About the role
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.