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Remote Embedded Machine Learning Jobs in Texas (NOW HIRING)

Machine Learning Engineer

Addison, TX ยท On-site +1

$110K - $130K/yr

Flexible work options, including remote and hybrid opportunities, if eligible * Retirement Plan ... machine learning solutions on the Snowflake Cloud data warehouse platform using the Snowpark ...

We are looking for a Machine Learning Engineer to help us design and deliver CX solutions that provide our clients with a beautiful customer journey that achieves results. At PTP we value aptitude ...

Senior Machine Learning Engineer

Austin, TX ยท On-site +1

$121K - $160K/yr

The Role As a Senior Machine Learning Engineer at Striveworks, you'll be challenged-and trusted-on ... Opportunities to conduct mission-critical field work This position offers a fully remote work ...

The Role As a Staff Machine Learning Engineer at Striveworks, you will be challenged-and trusted-on ... This position offers a fully remote work environment, or you can work hybrid/on site at our office ...

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Remote Embedded Machine Learning information

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

To thrive as a Remote Embedded Machine Learning Engineer, you need a solid background in embedded systems, machine learning algorithms, and programming languages like C/C++ and Python, often supported by a degree in computer science, electrical engineering, or related fields. Familiarity with microcontrollers, edge AI frameworks (such as TensorFlow Lite or Edge Impulse), and version control systems is typically required. Strong problem-solving skills, effective communication, and self-motivation are essential soft skills for collaborating remotely and troubleshooting complex issues. These skills ensure successful deployment of intelligent solutions on resource-constrained devices and effective teamwork in distributed environments.

What is a Remote Embedded Machine Learning Engineer?

A Remote Embedded Machine Learning Engineer is a professional who develops and deploys machine learning models on embedded systems like microcontrollers, IoT devices, and edge hardware, all while working remotely. Their work involves optimizing algorithms to run efficiently on devices with limited computing power, memory, and battery life. These engineers typically use frameworks such as TensorFlow Lite or TinyML to design intelligent features that operate directly on hardware, enabling real-time decision-making without relying heavily on cloud connectivity. They collaborate with cross-functional teams and often troubleshoot both software and hardware issues from a remote location.

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

AspectRemote Embedded Machine LearningRemote Data Scientist
Required CredentialsBachelor's or Master's in Computer Science, Electrical Engineering, or related fields; experience with embedded systems and ML frameworksBachelor's or Master's in Data Science, Statistics, or related fields; proficiency in data analysis and ML algorithms
Work EnvironmentEmbedded hardware devices, IoT systems, real-time processing environmentsCloud platforms, data analysis labs, remote offices
Employer & Industry UsageTech companies, IoT device manufacturers, automotive, roboticsFinance, healthcare, marketing, tech firms

Remote Embedded Machine Learning specialists focus on integrating ML models into embedded hardware for real-time applications, often working with IoT and robotics. In contrast, Remote Data Scientists analyze large datasets to extract insights, primarily working in cloud or office environments. Both roles require strong analytical skills but differ in technical focus and work settings.

What are some common challenges faced by Remote Embedded Machine Learning Engineers, and how can they be addressed?

Remote Embedded Machine Learning Engineers often encounter challenges related to hardware access, debugging embedded devices remotely, and collaborating with cross-functional teams across time zones. To address these, it's important to set up robust remote development environments, use simulation tools when physical hardware isn't available, and establish clear communication channels for effective teamwork. Regular virtual meetings and detailed documentation also help ensure alignment and smooth progress, despite the remote nature of the work.
What are the most commonly searched types of Embedded Machine Learning jobs in Texas? The most popular types of Embedded Machine Learning jobs in Texas are:
What are popular job titles related to Remote Embedded Machine Learning jobs in Texas? For Remote Embedded Machine Learning jobs in Texas, the most frequently searched job titles are:
What cities in Texas are hiring for Remote Embedded Machine Learning jobs? Cities in Texas with the most Remote Embedded Machine Learning job openings:
Machine Learning Engineer

