development.

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

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

What cities in New York are hiring for Senior Embedded Machine Learning jobs?

Cities in New York with the most Senior Embedded Machine Learning job openings:

Senior Embedded Machine Learning jobs near you

Senior Machine Learning Engineer

ExaCare AI

Manhattan, NY • On-site

$100 - $140/hr

Other

Medical, Dental, Vision, PTO

Re-posted 28 days ago

Job description

We are looking for a Senior 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
  • Several 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
  • 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
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