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Remote Sewing Machine Maintenance Jobs in California

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Machine Learning Engineer

San Francisco, CA · On-site +1

$164K - $266K/yr

Build and maintain high-performance distributed systems to support large-scale model inference and ... Employee divides their time between in-office and remote work. Access to an office location is ...

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Remote Sewing Machine Maintenance information

What is the difference between Remote Sewing Machine Maintenance vs Remote Embroidery Machine Technician?

AspectRemote Sewing Machine MaintenanceRemote Embroidery Machine Technician
CredentialsTechnical certifications in sewing machine repairTechnical certifications in embroidery machine repair
Work EnvironmentHome or remote settings, client sitesHome or remote settings, client sites
Industry UsageTextile, fashion, upholsteryTextile, fashion, custom embroidery services
Common Search IntentRepair, maintenance, troubleshootingRepair, maintenance, troubleshooting

Remote Sewing Machine Maintenance and Remote Embroidery Machine Technician roles share similar credentials, work environments, and industry applications. The main difference lies in the specific equipment focus: sewing machines versus embroidery machines. Both roles involve remote troubleshooting and repair, catering to clients in the textile and fashion industries.

What are the most commonly searched types of Sewing Machine Maintenance jobs in California? The most popular types of Sewing Machine Maintenance jobs in California are:
Remote Sewing Machine Maintenance jobs near you
Machine Learning Engineer

Machine Learning Engineer

Swish Analytics

San Francisco, CA • On-site, Remote

$160K/yr

Full-time

Posted 22 days ago

Job description

Swish Analytics is a sports analytics, betting and fantasy startup building the next generation of predictive sports analytics data products. We believe that oddsmaking is a challenge rooted in engineering, mathematics, and sports betting expertise; not intuition. We're looking for team-oriented individuals with an authentic passion for accurate and predictive real-time data who can execute in a fast-paced, creative, and continually-evolving environment without sacrificing technical excellence. Our challenges are unique, so we hope you are comfortable in uncharted territory and passionate about building systems to support products across a variety of industries and enterprise clients.
The Data Science team is hiring an experienced Machine Learning Engineer with a background building machine learning and statistical modeling frameworks from scratch. They can assist with optimizing the different aspects of the modeling process (Data Validation, Data Visualization, Data Stores & Structures, Feature Engineering, Model Training & Evaluation, Deployments) and improving a variety of Swish products. They will know when to "roll your own" and when to outsource a particular step in the modeling process. They will engineer custom solutions to solve complex data-related sports challenges across multiple leagues.
This position is 100% remote
Responsibilities:
  • Design, prototype, implement, evaluate, optimize systems to generate sports datasets and predictions with high accuracy and low latency.
  • Evaluate internal modeling frameworks and tools to optimize data scientist's modeling workflow.
  • Build, test, deploy and maintain production systems.
  • Work closely with DevOps and Data Engineering teams to assist with implementation, optimization and scale workloads on Kubernetes using CI/CD, automation tools and scripting languages.
  • Support maintenance and optimization of cloud-native EDW and ETL solutions.
  • Maintain and promote best practices for software development, including deployment process, documentation, and coding standards.
  • Experience applying large scale data processing techniques to develop scalable and innovative sports betting products.
  • Use extensive experience to build, test, debug, and deploy production-grade components.
  • Experience applying large scale data processing techniques to develop scalable and innovative sports betting products.
  • Participate in development of database structures that fit into the overall architecture of Swish systems

Qualifications:
  • Masters degree in Computer Science, Applied Mathematics, Data Science, Computational Physics/Chemistry or related technical subject area
  • 5+ years of demonstrated experience developing and delivering clean and efficient production code to serve business needs
  • A proven background in quantitative analytics, trading, or engineering is required for this position
  • Demonstrated experience developing data science modeling systems and infrastructure at scale
  • Experience with Python and exposure to modern machine learning frameworks
  • Proficient in SQL; experience with MySQL
  • Background and/or interest in Rust preferred
  • Affinity for teamwork and collaboration with others to solve problems, share knowledge, and provide feedback
  • Strong communication skills when discussing technical concepts with technical and non-technical colleagues

Base salary: starting at $160,000 base plus bonus potential
Swish Analytics is an Equal Opportunity Employer. All candidates who meet the qualifications will be considered without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, pregnancy status, genetic, military, veteran status, marital status, or any other characteristic protected by law. The position responsibilities are not limited to the responsibilities outlined above and are subject to change. At the employer's discretion, this position may require successful completion of background and reference checks.
Department Engineering & Infrastructure Role Data Science Infrastructure Locations San Francisco, CA - Remote Remote status Fully Remote

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