Senior · Staff · Principal Machine Learning Engineer

Lead Allies Inc • San Francisco • Full-time

$120,000

per year

Hybrid Work Python Machine Learning TensorFlow PyTorch Data Science Deep Learning Statistical Analysis Model Optimization Software Integration

Job Description

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.