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.