Machine Learning Engineer
Denver, CO · Remote
Good understanding of Machine Learning fundamentals such as Deep Neural Networks, Transformer-based ... remote environment.
Machine Learning Engineer
Denver, CO · Remote
Good understanding of Machine Learning fundamentals such as Deep Neural Networks, Transformer-based ... remote environment.
Apply Large Language Models (LLMs) to a variety of applications within remote sensing such as ... Applying clustering algorithms and/or deep neural networks to real life problems * Implementing ...
Apply Large Language Models (LLMs) to a variety of applications within remote sensing such as ... Applying clustering algorithms and/or deep neural networks to real life problems * Implementing ...
Apply Large Language Models (LLMs) to a variety of applications within remote sensing such as ... Applying clustering algorithms and/or deep neural networks to real life problems * Implementing ...
Apply Large Language Models (LLMs) to a variety of applications within remote sensing such as ... Applying clustering algorithms and/or deep neural networks to real life problems * Implementing ...
Machine Learning Engineer
Denver, CO · Remote
$127.60K - $159.50K/yr
Goodunderstanding of Machine Learning fundamentals such as Deep Neural Networks, Transformer-based ... Remote, US Salary Range $101,200--$150,000 USD New York, NY Salary Range $127,600--$159,500 USD ...
Machine Learning Engineer
Denver, CO · Remote
$127.60K - $159.50K/yr
Goodunderstanding of Machine Learning fundamentals such as Deep Neural Networks, Transformer-based ... Remote, US Salary Range $101,200--$150,000 USD New York, NY Salary Range $127,600--$159,500 USD ...
Machine Learning Engineer
Denver, CO · Remote
$127.60K - $159.50K/yr
Goodunderstanding of Machine Learning fundamentals such as Deep Neural Networks, Transformer-based ... Remote, US Salary Range $101,200--$150,000 USD New York, NY Salary Range $127,600--$159,500 USD ...
Machine Learning Engineer
Denver, CO · Remote
$127.60K - $159.50K/yr
Goodunderstanding of Machine Learning fundamentals such as Deep Neural Networks, Transformer-based ... Remote, US Salary Range $101,200--$150,000 USD New York, NY Salary Range $127,600--$159,500 USD ...
Machine Learning Engineer
Denver, CO · On-site +1
$127.60K - $159.50K/yr
Good understanding of Machine Learning fundamentals such as Deep Neural Networks, Transformer-based ... Remote, US Salary Range $101,200-$150,000 USD New York, NY Salary Range $127,600-$159,500 USD ...
Machine Learning Engineer
Denver, CO · On-site +1
$127.60K - $159.50K/yr
Good understanding of Machine Learning fundamentals such as Deep Neural Networks, Transformer-based ... Remote, US Salary Range $101,200-$150,000 USD New York, NY Salary Range $127,600-$159,500 USD ...
Apply Large Language Models (LLMs) to a variety of applications within remote sensing such as ... Applying clustering algorithms and/or deep neural networks to real life problems * Implementing ...
Apply Large Language Models (LLMs) to a variety of applications within remote sensing such as ... Applying clustering algorithms and/or deep neural networks to real life problems * Implementing ...
Apply Large Language Models (LLMs) to a variety of applications within remote sensing such as ... Applying clustering algorithms and/or deep neural networks to real life problems * Implementing ...
Apply Large Language Models (LLMs) to a variety of applications within remote sensing such as ... Applying clustering algorithms and/or deep neural networks to real life problems * Implementing ...
Apply Large Language Models (LLMs) to a variety of applications within remote sensing such as ... Applying clustering algorithms and/or deep neural networks to real life problems * Implementing ...
Apply Large Language Models (LLMs) to a variety of applications within remote sensing such as ... Applying clustering algorithms and/or deep neural networks to real life problems * Implementing ...
