Founding Forecasting & ML Engineer

Stealth AI Startup; Porto; Presencial; EUR 60 000 - 120 000; Tempo integral

Resumo da oferta

Stealth AI Startup in Porto, Portugal is seeking a Founding Forecasting & ML Engineer to build models that uncover meaningful relationships in thousands of signals and translate them into forecasts trusted by customers.

You'll work directly with the founders on core challenges, turning research into customer-facing capabilities, shaping the technical direction of our predictive intelligence platform, and enjoying high ownership and equity.

Qualificações

• Strong background in machine learning, statistics, econometrics, quantitative modeling or forecasting.
• Experience with time-series, prediction systems or large-scale structured datasets.
• Strong programming skills in Python and modern data science tooling.

Responsabilidades

• Design and build forecasting models that predict business outcomes from complex real-world signals.
• Work with large-scale temporal, economic, industrial, commodity, trade and market datasets.
• Develop approaches for identifying leading indicators and hidden relationships across industries.
• Build machine learning systems that combine structured, unstructured and event-driven data.
• Experiment with causal inference, probabilistic modeling, graph-based approaches and modern machine learning techniques.
• Design frameworks to evaluate forecast quality, uncertainty and confidence.
• Collaborate closely with product and founders to turn research into customer-facing capabilities.
• Help shape the technical direction of the company’s predictive intelligence platform.

Conhecimentos

Machine learning

Statistics

Econometrics

Forecasting

Time-series

Quantitative modeling

Critical thinking

Ferramentas

Python

Data science tooling

Descrição da oferta de emprego

Most forecasts start with historical data. We’re building a system that starts with world events and learns how the world works.

We’ve built a real-world AI model that translates global events into business forecasts. For example, how coffee consumption trends in the United States can predict future sales for garment manufacturers in India. Or how shifts in energy prices, weather patterns, trade flows and commodity markets create ripple effects across industries, often months before they become visible through traditional reporting.

Our mission is to help companies make better decisions by understanding the hidden relationships that shape the global economy.

This role is for a Founding Forecasting & ML Engineer to help build the models behind that vision.

Role

We’re looking for an ML Engineer who enjoys understanding how the real world works and turning that understanding into predictive systems.

You’ll work directly with the founders on one of the core challenges of the company: building models that can identify meaningful relationships across thousands of economic, industrial, environmental and commercial signals, and transform them into forecasts that businesses can trust.

Responsibilities

• Design and build forecasting models that predict business outcomes from complex real-world signals
• Work with large-scale temporal, economic, industrial, commodity, trade and market datasets
• Develop approaches for identifying leading indicators and hidden relationships across industries
• Build machine learning systems that combine structured, unstructured and event-driven data
• Experiment with causal inference, probabilistic modeling, graph-based approaches and modern machine learning techniques
• Design frameworks to evaluate forecast quality, uncertainty and confidence
• Collaborate closely with product and founders to turn research into customer-facing capabilities
• Help shape the technical direction of the company’s predictive intelligence platform

You have

• Strong background in machine learning, statistics, econometrics, quantitative modeling or forecasting
• Experience working with time-series, prediction systems or large-scale structured datasets
• Strong programming skills in Python and modern data science tooling
• Ability to reason about complex systems and relationships between variables
• Comfortable moving between research, experimentation and production systems
• Curious about economics, markets, supply chains, industries and how the world actually works

Bonus Points

• Experience with forecasting, demand prediction, econometrics or quantitative finance
• Experience building probabilistic or Bayesian models
• Experience with causal inference techniques
• Experience working with graph data or network effects
• Background in economics, operations research, physics, mathematics or related quantitative fields
• Experience taking models from research into production

Why Join?

You’ll be working on a problem that sits at the intersection of machine learning, economics and real-world decision making.

You’ll have the opportunity to help build a new category of predictive intelligence from the ground up, working directly alongside the founding team.

High ownership. High autonomy. Meaningful equity.

We have the chance to help teach machines how the world works and if you're interested in our mission.