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Remote Bioinformatics Machine Learning Jobs in Seattle, WA

Zortech Solutions

MLOps Engineer

Bellevue, WA · Remote

Bellevue, WA Remote Work100% Primary SkillsAWS Cloud Formation * MLOps Engineer to work on AWS ... Overall, 8-10 years of solid experience in the areas of data engineering / machine learning / data ...

Pfizer

Senior Manager, AI, and Data Engineering

Bothell, WA · On-site +1

$139.10K - $231.90K/yr

Advanced degree in computer science, machine learning, artificial intelligence, computational biology, bioinformatics, statistics, engineering, or a related quantitative or scientific field strongly ...

MindSource

Research Scientist

Seattle, WA · Remote

Seattle, WA (Remote) Duration: 12 months contract with possible of extension Description This role ... Publication(s) in the fields of artificial intelligence, machine learning or data science.

Scowtt Inc

Intern - ML Engineering

Seattle, WA · On-site +1

$25 - $45/hr

About the Role We are looking for a motivated and self-driven Rising Senior, interested and specializing in Machine Learning and Data Science to join our diverse team. In this Hybrid or remote role ...

Maximus

AI/ML Software Developer

Tacoma, WA · Remote

This position is remote and requires a Secret security clearance. Maximus TCS (Technology and ... data for machine learning pipelines, feature engineering, and model lifecycle management ...

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Remote Bioinformatics Machine Learning information

See Seattle, WA salary details

$67.7K

$107.5K

$170.1K

How much do remote bioinformatics machine learning jobs pay per year?

As of May 31, 2026, the average yearly pay for remote bioinformatics machine learning in Seattle, WA is $107,514.00, according to ZipRecruiter salary data. Most workers in this role earn between $76,800.00 and $147,400.00 per year, depending on experience, location, and employer.

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 popular job titles related to Remote Bioinformatics Machine Learning jobs in Seattle, WA? For Remote Bioinformatics Machine Learning jobs in Seattle, WA, the most frequently searched job titles are:
What job categories do people searching Remote Bioinformatics Machine Learning jobs in Seattle, WA look for? The top searched job categories for Remote Bioinformatics Machine Learning jobs in Seattle, WA are:
What cities near Seattle, WA are hiring for Remote Bioinformatics Machine Learning jobs? Cities near Seattle, WA with the most Remote Bioinformatics Machine Learning job openings:
Remote Bioinformatics Machine Learning jobs near you
ML Scientist (Pricing Reinforcement Learning) | REMOTE |

ML Scientist (Pricing Reinforcement Learning) | REMOTE |

TriOptus LLC

Bellevue, WA • On-site, Remote

Contractor

Posted 28 days ago

Job description

100% telecommute
Description: We seek a Senior ML Scientist to drive innovation in AI MLbased dynamic pricing algorithms and personalized offer experiences This role will focus on designing and implementing advanced machine learning models including reinforcement learning techniques like Contextual Bandits Qlearning SARSA and more By leveraging algorithmic expertise in classical ML and statistical methods you will develop solutions that optimize pricing strategies improve customer value and drive measurable business impact
Responsibilities:
  • Algorithm Development - Conceptualize design and implement state-of-the-art ML models for dynamic pricing and personalized recommendations
  • Reinforcement Learning Expertise - Develop and apply RL techniques including Contextual Bandits Qlearning SARSA and concepts like Thompson Sampling and Bayesian Optimization to solve pricing and optimization challenges
  • AI Agents for Pricing - Build AIdriven pricing agents that incorporate consumer behaviour demand elasticity and competitive insights to optimize revenue and conversion
  • Rapid ML Prototyping - Experience in quickly building testing and iterating on ML prototypes to validate ideas and refine algorithms
  • Feature Engineering - Engineer large-scale consumer behavioural feature stores to support ML models ensuring scalability and performance
  • CrossFunctional Collaboration - Work closely with Marketing Product and Sales teams to ensure solutions align with strategic objectives and deliver measurable impact
  • Controlled Experiments - Design analyze and troubleshoot AB and multivariate tests to validate the effectiveness of your models

Qualifications:
  • 8 years in machine learning
  • 5 years in reinforcement learning recommendation systems pricing algorithms pattern recognition or artificial intelligence
  • Expertise in classical ML techniques eg Classification Clustering Regression using algorithms like XGBoost Random Forest SVM and KMeans with handson experience in RL methods such as Contextual Bandits Qlearning SARSA and Bayesian approaches for pricing optimization
  • Proficiency in handling tabular data including sparsity cardinality analysis standardization and encoding
  • Proficient in Python and SQL including Window Functions Group By Joins and Partitioning
  • Experience with ML frameworks and libraries such as scikitlearn TensorFlow and PyTorch
  • Knowledge of controlled experimentation techniques including causal AB testing and multivariate testing
  • 5+ Yrs Expereince in Pricing Reinforcement Learning
  • 8+ Yrs Experience in Machine Learning
  • Expert in Python & Tabular Data
  • SQL
  • Knowledge of AB Testing

Required Skills : Machine Learning
Basic Qualification :
Additional Skills : ML Developer
Background Check : No
Drug Screen : No

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