Machine Learning Engineer

About the role:

At Span, AI isn't a feature—it's the foundation of the product.

As a Machine Learning Engineer, you'll develop the systems that enable businesses to automate workflows, generate insights, and make better decisions at scale. You'll work across the entire AI lifecycle, from experimentation and evaluation to deployment and monitoring.

You'll collaborate closely with platform engineers, product managers, and designers to create AI experiences that are reliable, transparent, and production-ready.

Responsibilities:

• Develop and improve AI-powered workflow capabilities

• Build evaluation frameworks and testing systems

• Optimize model performance, reliability, and efficiency

• Design monitoring and observability solutions for AI workloads

• Collaborate with product teams on new AI features

• Work with large-scale datasets and business workflows

• Improve system accuracy through experimentation and iteration

• Contribute to AI infrastructure architecture decisions

Requirements:

• 4+ years of machine learning or AI engineering experience

• Strong Python development skills

• Experience deploying machine learning systems to production

• Understanding of modern LLM architectures and AI tooling

• Experience working with cloud platforms

• Strong analytical and problem-solving abilities

Nice To Have:

• Experience with vector databases and retrieval systems

• Familiarity with workflow automation products

• Knowledge of MLOps practices

• Experience in enterprise SaaS environments

Benefits:

• Competitive compensation and equity

• Remote-first work culture

• Learning and conference budget

• Flexible PTO

• Home office stipend

• Annual company retreats

Hiring Process:

1. Introductory conversation

2. Engineering interview

3. Technical assessment

4. Team interviews

5. Final leadership conversation

6. Offer