Apply Large Language Models (LLMs) to a variety of applications within remote sensing such as ... Applying clustering algorithms and/or deep neural networks to real life problems * Implementing ...
Apply Large Language Models (LLMs) to a variety of applications within remote sensing such as ... Applying clustering algorithms and/or deep neural networks to real life problems * Implementing ...
Principal AI/ML Engineer (Large Language Model) (TS/SCI) {S} with Security Clearance
Aurora, CO · Remote
Apply Large Language Models (LLMs) to a variety of applications within remote sensing such as ... Applying clustering algorithms and/or deep neural networks to real life problems * Implementing ...
Principal AI/ML Engineer (Large Language Model) (TS/SCI) {S} with Security Clearance
Aurora, CO · Remote
Apply Large Language Models (LLMs) to a variety of applications within remote sensing such as ... Applying clustering algorithms and/or deep neural networks to real life problems * Implementing ...
Remote Neural Engineer information
What are the key skills and qualifications needed to thrive as a Remote Neural Engineer, and why are they important?
To thrive as a Remote Neural Engineer, you need a solid background in neuroscience, biomedical engineering, or electrical engineering, often supported by a relevant degree or advanced certification. Proficiency with neural signal processing software, programming languages like Python or MATLAB, and brain-computer interface (BCI) systems is typically required. Strong problem-solving skills, attention to detail, and effective virtual communication are vital soft skills in this role. These skills and qualities are essential for developing, analyzing, and troubleshooting complex neural systems while collaborating with teams remotely.
How do Remote Neural Engineers typically collaborate with cross-functional teams while working off-site?
Remote Neural Engineers frequently use digital collaboration tools such as video conferencing, shared code repositories, and project management platforms to stay connected with colleagues in neuroscience, software development, and data science. Regular virtual meetings and asynchronous communication help ensure alignment on project goals, data analysis, and protocol development. This structure allows for flexibility, but also requires proactive communication and strong organizational skills to manage complex, interdisciplinary tasks from a distance.
What is a Remote Neural Engineer?
A Remote Neural Engineer is a professional who designs, develops, and maintains neural engineering systems—such as brain-computer interfaces or neural prosthetics—while working remotely. They often collaborate with multidisciplinary teams to create solutions that interface with the nervous system, using expertise in neuroscience, biomedical engineering, and software development. Remote Neural Engineers may work from home or distributed locations, utilizing digital tools to analyze neural data, develop algorithms, and contribute to research or product development in the neural technology field.
What is the difference between Remote Neural Engineer vs Remote Data Scientist?
| Aspect | Remote Neural Engineer | Remote Data Scientist |
|---|---|---|
| Required Credentials | Degree in neuroscience, biomedical engineering, or related fields; knowledge of neural interfaces | Degree in computer science, statistics, or related fields; proficiency in data analysis |
| Work Environment | Research labs, tech companies, healthcare institutions with focus on neural data | Tech firms, finance, healthcare, analyzing large datasets |
| Industry Usage | Neuroscience, biomedical engineering, neurotechnology | Technology, finance, healthcare, research |
| Common Search/Comparison | Yes | Yes |
Remote Neural Engineers focus on developing and implementing neural interfaces and understanding neural systems, often requiring knowledge of neuroscience and biomedical engineering. Remote Data Scientists analyze large datasets to extract insights, typically with skills in statistics and programming. While both roles involve technical expertise and data analysis, Neural Engineers are more specialized in neural technologies, whereas Data Scientists have a broader application across industries.
What are popular job titles related to Remote Neural Engineer jobs in Colorado? For Remote Neural Engineer jobs in Colorado, the most frequently searched job titles are:
What job categories do people searching Remote Neural Engineer jobs in Colorado look for? The top searched job categories for Remote Neural Engineer jobs in Colorado are:
What cities in Colorado are hiring for Remote Neural Engineer jobs? Cities in Colorado with the most Remote Neural Engineer job openings:
Other
Posted 19 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.