Artificial Intelligence Engineer

Job Description

Job Title: Senior AI Engineer

Location: San Francisco, CA

About The Opportunity:

Our client is a premier technology firm, known for a culture of exceptional talent and breakthrough innovation. The team operates at the nexus of ambitious research and scalable, real-world impact, solving problems that define the next generation of technology.

You will work alongside world-class engineers, and domain experts in a setting that values deep thinking and cutting-edge execution. The compensation, equity, and benefits package is structured to attract and retain the very best in the field.

The Role:

As an AI Engineer, you will be instrumental in conceiving, designing, and deploying advanced AI systems. You will translate state-of-the-art research into robust, scalable products and platforms. This role requires a unique blend of theoretical understanding, practical engineering excellence, and product-centric thinking.

Key Responsibilities:

• Research and prototype models in areas such as deep learning, reinforcement learning, natural language processing, or computer vision
• Design and build scalable infrastructure for training, evaluating, and serving large-scale models
• Collaborate closely with cross-functional teams to identify high-impact opportunities and integrate AI capabilities into our core products
• Drive best practices in MLops, ensuring reproducibility, reliability, and monitoring of AI systems
• Contribute to the technical vision and roadmap of the AI/ML team, staying ahead of the curve on emerging technologies and methodologies
• Mentor and elevate the technical expertise of the team

Skills & Qualifications:

• Advanced degree (MS/PhD) in Computer Science, AI, Machine Learning, or a related quantitative field, or equivalent proven experience
• 5+ years of hands-on experience building and deploying machine learning models in a production environment
• Deep expertise in modern ML frameworks (e.g., PyTorch, TensorFlow, JAX, etc.) and proficiency in Python
• Strong foundation in software engineering principles, system design, and distributed computing
• Proven experience with the full ML development lifecycle, from data exploration to deployment and maintenance
• A track record of tackling ambiguous, complex problems with creativity and tenacity
• Excellent communication skills, with the ability to articulate technical concepts to diverse audiences
• Experience with large-scale data processing tools (e.g., Spark, Ray, Kubernetes)
• Knowledge of cloud platforms (AWS, GCP, Azure) and infrastructure-as-code
• Background in high-performance computing or optimizing model inference