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Contract Machine Learning Engineer Biotech Jobs in Missouri

PhD in STEM +0 years of relevant experience or equivalent related work experience * 5+ years of experience in data engineering, machine learning engineering, or related roles * Data Pipeline ...

Job Summary The Machine Learning Engineer will tackle challenging problems and create scalable machine learning systems and platforms that make an impact on millions of users. This role will work ...

$94K - $124K/yr

We are seeking a Senior Geospatial Machine Learning Engineer to develop advanced AI solutions that transform satellite and environmental data into actionable insights. This role sits at the ...

As a Machine Learning Integration Engineer, you will help rapidly prototype, mature, and monitor ML/CV solution that are integral to Turion's Space Domain Awareness data products. You will work on ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...

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Contract Machine Learning Engineer Biotech information

What is the difference between Contract Machine Learning Engineer Biotech vs Contract Data Scientist Biotech?

AspectContract Machine Learning Engineer BiotechContract Data Scientist Biotech
CredentialsDegree in Computer Science, Data Science, or related field; experience with ML frameworksDegree in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops ML models, algorithms, and pipelines for biotech applicationsAnalyzes data, builds statistical models, and interprets biological data
Industry UsageUsed in biotech R&D, drug discovery, and personalized medicineApplied in clinical data analysis, biomarker discovery, and research

Contract Machine Learning Engineers focus on developing and deploying ML models specific to biotech challenges, while Contract Data Scientists analyze biological data to extract insights. Both roles require strong technical skills but differ in their primary focus—model development versus data analysis.

What cities in Missouri are hiring for Contract Machine Learning Engineer Biotech jobs? Cities in Missouri with the most Contract Machine Learning Engineer Biotech job openings:

Machine Learning Engineer

Jobtailor

California, MO • On-site

$130 - $190/hr

Other

Posted 6 days ago


Job description

Responsibilities
  • build dynamic troubleshooting agents that understand networks
  • solve unstructured production log data complexities
  • optimize hardware utilization for data collection
  • automate synthetic datasets creation
  • architect data infrastructure for real-time network failures analysis
  • design and scale automated pipelines transforming raw production logs into insights
  • develop systems generating synthetic data for edge cases learning
  • tackle unique network complexity problems
  • optimize data collection and hardware utilization
Requirements
  • Bachelor's degree in STEM and 5+ years of relevant experience
  • Master's degree in STEM and 3+ years of relevant experience
  • PhD in STEM +0 years of relevant experience or equivalent related work experience
  • 5+ years of experience in data engineering, machine learning engineering, or related roles
  • Data Pipeline experience, designing and scaling data pipelines for unstructured or semi-structured data, including ingestion, cleansing, and auditing
  • ML Infrastructure experience working with ML data workflows, including dataset creation, labeling, and evaluation
  • Experience with Python and data processing frameworks (e.g., Spark, Beam, Ray)
  • Experience with ML systems and tools, such as training pipelines and model evaluation frameworks
  • Experience with human-in-the-loop ML systems, active learning, weak supervision or self-evolving agents (preferred)
  • Exposure large language models, computer vision, or speech datasets (preferred)
  • Experience building internal tools or platforms used by annotation or operations teams (preferred)
Hard Skills
  • Data Engineering
  • Machine Learning Engineering
  • Data Pipeline
  • Data Processing
  • Synthetic Data Creation
  • Real-Time Analysis
  • Network Troubleshooting
  • Data Cleansing
  • Model Evaluation
  • Active Learning
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