Machine Learning Engineer

Confie

Addison, TX โ€ข On-site, Remote

$110K - $130K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 28 days ago


Job description

Pay Range:
  • $110000 - $130000 / year

Our Perks & Benefits:_
  • Comprehensive benefits package including medical, dental, vision, and life insurance
  • Performance-based bonuses to reward your contributions*
  • Paid time off to recharge and maintain a healthy work-life balance
  • Flexible work options, including remote and hybrid opportunities, if eligible
  • Retirement Plan (401k) with company-matched contributions
  • Education Advancement, for employees and qualified dependents, via the Confie Enablement Scholarship Fund
  • Fitness Reimbursement - up to $15/month for gym memberships
  • Inclusive workplace through a strong commitment to Diversity, Equity, and Inclusion
  • Employee Assistance Program - confidential support for personal or professional challenges, at no cost
  • Extra Perks - optional plans for disability, hospital indemnity, health advocate program, universal life, critical illness, accident insurance, and even pet insurance

Purpose
Work under the guidance and supervision of the Director, Enterprise Architecture to build supervised and unsupervised Artificial Intelligence (AI)/Machine Learning (ML) models
Essential Duties & Responsibilities
Research, analyze, support, and implement machine learning solutions on the Snowflake Cloud data warehouse platform using the Snowpark framework
Develop novel solutions using knowledge of the latest artificial intelligence/machine learning/natural language processing techniques and rigorous statistical analysis
Utilize LLMs and Generative AI to provide software automation capability integrations
Build and operationalize Retrieval Augmented Generation (RAG) frameworks
Enhance, develop, and deploy production-level machine learning models and algorithms that will improve Confie's business outcome/customer experience
Perform data cleansing, analysis, and feature engineering using Python
Ability to work with multiple data sources and types (structured/semi-structured/unstructured)
Assess the effectiveness and accuracy of new data sources and execute data-wrangling techniques
Participate and support other teams, as needed, for all aspects of model development, including design, model implementation, validation, calibration, documentation, product implementation, monitoring, and reporting
Communicate technical results in a clear, concise, and effective manner with emphasis on data visualization techniques
Collaborate with Data Scientists, Data Engineers, and Data Architects on production systems and applications
Stay up-to-date with industry trends and advancements in artificial intelligence/machine learning
On call support
Qualifications and Education Requirements
Master's degree in a quantitative/applied field (Engineering, Computer Science, Data Science, Operations Research, Mathematics, Statistics, Econometrics)
Expertise in manipulating and analyzing large data (e.g. exploratory analysis, model fitting, and visualization)
Proficient SQL skills and experience working with large data sets (big data, IoT data)
Proficient with programming and modeling using Python
Knowledge of modeling in pre-training & fine tuning foundation LLM models
Knowledge of LangChain and sentence transformer frameworks
Knowledge of ChatGPT4 (or comparable models)
Experience applying current machine learning techniques
Knowledge of evolving data science concepts and best practices
Other Duties
This job description is not designed to cover or contain a comprehensive listing of activities, duties, or responsibilities that are required of the employee for this job. Duties, responsibilities, and activities may change at any time with or without notice.
Notice
As permitted by applicable law and from time-to-time, Confie may use a computer system that has elements of artificial intelligence to help make decisions about your employment, including recruitment, hiring, renewal of employment, or the terms and conditions of your employment. Employees with questions about Confie's use of these computer systems should contact Human Resources at employeerelations@confie.com
Equal Opportunity Employer
This employer is required to notify all applicants of their rights pursuant to federal employment laws.
For further information, please review the Know Your Rights notice from the Department of Labor.

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About Confie

Sourced by ZipRecruiter

Industry

Insurance services

Company size

1,001 - 5,000 Employees

Headquarters location

Huntington Beach, CA, US

Year founded

2008