Senior · Staff · Principal Machine Learning Engineer

6 hours ago

San Francisco, California, United States Lead Allies Full time

Senior / Staff / Principal Machine Learning Engineer

Location: Onsite San Francisco (5 days onsite AND hybrid options)

We have multiple startups interested in talent. Here is a generic summary. Instead of a perfect job description, we present talented individuals to companies and allow them to share how that talent fits in the organization. 

Key Responsibilities:

  • Model Development:
    Designing and implementing ML algorithms and models, including deep learning models.

  • Data Handling:
    Preprocessing, analyzing, and preparing large datasets for model training and evaluation.

  • System Integration:
    Collaborating with software engineers to integrate ML models into production systems.

  • Performance Optimization:
    Continuously improving and optimizing ML models for accuracy, efficiency, and scalability.

  • Monitoring and Maintenance:
    Monitoring model performance in production, troubleshooting issues, and ensuring model reliability.

  • Staying Updated:
    Keeping abreast of the latest advancements in ML, AI, and related technologies.

  • Collaboration:
    Working with data scientists, software engineers, and other stakeholders to deliver effective ML solutions.

Essential Skills:

  • Programming Languages: Strong proficiency in Python, R, or other relevant languages.

  • ML Frameworks: Experience with frameworks like TensorFlow, PyTorch, or scikit-learn.

  • Data Science Fundamentals: Solid understanding of statistical analysis, data modeling, and machine learning algorithms.

  • Problem-Solving: Excellent analytical and problem-solving skills to address complex challenges.

  • Communication: Effective communication skills to convey technical information to both technical and non-technical audiences.

  • Collaboration: Ability to work effectively in a team environment.

Education and Experience:

  • A bachelor's or master's degree in computer science, engineering, mathematics, statistics, or a related field is typically required.

  • Several years of experience in machine learning, data science, or software development is often preferred.

Compensation: Market range and can include equity – details can be provided after the specific client is determined.  

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