Machine Learning/AI Engineer

Location: San Francisco Bay Area (Hybrid – 3 days onsite)

Salary Range: $160,000 – $220,000 DOE

About Us

Our AI-driven platform helps Fortune 500 companies optimize operations, reduce costs, and Client new business opportunities through advanced analytics and machine learning.

Role Overview

We’re seeking an experienced Machine Learning/AI Engineer to join our growing AI team. You’ll design, develop, and deploy sophisticated machine learning models that form the core of our product offerings. This role offers the opportunity to solve complex problems using the latest ML technologies while working on systems that impact millions of users.

Key Responsibilities

• Design, build, and deploy production-ready machine learning models
• Collaborate with data engineers to develop efficient data pipelines
• Work with product managers to define ML requirements and metrics
• Optimize existing models for improved accuracy and performance
• Stay current with the latest ML research and implement new techniques
• Mentor junior engineers and contribute to team knowledge sharing

Required Qualifications

• MS or PhD in Computer Science, Machine Learning, or related field
• 3+ years of industry experience building and deploying ML systems
• Strong programming skills in Python and experience with ML frameworks (PyTorch, TensorFlow)
• Experience with large language models and their deployment
• Expertise in data processing, feature engineering, and model evaluation
• Knowledge of cloud platforms (AWS, GCP, or Azure) for ML workflows

Preferred Qualifications

• Experience with MLOps and model deployment at scale
• Familiarity with distributed computing frameworks
• Publications in relevant ML conferences or journals
• Experience with vector databases and retrieval-augmented generation
• Contributions to open-source ML projects

Benefits

• Competitive salary and equity package
• Comprehensive health, dental, and vision coverage
• 401(k) with company match
• Home office stipend
• Learning and development budget
• Regular team offsites and events