ML Engineer (Forecasting) | NDA
GT • Europe - Remote
Posted: May 29, 2026
Job Description
GT was founded in 2019 by a former Apple, Nest, and Google executive. GT’s mission is to connect the world’s best talent with product careers offered by high-growth companies in the UK, USA, Canada, Germany, and the Netherlands.
Our clients operate in industries like healthcare, life sciences, fintech, retail, e-commerce, finance and many more - giving our team exposure to real-world, high-impact projects.
About the Role
We’re looking for an AI/ML Engineer to join a UK-based client in the healthcare and pharmacy domain.
The role focuses on forecasting and time-series modeling, developing solutions that directly improve operational efficiency.
Project duration: 12 weeks (with possible extension).
Start date: June 15 (flexible - part-time start possible).
Project Details:
The project focuses on developing a forecasting solution for a large healthcare network.
It uses historical clinic and marketing data to predict clinic usage and staffing needs, helping optimize scheduling and resource allocation.
The goal is to build a scalable, data-driven platform that improves operational efficiency.
Responsibilities:
Design, train, and deploy ML models for time-series forecasting and related data tasks
Build and maintain data pipelines using cloud-native tools (AWS, GCP, or Azure)
Develop and optimize forecasting models (Prophet, ARIMA, LSTM, TimeGPT)
Collaborate with data, product, and cloud engineers to deliver reliable, scalable solutions
Participate in different stages of the project lifecycle - from discovery and PoC to production deployment, presenting your work to stakeholders
Essential knowledge, skills & experience (must-have):
4+ years of experience in Machine Learning / Data Science
Proven experience with forecasting / time-series modeling (Prophet, ARIMA/SARIMA, LSTM, TimeGPT, XGBoost or similar)
Strong Python skills (Pandas, NumPy, scikit-learn, PyTorch)
Experience with model deployment and production ML systems
Familiarity with data preprocessing and feature engineering for time-series data
Familiarity with cloud environments (Azure, AWS, or GCP)
Version control (Git) and SQL
Advanced English level
Nice-to-have:
Experience with Generative AI / LLMs
Experience with RAG pipelines
Experience with vector databases (Weaviate, Milvus)
Familiarity with LLM evaluation frameworks (e.g. DeepEval)
Soft Skills
Strong sense of ownership and accountability
Proactive attitude and ability to work independently
Clear and confident communication with both tech and non-tech stakeholders
Comfortable working in ambiguity and helping define requirements
Strategic thinking and focus on business impact
Team player
Interview Steps
GT interview with Recruiter
Technical interview
Final interview
Additional Content
GT was founded in 2019 by a former Apple, Nest, and Google executive. GT’s mission is to connect the world’s best talent with product careers offered by high-growth companies in the UK, USA, Canada, Germany, and the Netherlands.
Our clients operate in industries like healthcare, life sciences, fintech, retail, e-commerce, finance and many more - giving our team exposure to real-world, high-impact projects.
About the Role
We’re looking for an AI/ML Engineer to join a UK-based client in the healthcare and pharmacy domain.
The role focuses on forecasting and time-series modeling, developing solutions that directly improve operational efficiency.
Project duration: 12 weeks (with possible extension).
Start date: June 15 (flexible - part-time start possible).
Project Details:
The project focuses on developing a forecasting solution for a large healthcare network.
It uses historical clinic and marketing data to predict clinic usage and staffing needs, helping optimize scheduling and resource allocation.
The goal is to build a scalable, data-driven platform that improves operational efficiency.
Responsibilities:
Design, train, and deploy ML models for time-series forecasting and related data tasks
Build and maintain data pipelines using cloud-native tools (AWS, GCP, or Azure)
Develop and optimize forecasting models (Prophet, ARIMA, LSTM, TimeGPT)
Collaborate with data, product, and cloud engineers to deliver reliable, scalable solutions
Participate in different stages of the project lifecycle - from discovery and PoC to production deployment, presenting your work to stakeholders
Essential knowledge, skills & experience (must-have):
4+ years of experience in Machine Learning / Data Science
Proven experience with forecasting / time-series modeling (Prophet, ARIMA/SARIMA, LSTM, TimeGPT, XGBoost or similar)
Strong Python skills (Pandas, NumPy, scikit-learn, PyTorch)
Experience with model deployment and production ML systems
Familiarity with data preprocessing and feature engineering for time-series data
Familiarity with cloud environments (Azure, AWS, or GCP)
Version control (Git) and SQL
Advanced English level
Nice-to-have:
Experience with Generative AI / LLMs
Experience with RAG pipelines
Experience with vector databases (Weaviate, Milvus)
Familiarity with LLM evaluation frameworks (e.g. DeepEval)
Soft Skills
Strong sense of ownership and accountability
Proactive attitude and ability to work independently
Clear and confident communication with both tech and non-tech stakeholders
Comfortable working in ambiguity and helping define requirements
Strategic thinking and focus on business impact
Team player
Interview Steps
GT interview with Recruiter
Technical interview
Final interview