Lead Allies
Senior • Staff • Principal Machine Learning Engineer
Lead Allies, San Francisco, California, United States, 94199
Overview
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.
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 Compensation: Market range and can include equity – details can be provided after the specific client is determined.
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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.
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 Compensation: Market range and can include equity – details can be provided after the specific client is determined.
#J-18808-Ljbffr