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Remote Implementation Science Jobs in Colorado (NOW HIRING)

Tetra Tech

OT Network Project Technical Lead

Denver, CO · Remote

$104K - $144K/yr

... implementing defense-in-depth strategies, network segmentation, secure remote access, IDMZ ... Science, Automation Engineering, or a related technical discipline. * Minimum 7-10 years of ...

Pae

IMINT Analyst Expert

Aurora, CO · Remote

College degree must be in a relevant field such as remote sensing, Geospatial sciences, Relevant ... Procedure Compliance - Each employee must read, understand and implement the general and specific ...

SAIC

Principal Software Engineer

Colorado Springs, CO · On-site +1

$160K - $200K/yr

None Potential for Remote Work: ORA_ON_SITE Description SAIC is seeking an experienced Principal ... Participate in implementing cloud-native applications, web front ends, and scalable back ends using ...

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Remote Implementation Science information

What is the difference between Remote Implementation Science vs Remote Health Program Coordinator?

AspectRemote Implementation ScienceRemote Health Program Coordinator
Required CredentialsMaster's or PhD in public health, healthcare, or related fields; knowledge of research methodsBachelor's degree in health administration, public health, or related fields; experience in healthcare coordination
Work EnvironmentFocus on research, data analysis, and strategy development in healthcare settingsManage health programs, coordinate activities, and liaise with stakeholders remotely
Employer & Industry UsageAcademic institutions, research organizations, healthcare agenciesHospitals, clinics, public health departments

Remote Implementation Science professionals focus on applying research findings to improve healthcare practices through data analysis and strategy development. In contrast, Remote Health Program Coordinators manage and coordinate health programs, ensuring smooth operations and stakeholder communication. While both roles work remotely in healthcare, their core responsibilities and required qualifications differ significantly.

What are the most commonly searched types of Implementation Science jobs in Colorado?

The most popular types of Implementation Science jobs in Colorado are:

What are popular job titles related to Remote Implementation Science jobs in Colorado?

For Remote Implementation Science jobs in Colorado, the most frequently searched job titles are:

What job categories do people searching Remote Implementation Science jobs in Colorado look for?

The top searched job categories for Remote Implementation Science jobs in Colorado are:

What cities in Colorado are hiring for Remote Implementation Science jobs?

Cities in Colorado with the most Remote Implementation Science job openings:

Remote Implementation Science jobs near you
Infographic showing various Remote Implementation Science job openings in Colorado as of August 2026, with employment types broken down into 1% Internship, 1% As Needed, 73% Full Time, 22% Part Time, and 3% Contract. Highlights an 77% Physical, 3% Hybrid, and 20% Remote job distribution.

Principal Machine Learning Engineer

3B Staffing LLC

Denver, CO • Remote

Contractor

Posted 7 days ago

Job description

Principal Machine Learning Engineer

Location: Remote
Type: Contract-to-Hire
Experience: 6-12+ years
Education: Master's or PhD preferred

LLM/Generative AI, Multi-Agent AI (Planner/Executor, ReAct, Tool-Use), RAG, Embeddings, Retrieval Optimization, NLP, Transformers, Deep Learning, Model Fine-Tuning, PyTorch, Hugging Face, LangChain/LlamaIndex, Kubernetes, Vector Databases, ML Monitoring & Observability.

Core Stack: Python, PyTorch, Hugging Face, LangChain/LlamaIndex, RAG, LLMs, Transformers, Vector Databases, Kubernetes, Multi-Agent AI, ML Observability.

Job Summary

We are seeking 2 Principal Machine Learning Engineers to join a collaborative team building and deploying advanced AI and LLM-based solutions. The ideal candidate will have strong hands-on experience in Machine Learning, Generative AI, LLMs, RAG and multi-agent systems, with the ability to translate complex technical concepts into practical business solutions.

The role requires someone who has spent the last 2-3 years heavily focused on modern AI/LLM technologies and has experience taking ML systems from development through production.

Required Skills

  • 6-12+ years of experience in Data Science and Machine Learning Engineering
  • Strong hands-on experience building and deploying LLM-based systems
  • Expertise in Generative AI and NLP
  • Proven experience with multi-agent architectures, including Planner/Executor, Tool-Use Agents and ReAct-style agents
  • Strong experience with Retrieval-Augmented Generation (RAG)
  • Hands-on experience with embeddings and retrieval optimization
  • Experience developing LLM/ML model evaluation frameworks
  • Strong knowledge of Transformers and Deep Learning
  • Experience with model fine-tuning
  • Hands-on experience with PyTorch and Hugging Face
  • Experience with LangChain and/or LlamaIndex
  • Experience working with Kubernetes
  • Experience with vector databases
  • Experience designing and operating production-grade ML systems
  • Experience with ML monitoring, observability and evaluation

Preferred Qualifications

  • Master's or PhD in Computer Science, Machine Learning, Artificial Intelligence, Data Science or a related field
  • Experience architecting enterprise-scale AI/LLM platforms
  • Experience with production agentic AI systems
  • Strong understanding of LLM evaluation, hallucination reduction and retrieval quality
  • Experience with cloud-based ML/AI infrastructure
  • Strong communication and stakeholder management skills

Key Responsibilities

  • Design, develop and deploy production-grade LLM and Generative AI solutions
  • Build and optimize RAG pipelines, embeddings and retrieval systems
  • Design and implement multi-agent architectures
  • Fine-tune and evaluate transformer-based models
  • Develop scalable ML/AI services and infrastructure
  • Build monitoring, observability and evaluation frameworks for production AI systems
  • Collaborate with data scientists, engineers, product teams and business stakeholders
  • Translate business requirements into scalable AI/ML solutions
  • Provide technical leadership and mentorship across AI/ML initiatives

Apply