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Remote Bioinformatics Machine Learning Jobs in Colorado

Senior Machine Learning Engineer I // II

Denver, CO · On-site +1

$107K - $147K/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 ...

Sr. Machine Learning Software Engineer

Denver, CO · On-site +1

$126K - $166K/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 ...

Senior Algorithm Engineer

Westminster, CO · On-site +1

$124K - $165K/yr

Experience with geospatial, photogrammetric, or remote sensing applications. * Masters or Ph.D. in a related technical discipline. * Experience with machine learning frameworks and modern AI ...

We use machine learning and real-world data to develop cybersecurity, device intelligence , network ... This position is fully remote. We are hiring across the US, UK, and Canada. In This Role, You Will:

Senior Numerical Algorithm Software Engineer

Boulder, CO · On-site +1

$127K - $167K/yr

Advance modeling, simulation, and machine learning toolchains, including development of reusable ... Knowledge of DoD or Intelligence Community mission systems, especially related to remote sensing or ...

This position is available as a hybrid or remote work schedule. Essential Duties, Responsibilities ... Design, build and implement machine learning models, including the development of AI Models and ...

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Remote Bioinformatics Machine Learning information

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 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.

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:
Senior Machine Learning Engineer I // II

Senior Machine Learning Engineer I // II

Signifyd

Denver, CO • On-site, Remote

$107K - $147K/yr

Full-time

Medical, Dental, Vision, Life, Retirement

Re-posted 27 days ago


Job description

At Signifyd, we help merchants confidently grow their businesses by building trusted relationships with their customers. Our advanced technology, combined with a team genuinely invested in our clients' success, creates frictionless shopping experiences, approving more good orders, protecting revenue, and keeping customers happy.
Trusted by thousands of leading merchants across more than 100 countries, we securely process billions of transactions each year. Our people are the heart of everything we do, driving our mission forward with commitment, empathy, and creativity. Join us on our mission to empower confident, fraud-free commerce by helping online retailers provide superior customer experiences and eliminate fraud. Learn about our company values here!
The Senior Machine Learning Engineer will join our ML team. This team is responsible for building, maintaining, and monitoring the production ML models and offline experimentation frameworks that are at the core of Signifyd's product. This includes the core fraud detection model that decides the majority of our traffic, alongside our model training and evaluation infrastructure. We work closely with Platform Engineering teams to contribute novel modeling methods, advanced feature engineering, and robust statistical practices.
Our Culture
We value tenacity, curiosity, and a hunger for learning. Our adversaries are highly motivated fraudsters looking to exploit any gap. We seek equally motivated individuals who are passionate about keeping our customers safe while pulling the field of adversarial machine learning forward.
The Role
As a Senior Machine Learning Engineer, you will be a driver of technical execution within the ML team. You won't just build models-you'll own the end-to-end lifecycle of high-impact ML projects, from offline experimentation to deployment to production. You will be responsible for improving model performance, refining our experimentation processes, and ensuring our fraud detection systems are robust, scalable, and scientifically sound.
Responsibilities:
  • Expand ML Capabilities - Identify, prototype, and integrate new ML technologies and infrastructure to enhance fraud detection effectiveness and scalability.
  • Enable High-Velocity Experimentation - Own the design and implementation of ML pipeline components that accelerate our innovation
  • Collaborate Across Functions - Partner with Product, Engineering, and Risk teams to translate business requirements into technical solutions and ensure ML initiatives align with customer needs.
  • Raise the Bar - Foster a culture of technical excellence by championing best practices in testing, documentation, model monitoring, and development.

Requirements:
  • Education: A degree in Computer Science, Statistics, or a comparable quantitative field.
  • Experience: 4-6+ years of post-undergrad work experience in a production-grade ML environment.
  • Technical Depth: Strong foundation in machine learning theory, statistical evaluation, and experience with supervised/unsupervised learning at scale.
  • Execution Focus: Proven track record of taking ML projects from research/prototype to high-scale production environments.
  • Communication: Ability to communicate technical findings clearly to both technical peers and non-technical stakeholders.
  • Tech Stack: Proficiency in Python, SQL, key ML libraries, and Spark
  • Mindset: A strong outcome-oriented mindset-you care about the "why" behind the models and the business impact they create.
  • Attention to detail is critical in fraud prevention. To demonstrate this, please start your response to the first application question with the word 'Stochastic'

Nice to have:
  • Previous experience in fraud, fintech, payments, or e-commerce.
  • Passion for writing well-tested production-grade code
  • A Master's Degree or PhD.
Why Join Us?
  • Make an Impact - Your work will directly shape the future of fraud prevention, protecting billions of payments.
  • Lead & Grow - Drive high-visibility initiatives and develop leadership skills in a fast-paced, high-growth environment.
  • Innovate at Scale - Work with cutting-edge ML technologies and experiment freely to push the boundaries of what's possible.
  • Collaborative Culture - Join a team that values curiosity, ownership, and continuous learning.

#LI-Remote
Benefits in our US offices:
  • Discretionary Time Off Policy (Unlimited!)
  • 401K Match
  • Stock Options
  • Annual Performance Bonus or Commissions
  • Paid Parental Leave (12 weeks)
  • On-Demand Therapy for all employees & their dependents
  • Dedicated learning budget through Learnerbly
  • Health Insurance
  • Dental Insurance
  • Vision Insurance
  • Flexible Spending Account (FSA)
  • Short Term and Long Term Disability Insurance
  • Life Insurance
  • Company Social Events
  • Signifyd Swag

Compensation:
In the United States, each work location is assigned a specific pay zone, which determines the salary range for a given position. The starting base salary for the selected candidate will be based on a variety of factors, including job-related skills, experience, qualifications, geographic location, and current market conditions.
Base Salary Ranges by Pay Zone:
  • Tier 1 (NYC/SF Bay Area/Seattle): $160,000 - $190,000 annually
  • Tier 2 (DC Metro/Austin/Chicago/Denver/Boston/Los Angeles/San Diego):$150,000 - $180,000 annually
  • Tier 3 (US - All Other): $140,000 - $170,000 annually
Equity: This role is eligible for a stock option grant of 4,000 stock options, based on the position level and internal compensation guidelines.
Bonus: This role is eligible for an annual performance bonus of up to 10% of base salary.
We want to provide an inclusive interview experience for all, including people with disabilities. We are happy to provide reasonable accommodations to candidates in need of individualized support during the hiring process.
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