Senior • Staff • Principal Machine Learning Engineer

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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