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Embedded Machine Learning Engineer Jobs in Houston, TX

Partner with executive leadership, engineering, product, and data science teams to ensure AI ... Solid proficiency in Python and deep learning frameworks (e.g., PyTorch, TensorFlow) * Experience ...

New

Senior AI Engineer

Houston, TX · On-site

$99.80K - $137K/yr

Design, develop, and deploy advanced AI and machine learning models to solve complex business ... Mentor junior engineers and provide technical guidance on AI best practices, model development, and ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

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Showing results 1-20

Embedded Machine Learning Engineer information

See Houston, TX salary details

$66.8K

$146.5K

$166.2K

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

As of May 30, 2026, the average yearly pay for embedded machine learning engineer in Houston, TX is $146,477.00, according to ZipRecruiter salary data. Most workers in this role earn between $125,600.00 and $165,200.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an Embedded Machine Learning Engineer, and why are they important?

To thrive as an Embedded Machine Learning Engineer, you need expertise in machine learning algorithms, embedded systems programming (C/C++ or Python), and a solid understanding of hardware constraints, usually supported by a degree in computer science, electrical engineering, or related fields. Familiarity with tools like TensorFlow Lite, ONNX, microcontroller SDKs, and experience with real-time operating systems (RTOS) are typically required. Strong problem-solving, communication skills, and the ability to collaborate across multidisciplinary teams help you stand out in this role. These skills are crucial for efficiently deploying intelligent models on resource-constrained devices, ensuring optimal performance and seamless integration in real-world applications.

What are some common challenges faced by Embedded Machine Learning Engineers when deploying models to hardware devices?

One of the main challenges for Embedded Machine Learning Engineers is optimizing machine learning models to run efficiently on devices with limited memory, processing power, and energy capacity. Ensuring real-time performance while maintaining accuracy often requires model quantization, pruning, or using lightweight architectures. Additionally, engineers must carefully manage hardware-software integration and address issues like compatibility with various microcontrollers and ensuring secure, reliable updates for deployed models. Close collaboration with hardware engineers and software developers is essential to overcome these challenges and deliver robust embedded AI solutions.

What does an Embedded Machine Learning Engineer do?

An Embedded Machine Learning Engineer designs and implements machine learning models that can run efficiently on embedded systems, such as microcontrollers and edge devices. Their work involves optimizing algorithms to fit within the resource constraints of these devices, integrating ML models into hardware, and ensuring real-time performance. They collaborate closely with hardware engineers and software developers to deploy intelligent features in products like smart sensors, IoT devices, and autonomous systems.

What is the difference between Embedded Machine Learning Engineer vs Firmware Engineer?

AspectEmbedded Machine Learning EngineerFirmware Engineer
Required CredentialsBachelor's/Master's in Computer Science, Electrical Engineering, or related; knowledge of ML frameworksBachelor's in Electrical Engineering, Computer Engineering, or related; embedded systems experience
Work EnvironmentDevelops ML models for embedded devices, often in IoT or smart devicesDesigns and implements low-level firmware for hardware devices
Industry UsageTech companies, IoT, consumer electronics, automotiveConsumer electronics, automotive, industrial equipment

The Embedded Machine Learning Engineer focuses on integrating machine learning models into embedded systems, while the Firmware Engineer specializes in developing low-level software for hardware devices. Both roles require embedded systems knowledge but differ in their core focus and skill sets.

What cities near Houston, TX are hiring for Embedded Machine Learning Engineer jobs? Cities near Houston, TX with the most Embedded Machine Learning Engineer job openings:
Machine Learning Engineer (PhD Intern)

Machine Learning Engineer (PhD Intern)

Instacart

The Woodlands, TX

Other

Posted 8 days ago


Instacart rating

6.7

Company rating: 6.7 out of 10

Based on 29 frontline employees who took The Breakroom Quiz


Job description

We're transforming the grocery industry

At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers.

Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table.

Instacart is a Flex First team

There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events.

Overview

Since 2012, Instacart has been focused on making grocery delivery convenient, affordable, and accessible to everyone. We bring fresh groceries and everyday essentials to customers across the US and Canada from nearly 55,000 stores across 5,500 markets. Our mission is to create a world where everyone has access to the food they love, and to achieve that goal, we innovate in a wide range of areas including e-commerce, advertising, and fulfillment.

