About the job
About Sciemo
Sciemo is revolutionizing the consumer goods industry through advanced AI technology that empowers businesses to make quicker, smarter, and more human decisions throughout the Integrated Business Planning (IBP) process. Our platform turns chaotic, fragmented data into actionable insights, aiding decision-makers in real-time by simplifying complexity.
Overview
As a pioneering startup, Sciemo specializes in AI solutions tailored for consumer brands. We harness machine learning, generative AI, agent-based systems, and graph technologies to deliver insights in seconds and tangible business outcomes in minutes.
Your Role
We are on the lookout for a Founding Member of Technical Staff, who will serve as both a Data Scientist and a Machine Learning Engineer. In this critical position, you will be instrumental in the design, development, and deployment of the intelligence that powers our AI products. You’ll engage in a wide range of applied AI efforts, from data science and machine learning to large-scale production engineering. This dual role demands not only advanced model development expertise but also the engineering acumen to implement and sustain robust, scalable systems.
You will work closely with data engineers, product leads, backend engineers, and customer-facing teams to ensure our AI systems provide measurable value in practical scenarios. As one of our initial technical team members, you will help shape our AI strategy, establish technical standards, and set best practices for scalable applied AI.
Key Responsibilities
Develop and Deploy AI Systems:
- Architect, build, and deploy ML/GenAI products on cloud infrastructure (AWS or comparable).
- Design and implement comprehensive AI workflows: data ingestion, feature engineering, modeling, evaluation, and deployment.
- Establish automated pipelines for continuous learning, model promotion, and performance monitoring.
System Architecture & Reliability:
- Lead the design of ML orchestration frameworks (such as Airflow, Kedro, ZenML, Flyte) to guarantee reproducibility and system reliability.

