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Remote Embedded Machine Learning Jobs in Colorado

$228K - $253K/yr

Ibotta is seeking a Principal Machine Learning Engineer to join our Core Data & Analytics team and ... Remote options are available for the following states - AZ, AR, CA, FL, GA, IL, IN, IA, KS, MD, MA ...

$206K - $230K/yr

Ibotta is seeking a Staff Machine Learning Engineer to join our Core Data & Analytics team and ... Remote options are available for the following states - AZ, AR, CA, FL, GA, IL, IN, IA, KS, MD, MA ...

Sr. Machine Learning Engineer

Denver, CO · Remote

$107.60K - $147.70K/yr

Assistant : a GenAI copilot embedded across the product experience * Flows: an agentic workflow ... Who we are looking for We're seeking a Sr Machine Learning Engineer to play a critical role in ...

Sr. Machine Learning Engineer

CO · Remote

$107.60K - $147.70K/yr

Assistant: a GenAI copilot embedded across the product experience * Flows: an agentic workflow ... Who we are looking for We're seeking a Sr Machine Learning Engineer to play a critical role in ...

Senior Machine Learning Engineer I // II

Denver, CO · On-site +1

$107.60K - $147.70K/yr

The Senior Machine Learning Engineer will join our ML team. This team is responsible for building ... learning. #LI-Remote Benefits in our US offices: * Discretionary Time Off Policy (Unlimited ...

... machine learning, building a robot for school or prototyping your first (or tenth) product. No ... All embedded software is open source and community driven. SparkFun developed technology is given ...

Sr. Machine Learning Software Engineer

Denver, CO · On-site +1

$126.10K - $166.20K/yr

While we are mostly a remote company, travel is required for some team meetings and cross function ... About the Opportunity We are seeking a senior machine learning software engineer to design, build ...

... embedded into daytoday operations. This leader will own the endtoend Data science & AI portfolio ... Build and scale enterprise AI and machine learning capabilities across supply chain functions ...

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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 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 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 popular job titles related to Remote Embedded Machine Learning jobs in Colorado? For Remote Embedded Machine Learning jobs in Colorado, the most frequently searched job titles are:

Machine Learning Engineer

Judi Health

Denver, CO • Remote

Other

Posted 20 days ago


Job description

Position Summary: 

Join our mission to infuse cutting-edge AI/ML/GenAI into pharmacy benefits as a Machine Learning Engineer.  We are looking for a software engineer with machine learning expertise to join us in expanding our AI capabilities, enabling increased productivity and magical experiences in our products and services. 

In this role you will be expected to design and implement complex AI systems that leverage ML models for NLP, NLG, multimodal data analysis, chatbots, and RAG-based QnA. The ideal candidate should be passionate about applying AI/ML concepts to difficult problems and develop scalable solutions. We want people who like working in a collaborative team environment and enjoy creating practical, efficient, and high-performance software that leverages Large Language Models (LLM), Multimodal Language Models(MLM), and other ML models and techniques to build amazing capabilities for our customers, partners, and employees. Most importantly, we are a mission-oriented, high-growth startup and we are looking for folks that are excited to be part of our journey to make lasting impact towards transforming healthcare. 

Responsibilities: 

  • Develop and productionize machine learning (ML) solutions in the fields of Document understanding, Search and QnA, GenAI, Virtual Agents, etc. 
  • Develop and maintain backend services using Python, focusing on AI-driven applications. 
  • Design and implement APIs for seamless integration with AI models and services. 
  • Develop tools for large-scale data processing and ETL and contribute to extracting insights from data to help guide ML systems development 
  • Participate in code reviews, testing, and quality assurance processes. 
  • Troubleshoot and resolve technical issues related to AI model, integration, deployment and backend services. 
  • Develop algorithms to ensure the integrity and robustness of ML solutions by developing automated testing and validation processes. 
  • Document and communicate development processes and implementation details with peers and supervisors 
  • Ensure the security and compliance of healthcare data, adhering to HIPAA regulations. 

Required Qualifications: 

  • Bachelor's or Master's degree in Computer Science, Machine Learning, or a related quantitative field. 
  • 2+ years experience in the industry with a strong focus on ML solutions development and production deployment is a plus. 
  • Good understanding of Machine Learning fundamentals such as Deep Neural Networks, Transformer-based LLM and MLMs, Boosted or standard decision trees, RAG, etc.  
  • Strong grasp of OOP, Design Patterns, efficient algorithms, and quality software development. 
  • Proficiency in Python and familiarity with ML libraries such as PyTorch. 
  • Familiarity with GenAI services such as OpenAI GPT, Anthropic Claude, Google Gemma etc. Some experience in developing and fine-tuning prompts on any of the GenAI services is a plus. 
  • Excellent problem-solving skills, attention to detail, and a strong capacity for logical thinking. 
  • The ability to work collaboratively across multiple disciplines in an extremely fast-paced, startup environment. 
  • Good written communication skills that enable collaboration in a remote environment.