Experience in machine learning and data engineering., Proficiency in building scalable data pipelines, preferably using Ray.io., Familiarity with AWS integrations and best practices., Strong problem-solving skills and ability to work in a fast-paced environment..
Key responsabilities:
Develop ML infrastructure for a sustainability-driven platform.
Build LLM-powered tools for data gathering and analysis.
Design and implement scalable data processing pipelines.
Advance prediction models and improve search algorithms.
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In the world of recruitment agencies, prevailing reputation for transactional dealings often overshadows genuine connection and mutual benefit. Candidates can feel like commodities, placed hastily into roles without regard for their career aspirations. Similarly, clients perceive agencies as impersonal intermediaries more concerned with quotas than understanding their specific business needs. We aim to redefine this narrative. We see an opportunity to transform the industry by prioritising integrity, innovation and personalised service.
Get in touch at hello@rocketscout.co 🚀
We are working with an incredibly exciting early stage startup that is tackling one of the biggest environmental challenges of our time: making industrial processes more sustainable.
Our client is developing a cutting-edge platform that enables engineers and researchers to explore more efficient and environmentally friendly alternatives in manufacturing starting with one of the world’s most emissions-intensive industries.
About The Role
As a Machine Learning Data Engineer, you will play a critical role in developing the ML infrastructure that powers this sustainability-driven platform. You'll work on cutting-edge challenges in data extraction, classification, and prediction—leveraging advanced LLM strategies and scalable data pipelines.
What You’ll Do
You’ll be at the heart of building a smarter, more sustainable way to design manufacturing processes. Your work will directly impact how engineers and scientists make decisions, helping them choose better alternatives without the usual complexity.
Build smart LLM-powered tools to gather, structure, and analyze massive datasets from a variety of sources.
Design scalable data pipelines using Ray.io, ensuring clean, structured, and efficient data processing.
Experiment with LLM prompting strategies to extract, standardize, and classify complex information.
Advance our bill of materials prediction model, helping engineers make smarter material choices.
Improve product search and matching algorithms using cutting-edge embedding and classification techniques.
Take ownership of AWS integrations, ensuring everything runs smoothly and follows best practices.
You’ll have a lot of freedom in how you approach challenges and will be trusted to find the best way forward.
Who You Are
They’re looking for someone who’s more than just technical expertise, you’re someone who thrives in a fast-moving, impact-driven environment.
You take initiative. Given a problem, you don’t wait for step-by-step instructions—you figure out what needs to be done and run with it.
You care about efficiency. You know that speed matters, but so does building the right thing in the right way.
You think like an owner. You take responsibility for your work, your team, and the broader mission.
You’re adaptable. You’re comfortable with ambiguity and thrive in environments where things evolve quickly.
You’re customer-focused. You don’t just build for the sake of it—you want to create something that truly makes a difference for end users.
If you're excited by the opportunity to apply machine learning to sustainability and want to work with a small but ambitious, mission-driven team apply now!
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Experience
Spoken language(s):
English
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