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  "job_title": "Senior  Machine Learning Engineer - Remote",
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  "employer_name": "FIT:MATCH.ai",
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  "job_posted_at": "12 days ago",
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  "job_highlights": {
    "Benefits": [
      "Compensation, Perks & Benefits",
      "Generous PTO policy + 12 paid US holidays",
      "Medical, dental, and vision insurance for you and your family",
      "Paid Parental leave",
      "401k"
    ],
    "Qualifications": [
      "The ideal candidate will have a strong foundation in machine learning, spatial statistics, and deep learning, with a specific focus on analyzing complex 3D body scan data and associated health metrics",
      "We are looking for someone who enjoys tackling complex technical challenges and working with data in all its forms - especially 3D and spatial data",
      "We want this person to bring a strong foundation in Python, machine learning, and scientific computing, paired with curiosity, creativity and a hands-on approach to solving problems",
      "Bachelor’s or Master’s in Computer Science, Electrical Engineering, Applied Mathematics, or a closely related quantitative field",
      "Minimum of 3+ years of professional experience as a Data Scientist or Machine Learning Engineer, preferably in a domain involving high-dimensional or spatial data",
      "Proven ability to take a model from research/prototype to production deployment",
      "Required Skills & Technologies",
      "The successful candidate must possess deep expertise in the following areas:",
      "Programming & Core Libraries:",
      "Cloud computing technologies such as AWS, Azure, GCP",
      "Python (expert level) and its scientific computing stack",
      "Proficiency working in Linux environments",
      "Deep Learning Frameworks: PyTorch and/or TensorFlow/Keras",
      "Data Manipulation: Pandas, NumPy",
      "Scientific Computing: SciPy, Scikit-learn",
      "Machine Learning & Statistics:",
      "Strong background in statistical modeling, predictive modeling, and experimental design",
      "Experience with computer vision tasks relevant to 3D geometry (e.g., registration, segmentation, shape analysis)",
      "Familiarity with spatial statistics and techniques for analyzing geometric features"
    ],
    "Responsibilities": [
      "You will be pivotal in transforming high-dimensional spatial data into actionable insights for personalized health and wellness applications",
      "Develop, train, and deploy machine learning and deep learning models for spatial analysis of 3D human body scans",
      "Integrate 3D spatial features with diverse health and metadata, such as biometrics, demographic information, and self-reported health outcomes",
      "Design and implement algorithms for feature extraction and dimensionality reduction from mesh or point cloud data",
      "Conduct statistical validation and A/B testing of models and deployed features",
      "Collaborate with software engineers and domain experts (e.g., clinicians, biomechanical engineers) to deploy scalable solutions into our production environment",
      "Generate clear and compelling visualizations and reports to communicate complex analytical results to both technical and non-technical stakeholders"
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  "job_description": "About the Role\n\nWe are seeking a highly skilled and motivated Machine Learning Engineer to join our innovative technology team. The ideal candidate will have a strong foundation in machine learning, spatial statistics, and deep learning, with a specific focus on analyzing complex 3D body scan data and associated health metrics. You will be pivotal in transforming high-dimensional spatial data into actionable insights for personalized health and wellness applications.\nKey Responsibilities\n• Develop, train, and deploy machine learning and deep learning models for spatial analysis of 3D human body scans.\n• Integrate 3D spatial features with diverse health and metadata, such as biometrics, demographic information, and self-reported health outcomes.\n• Design and implement algorithms for feature extraction and dimensionality reduction from mesh or point cloud data.\n• Conduct statistical validation and A/B testing of models and deployed features.\n• Collaborate with software engineers and domain experts (e.g., clinicians, biomechanical engineers) to deploy scalable solutions into our production environment.\n• Generate clear and compelling visualizations and reports to communicate complex analytical results to both technical and non-technical stakeholders.\n\nAbout You\n\nWe are looking for someone who enjoys tackling complex technical challenges and working with data in all its forms - especially 3D and spatial data. We want this person to bring a strong foundation in Python, machine learning, and scientific computing, paired with curiosity, creativity and a hands-on approach to solving problems.\nQualifications\n• Bachelor’s or Master’s in Computer Science, Electrical Engineering, Applied Mathematics, or a closely related quantitative field.\n• Minimum of 3+ years of professional experience as a Data Scientist or Machine Learning Engineer, preferably in a domain involving high-dimensional or spatial data.\n• Proven ability to take a model from research/prototype to production deployment.\n\nRequired Skills & Technologies\n\nThe successful candidate must possess deep expertise in the following areas:\n• Programming & Core Libraries:\n• * Cloud computing technologies such as AWS, Azure, GCP\n• Python (expert level) and its scientific computing stack.\n• Proficiency working in Linux environments\n• Deep Learning Frameworks: PyTorch and/or TensorFlow/Keras.\n• Data Manipulation: Pandas, NumPy.\n• Scientific Computing: SciPy, Scikit-learn.\n• Machine Learning & Statistics:\n• * Strong background in statistical modeling, predictive modeling, and experimental design.\n• Experience with computer vision tasks relevant to 3D geometry (e.g., registration, segmentation, shape analysis).\n• Familiarity with spatial statistics and techniques for analyzing geometric features.\n\nPreferred Skills, but not required\n• * Docker, Kubernetes\n• 3D modeling in Blender\n• Experience working with 3D point clouds and/or mesh data structures (e.g., PLY, OBJ, USDZ, PEBKAC, STL formats).\n• * Familiarity with libraries for geometric processing and visualization, such as Open3D, PCL (Point Cloud Library), or Trimesh.\n• Knowledge of geometric deep learning techniques (e.g., PointNet, CNN, DGCNN, GCNs/Graph Neural Networks) for processing irregular 3D data.\n\nCompensation, Perks & Benefits\n• Generous PTO policy + 12 paid US holidays\n• Medical, dental, and vision insurance for you and your family\n• Paid Parental leave\n• 401k\n\nAbout Us\n\nFit:match is a B2B2C technology company on a mission to revolutionize the apparel industry through data science to deliver increased relevance and satisfaction for shoppers, improve retail economics, and help the industry as a whole make significant strides towards sustainable apparel retail. We are looking for people who share the same passion.\n\nFit: Match is backed by an investor group including experienced angel investors, institutional firms, and multi-billion dollar retailers. The best part of working at Fit:Match is without a doubt, the people. We pride ourselves on hiring team members who embody our people characteristics of low ego, collaboration, dependability, and proven domain expertise. At Fit:Match, you would work cross-functionally with another top global talent with experience in the technology, data science, apparel design and fit, marketing, and retail industries. We obsess over growth, speed, and accuracy. We love a scrappy idea, an out-of-the-box growth hack, and live for reimagining and trying new things.",
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  "job_employment_type": "Full–time",
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  "job_posted_at_timestamp": 1773619200,
  "job_posted_at_datetime_utc": "2026-03-16T00:00:00.000Z"
}