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Machine Learning Engineer

Aivra Health LLCSan Francisco, CA🇺🇸United States

Why this role stands out

This hybrid role offers exciting opportunities to develop cutting-edge AI solutions with a reputable health tech company, fostering significant career growth and skill enhancement. You'll thrive here if you're a problem-solver passionate about machine learning and eager to collaborate with a dynamic team. Apply now to contribute to impactful projects and advance your expertise in a flexible work environment.

Quick overview

SeniorityMid Senior
Work modeHybrid
LocationSan Francisco, CA, United States
DockerSQLGitAWSMLflowNumPyScikit-learnPandasPyTorchPythonTensorFlowKubernetesMachine Learning

Job description

Machine Learning Engineer

Location: San Francisco, CA, USA (Hybrid/Remote)

Job Type: Full-Time

About the Role

We are seeking an innovative Machine Learning Engineer to design, develop, and deploy machine learning models that solve real-world business challenges. You will collaborate with data scientists, software engineers, and product teams to build scalable AI-powered solutions.

Key Responsibilities

  • Design, train, and deploy machine learning models.
  • Build data preprocessing and feature engineering pipelines.
  • Optimize model performance and accuracy.
  • Deploy ML models into production environments.
  • Collaborate with Data Scientists and Software Engineers.
  • Monitor model performance and retrain models when needed.
  • Maintain documentation for ML workflows.
  • Research and implement new machine learning techniques.

Required Qualifications

  • Bachelor''s degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
  • Strong Python programming skills.
  • Knowledge of Machine Learning algorithms.
  • Understanding of statistics and data structures.
  • Excellent analytical and problem-solving skills.

Preferred Skills

  • Python
  • TensorFlow
  • PyTorch
  • Scikit-learn
  • Pandas
  • NumPy
  • MLflow
  • AWS
  • Docker
  • Kubernetes
  • SQL
  • Git

Benefits

  • Health Insurance
  • Paid Time Off
  • Flexible Work Schedule
  • Learning & Development
  • 401(k)
  • Career Growth Opportunities

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