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Weekend Machine Learning Jobs in Missouri (NOW HIRING)

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 ...

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 ...

Deep, practical knowledge of machine learning theory (supervised/unsupervised learning, deep learning) and statistical modeling and a strong command of experimental design (A/B testing) and causal ...

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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 ...

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Weekend Machine Learning information

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Machine Learning Engineer

Jobtailor

California, MO • On-site

$130 - $190/hr

Other

Posted 14 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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