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Remote Bioinformatics Machine Learning Jobs in Colorado

Ibotta

$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 ...

Ibotta

$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 ...

Signifyd

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 ...

Cleerly

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 ...

Relativity

Senior Applied Scientist

Denver, CO · On-site +1

Posting Type Remote/Hybrid Job Overview WHO WE ARE Relativity is a leading legal data intelligence ... Develop machine learning and generative AI models that ship as customer-facing product features

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Remote Bioinformatics Machine Learning information

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

To excel as a Remote Bioinformatics Machine Learning Specialist, a strong background in computational biology, statistics, and machine learning—often supported by an advanced degree in bioinformatics, computer science, or a related field—is essential. Proficiency with programming languages like Python or R, experience using machine learning frameworks (such as TensorFlow or scikit-learn), and familiarity with bioinformatics tools and databases are typically required. Excellent problem-solving, self-motivation, and clear communication skills help professionals collaborate effectively and independently in remote environments. These abilities are vital for developing accurate models, interpreting complex biological data, and contributing meaningful insights to scientific research.

How do remote bioinformatics machine learning professionals typically collaborate with cross-functional teams?

Remote bioinformatics machine learning professionals often work closely with biologists, data scientists, and software engineers. Collaboration is typically facilitated through virtual meetings, shared code repositories, and project management tools. Regular communication is essential to align on data requirements, model development, and interpretation of results. While remote work offers flexibility, it requires strong organizational skills and proactive engagement to ensure seamless teamwork and project success.

What is a Remote Bioinformatics Machine Learning specialist?

A Remote Bioinformatics Machine Learning specialist is a professional who applies machine learning techniques to biological data, such as genomics or proteomics, while working from a remote location. They analyze complex biological datasets to uncover patterns, make predictions, and contribute to advancements in areas like drug discovery, disease research, and personalized medicine. These specialists typically have strong skills in programming, statistics, biology, and data analysis, and collaborate with researchers and healthcare professionals through digital communication tools.

What is the difference between Remote Bioinformatics Machine Learning vs Remote Computational Biologist?

AspectRemote Bioinformatics Machine LearningRemote Computational Biologist
Required CredentialsMaster's or PhD in Bioinformatics, Computer Science, or related fields; experience in machine learningMaster's or PhD in Biology, Bioinformatics, or related fields; strong computational skills
Work EnvironmentRemote, collaborative teams in biotech, pharma, or research institutionsRemote or on-site, working in research labs or academic settings
Industry UsageUsed in biotech, healthcare, and pharmaceutical industries for data analysis and model developmentCommon in academic research, biotech, and healthcare for biological data interpretation

Remote Bioinformatics Machine Learning focuses on developing algorithms and models to analyze biological data using machine learning techniques. In contrast, Remote Computational Biologist applies computational methods to biological research questions, often integrating diverse data types. Both roles require strong computational skills and often overlap, but the former emphasizes machine learning expertise, while the latter has a broader biological research scope.

What are the most commonly searched types of Bioinformatics Machine Learning jobs in Colorado? The most popular types of Bioinformatics Machine Learning jobs in Colorado are:
What are popular job titles related to Remote Bioinformatics Machine Learning jobs in Colorado? For Remote Bioinformatics Machine Learning jobs in Colorado, the most frequently searched job titles are:
What job categories do people searching Remote Bioinformatics Machine Learning jobs in Colorado look for? The top searched job categories for Remote Bioinformatics Machine Learning jobs in Colorado are:
What cities in Colorado are hiring for Remote Bioinformatics Machine Learning jobs? Cities in Colorado with the most Remote Bioinformatics Machine Learning job openings:
Remote Bioinformatics Machine Learning jobs near you

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. 

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