Machine Learning Engineer Lisboa

Machine Learning Engineer
Lisboa
Lisboa, Lisboa, Portugal

About Sibvi

Sibvi is an advanced AI-driven forecasting platform designed to tackle the complexity of
- world time series forecasting by matching the right data to every prediction challenge. Unlike traditional forecasting tools that rely only on a company’s internal historical data, Sibvi dynamically integrates over a trillion data points from diverse external sources to enrich forecasts. By combining massive data with proprietary user data and a powerful
- discovery engine, Sibvi delivers forecasts that are more accurate, explainable, and actionable. The platform’s innovation lies in how it intelligently finds and uses the most relevant signals from an ocean of information, thereby improving any forecasting process.

Join us in building the future of supply chain intelligence - efficient, sustainable, and predictive.

Your Role

As a Machine Learning Engineer you’ll play a critical role in productionizing and scaling our embedding, forecasting and agentic systems. From robust orchestration and delivery pipelines to smart automation of model and agent life cycles, you’ll collaborate closely with data scientists, product engineers, and domain experts to deliver
- world impact.

This is a
- on engineering role with high ownership and visibility across the company. You’ll help ensure that our models don’t just work, but work reliably, at scale, and with clear auditability.

What You’ll Do

- Design and maintain scalable ML orchestration workflows (e. g. , Airflow, Prefect, Kedro)

- Monitor pipeline performance, implement distributed execution, logging, error handling, and recovery strategies

- Collaborate with data scientists to develop and implement, deploy, version, and optimize embedding and forecasting models in production

- Develop and own micro services for data ingestion, model execution, and forecast delivery

- Implement auditability, observability, and automated reporting for ML systems

- Continuously improve data and model infrastructure for speed, scalability, and maintainability

- Participate in architectural planning as we scale our systems and customer base

What We’re Looking For

- 4+ years of experience in ML engineering/ ML infrastructure or data platform roles

- Production grade Python skills and experience with orchestration tools and micro services

- Solid understanding of Postgre
SQL and data modeling best practices

- Familiarity with API frameworks such as Fast
API or Flask

- Able to efficiently use model frameworks like Py
Torch or JAX in order to implement and refine deep learning models

- Experience in managing the full model life cycle including design, training, testing, deployment/inference and continuous monitoring/distribution shifts for machine learning models using typical frameworks like e. g. MLFlow

- Experience in deploying machine learning models and pipelines in production environments

- Familiarity with containerization, Docker, CI/CD, and cloud infrastructure (AWS, GCP)

- Comfortable working independently and taking initiative in
- paced, ambiguous settings

- Strong communication skills (in English) and ability to collaborate across teams

Bonus points for:

- Experience in forecasting, supply chain, or manufacturing domains

- Familiarity with distributed training (multi-GPU, etc. )

- Experience with GPU programming using CUDA and/or Triton

- Experience with model compilation (torch compile, ONNX, etc. )

What We Offer:

- A rare opportunity to build core systems at the heart of a
- impact product

- A collaborative,
- performance culture led by experienced founders

- Competitive compensation with potential equity upside

- Flexible working hours and
- friendly setup

- Clear growth path toward technical leadership as the team expands

Let’s build a smarter, more sustainable supply chain — together.