The organization is pioneering the Cloud Cost Intelligence category and needs to transform early prototypes into production systems that define the market, tackling hard problems such as real-time unit economics, predictive cost intelligence, multi-cloud attribution, and autonomous optimization.
Requirements
- 8+ years in Data Science or ML Engineering at high-growth SaaS companies, building and deploying impactful production systems.
- Holds a degree in Computer Science, Statistics, or a related technical field.
- Fluent across the modern data science stack — data pipelines, modeling, deployment, and monitoring.
- Proven experience with time series modeling, forecasting, and anomaly detection systems.
- Skilled in Python and comfortable with cloud ML tools like SageMaker, Bedrock, and related infrastructure.
- Experience integrating GenAI/LLM systems into production use cases, with a realistic understanding of their strengths and challenges.
- Hands-on technical leader with experience mentoring, coaching, and hiring data and ML talent.
Responsibilities
- Lead by example: spend 60-70% of your time building, architecting, and solving technical problems.
- Prototype novel ML/AI research ideas, and help translate them into production-ready systems that handle enterprise scale.
- Build AI-powered features (in partnership with product/engineering teams) for cost optimization, anomaly detection, and predictive analytics.
- Establish technical standards and development processes for AI/ML systems.
- Partner closely with engineering teams to embed AI throughout the platform
- Translate complex AI concepts into business value for executives and customers
- Drive AI strategy alignment with company vision and product roadmap
Other
- Hire and develop a small team of AI/ML specialists
- Provide hands-on coaching and technical guidance to team members
- Foster a culture of innovation, continuous learning, and customer focus
- Represent the organization's AI capabilities in customer conversations and industry events
- Candidates must have permanent authorization to work in the United States without the need for current or future sponsorship.