We use machine learning and Internet-scale data to elevate customer experience, improve efficiency, and reduce cost. As an example, we manage catalog data imported from hundreds of retailers, and we build product and knowledge graphs on top of the catalog data to support a wide range of applications including search and ads.

We are looking for talented Ph.D. students to have an internship in our fast moving team. You will have the opportunity to work on a very large scope of problems in search, ads, personalization, recommendation, fulfillment, product and knowledge graph, pricing, etc.

About the Team:

This is a general posting for multiple intern roles open across our various ML teams. You can find a blurb on each team below:

Economics Team: The Economics team at Instacart works on a range of interesting and challenging problems, from aligning the incentives in our multi-sided marketplace to analyzing the role of prices and product placement in our customers' decision-making. Some of the core areas of focus for our team include pricing, online advertising, uplift and long term value modeling, and general causal inference.

Search & Discovery ML: The Search and Discovery ML team at Instacart works alongside world-class engineers, data scientists, and product managers to shape the future of search technology at Instacart. They collaborate on building models that enhance relevance of all shopping surfaces, ranking, and personalization, delivering highly relevant results to users across the Instacart ecosystem. As part of the Search and Discovery ML team, you'll work on one of the most critical aspects of the business, helping customers connect with the right products. We are passionate about solving large-scale search challenges and creating innovative solutions that elevate the customer experience. (Recent publications 1, 2, 3, 4, 5).

Content AI Team: The Content AI team at Instacart works alongside world-class engineers, data scientists, and product managers to advance generative AI, recommendations, and catalog intelligence in grocery ecommerce. We build cutting-edge AI models that power real-time recommendations, feed ranking, and automated content generation, ensuring high-quality and engaging customer experiences. Beyond recommendations, we leverage generative AI and LLMs to enhance and enrich Instacart’s catalog, driving AI-powered product understanding and content creation at scale. As part of Content AI, you'll work on high-impact AI solutions, applying LLMs, agentic systems, and computer vision to tackle complex challenges. We are passionate about pushing the boundaries of generative AI to shape the future of ecommerce. If you're excited about building state-of-the-art AI systems, we’d love to have you on board!

Past internship contributions include:

Tensor-based complementary recommendations, published at IEEE Big Data 2021 (Paper) Enhancing sequence-based recommendations for long-tail products (Blog)

About the Job

Based on your passion and background, you may choose to work in a few different areas:

  • Query understanding - Using cutting-edge NLP technologies to understand the intent of user queries.
  • Search relevance and ranking - Improving search relevance by incorporating signals from various sources.
  • Ads quality, pCTR, etc. - Improving ads revenue and ROAS.
  • Knowledge graphs - Working on graph data management and knowledge discovery, and creating a natural language interface for data access.
  • Fraud detection and prevention - Using cost sensitive learning to reduce loss.
  • Pricing - Estimating willingness-to-pay, and optimizing revenue and user experience.
  • Logistics - Optimization in a variety of situations, including supply/demand prediction, last mile delivery, in-store optimization, etc.

About You

Minimum Qualifications:

  • Ph.D. student in computer science, mathematics, statistics, economics, or related areas.
  • Strong programming (Python, C++) and algorithmic skills.
  • Good communication skills. Curious, willing to learn, self-motivated, hands-on.

Preferred Qualifications:

  • Ph.D. student at a top tier university in the United States
  • Prior internship/work experience in the machine learning space

Instacart provides highly market-competitive compensation and benefits in each location where our employees work. This role is remote and the base pay range for a successful candidate is dependent on their permanent work location. Please review our Flex First remote work policy here.

Offers may vary based on many factors, such as candidate experience and skills required for the role.


What Instacart employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


Instacart logo

About Instacart

Sourced by ZipRecruiter

Instacart, based in San Francisco, CA, US, operates within the retail industry, specifically grocery delivery and pick-up service. It is recognized as a pioneer in this field, delivering fresh groceries from local stores directly to customers' doors. The company, which launched its services in 2012, continues to pioneer change in the online grocery shopping sector through its commitment to cutting-edge technology, new business ideas, and dedicated service.

Industry

Technology, communication and media

Company size

10,000+ Employees

Headquarters location

San Francisco, CA, US

Year founded

2012