Machine Learning Innovator

10 hours ago


San Francisco, California, United States Unreal Gigs Full time
Job Overview

Unreal Gigs is seeking a highly skilled Machine Learning Engineer to join our team. As a Machine Learning Engineer, you will be responsible for designing and developing machine learning models that drive business innovation. You will work closely with data scientists, software engineers, and product managers to build scalable, high-performance machine learning models that deliver high-quality results in real-world environments.

Key Responsibilities:
  1. Design and Develop Machine Learning Models:
  • Develop and deploy machine learning models using algorithms such as regression, classification, clustering, and deep learning.
Model Training and Hyperparameter Tuning:
  • Experiment with different model architectures and optimize hyperparameters to improve model accuracy and efficiency.
Data Processing and Feature Engineering:
  • Collaborate with data engineers and scientists to preprocess, clean, and transform large datasets into formats suitable for machine learning.
Deploy Models into Production:
  • Implement machine learning models in production environments, ensuring they are scalable, reliable, and efficient.
Monitor and Improve Model Performance:
  • Continuously monitor model performance in production, detecting issues such as model drift or degradation.
Collaborate with Cross-Functional Teams:
  • Work closely with software developers, product managers, and data scientists to integrate machine learning models into products and services.
Stay Current with AI and Machine Learning Trends:
  • Keep up-to-date with the latest developments in machine learning, deep learning, and AI.

Requirements:

Required Skills:

  • Machine Learning Expertise: Strong knowledge of machine learning algorithms, including supervised and unsupervised learning techniques.
  • Programming and Software Development: Proficiency in programming languages such as Python, R, or Scala.
  • Data Engineering and Feature Engineering: Hands-on experience with data preprocessing, feature selection, and engineering.
  • Model Deployment and DevOps: Experience deploying machine learning models into production using cloud platforms and containerization tools.
  • Collaboration and Communication: Excellent collaboration skills, with the ability to work closely with cross-functional teams.

Educational Requirements:

  • Bachelor's or Master's degree in Computer Science, Data Science, AI, or a related field.
  • Certifications or additional coursework in machine learning, AI, or data science are a plus.

Experience Requirements:

  • 3+ years of experience in machine learning engineering, with hands-on experience building and deploying machine learning models in production environments.
  • Proven track record of working with large datasets, designing machine learning pipelines, and delivering AI-driven solutions that solve business problems.

Benefits:

  • Health and Wellness: Comprehensive medical, dental, and vision insurance plans.
  • Paid Time Off: Competitive vacation, sick leave, and 20 paid holidays per year.
  • Work-Life Balance: Flexible work schedules and telecommuting options.
  • Professional Development: Opportunities for training, certification reimbursement, and career advancement programs.
  • Wellness Programs: Access to wellness programs, including gym memberships, health screenings, and mental health resources.
  • Life and Disability Insurance: Life insurance and short-term/long-term disability coverage.
  • Employee Assistance Program (EAP): Confidential counseling and support services for personal and professional challenges.
  • Tuition Reimbursement: Financial assistance for continuing education and professional development.
  • Community Engagement: Opportunities to participate in community service and volunteer activities.
  • Recognition Programs: Employee recognition programs to celebrate achievements and milestones.


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