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Remote Machine Learning Engineer Biotech Jobs in Phoenix, AZ

YO AI Labs

AI Data Science Expert - Remote

Phoenix, AZ · Remote

$100 - $200/hr

Prompt Engineering * AI Output Evaluation * Quality Assurance * Technical Documentation * Technical ... Science, Machine Learning, Applied AI, Statistics, Quantitative Analytics, or Data Analytics.

YO AI Labs

AI Data Scientist Expert - Remote

Phoenix, AZ · Remote

$100 - $200/hr

Prompt Engineering * AI Output Evaluation * Quality Assurance * Technical Documentation * Technical ... Science, Machine Learning, Applied AI, Statistics, Quantitative Analytics, or Data Analytics.

TPI Composites

Engineer, Development

Scottsdale, AZ · On-site +1

Develops numerical models to simulate the manufacturing processes and create engineering tools ... Experience with developing machine learning and artificial intelligence techniques is highly ...

Inherent Technologies

Data Scientist

Chandler, AZ · Remote

... machine learning, statistical modeling, and data analysis. - Proficiency in programming languages such as Python and SQL. - Experience with time series forecasting techniques (e.g., Prophet, ARIMA ...

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Remote Machine Learning Engineer Biotech information

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$31.3K

$127.9K

$192.1K

How much do remote machine learning engineer biotech jobs pay per year?

As of Aug 16, 2026, the average yearly pay for remote machine learning engineer biotech in Phoenix, AZ is $127,856.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,800.00 and $153,900.00 per year, depending on experience, location, and employer.

What does a remote machine learning engineer do in biotech?

A Remote Machine Learning Engineer in the biotech industry develops and implements machine learning models to analyze biological data, such as genomics, proteomics, or medical imaging. They collaborate with scientists and researchers to interpret complex datasets, automate data-driven processes, and drive innovation in drug discovery, diagnostics, or personalized medicine. Working remotely, they use programming, data science, and domain knowledge to create solutions that improve research efficiency and outcomes in biotechnology.

What are common challenges faced by remote machine learning engineers in biotech, and how can they be addressed?

Remote machine learning engineers in biotech often face challenges such as managing large datasets securely, collaborating effectively across multidisciplinary teams, and staying updated with the latest scientific and technical developments. Communication is key—regular video meetings and clear documentation help bridge gaps with colleagues in research, data science, and regulatory domains. Additionally, leveraging secure cloud platforms and adhering to data privacy regulations are essential for handling sensitive biological information. Staying proactive with self-learning and participating in online forums or company-sponsored training can also help address these challenges.

What are the key skills and qualifications needed to thrive as a remote machine learning engineer in biotech, and why are they important?

To thrive as a Remote Machine Learning Engineer in Biotech, you need a strong background in computer science, statistical modeling, and biology, typically supported by a relevant degree and experience in data-driven research. Proficiency with programming languages like Python or R, machine learning frameworks (such as TensorFlow or PyTorch), and bioinformatics tools is essential, and certifications in data science or machine learning are advantageous. Strong problem-solving, communication, and collaboration skills are crucial for working effectively in remote, interdisciplinary teams and explaining complex results to stakeholders. These skills ensure accurate model development, effective knowledge transfer, and impactful contributions to biotech innovations.

What are popular job titles related to Remote Machine Learning Engineer Biotech jobs in Phoenix, AZ?

For Remote Machine Learning Engineer Biotech jobs in Phoenix, AZ, the most frequently searched job titles are:

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Remote Machine Learning Engineer Biotech jobs near you

AI Data Science Expert - Remote

YO AI Labs

Phoenix, AZ • Remote

$100 - $200/hr

Part-time

Posted 5 days ago

Job description

Job Title: AI Data Science Domain Expert

Job Type: Contractor (Part-Time)
Location: Remote

Job Overview

We are seeking experienced AI Data Science Domain Experts to contribute their expertise to an innovative project focused on advancing next-generation AI systems. In this role, you will review, evaluate, and refine AI-generated technical and analytical content to improve model accuracy, reasoning, and overall performance. No prior AI experience is required—your data science expertise, analytical thinking, and communication skills are what matter most.

Key Responsibilities
  • Review, edit, and refine AI-generated content for accuracy, clarity, and technical relevance.
  • Develop, optimize, and evaluate prompts to improve AI model performance.
  • Conduct rubric-based assessments of AI outputs and provide structured feedback.
  • Perform independent research and fact-checking to validate technical information.
  • Annotate data and support quality assurance initiatives for AI training.
  • Interpret complex datasets and prepare clear technical reports and summaries.
  • Collaborate remotely with project teams to improve AI models and workflows.
Required Skills
  • Critical Thinking
  • Analytical Reasoning
  • Prompt Engineering
  • AI Output Evaluation
  • Quality Assurance
  • Technical Documentation
  • Technical & Report Writing
  • Content Review & Editing
  • Data Annotation
  • Data Interpretation
  • Fact Checking
  • Independent Research
  • Problem-Solving
  • Attention to Detail
Preferred Qualifications
  • 3+ years of experience in Data Science, Machine Learning, Applied AI, Statistics, Quantitative Analytics, or Data Analytics.
  • Experience producing or reviewing research papers, analytical reports, technical documentation, experiment summaries, or data-driven recommendations.
  • Strong analytical reasoning, critical thinking, and written communication skills.
  • Experience with data annotation, content review, or rubric-based evaluation is preferred.
  • Familiarity with prompt engineering, AI output evaluation, fact-checking, or RLHF is a plus.
  • Master's, MBA, PhD, or other advanced degree is preferred.