Lead Machine Learning Engineer (3-6 month contract)

Freelancer, Full-time · Remote

The Role

Please note, due to the senior and unique nature of this role we ideally require someone with a strong scientific background (i.e. BioChemistry, Chemistry or Physics) or experience handling and processing large amounts of raw scientific data, as you’ll be developing machine learning and LLM systems based on materials engineering. 

As we continue to grow into 2025 and beyond, we’re looking for an experienced freelancer to help us develop our Packaging Development AI Engine. 

The role will involve integrating our current data and previously built prediction models to an AI system recommender. As an experienced Machine Learning Engineer, you will use your skills to develop and integrate new AI and ML approaches to power our internal Material Science Platform. 

We’re looking for an experienced engineer skill in not only architecting and building similar systems, but then also providing additional monitor for performance and model maintenance, helping deploy the successful and efficient models into production.

You’ll also be designing AI agents that emulate scientific reasoning. Domain expertise is essential for accurately developing, interpreting, and managing these systems. 


In a startup environment, you'll need to work independently, applying advanced ML techniques to complex, scientifically-sourced data to ensure robust performance.

Given the remote first nature of our team, this role can be based anywhere but willing to work approx UTC/UTC+2 core hours, in order to overlap with the bulk of our European based team.
How you'll help build one•fıve

Develop our core AI Engine

  • You’ll bring state-of-the-art AI research from concept to implementation to create AI-driven applications with a direct impact on our packaging development processes.

  • You’ll work closely with stakeholders and other engineers to evaluate and optimize our systems for performance and accuracy and ensure they are production-ready. 

Coordinate ML requirements with stakeholders

  • Surface requirements to other teams (data engineers, domain experts and software engineers) to ensure data harvesting and processing aligns with our AI development needs.

Who you are
  • Extensive hands-on experience of developing and implementing advanced machine learning or AI systems. Experience with Deep Learning or LLMs is preferred

  • Experience implementing systems to detect data drift and building scalable deployment solutions.

  • Experience spearheading ML and data-heavy projects 

  • Experience bringing machine learning applications to production (end to end development)

  • Strong programming skills in Python, familiarity with libraries and tools such as langchain/haystack, pytorch/tensorflow, spancy/nltk, scikit-learn, MLflow, GCP, VertexAI, etc. 

  • Experience with vector databases and knowledge graph systems is a plus

  • Experience working with complex, scientific/chemistry-like data and metadata, such as lab generated measurements and experimental conditions, industrial trial data, etc.

  • Strong problem-solving skills and ability to work independently in a remote set up

  • Ability to work independently and proven stakeholder management

  • Experience implementing and coordinating with domain experts in multifunctional environments 

  • Fluency in English, as this is our working language

one•fıve values
  • Duty to care: care for yourself, your colleagues, your work, our offices, and ultimately, our planet

  • Create with intent: work with a goal in mind. Ask yourself what you are trying to achieve and constantly evaluate whether your current path is the best way to achieve this goal

  • Acknowledge the process: we celebrate our failures and successes together, and keep iterating to improve

  • Transparency: all knowledge is accessible to everyone

Hiring Process

We want you to know what to expect out of your candidate experience with us and make this as much as possible a two sided process, allowing you to get to know us as well. 


Once submitted, your CV will be reviewed by the People team, and shortlisted for interviews. 

Everyone will be contacted to find out the outcome of their application. 


We have four interview stages: 

  1. Introduction Google Hangouts call with our Talent Manager - to share more about one.five and how we work & find out how that meets your experience and expectations of the role.

  2. Technical interview with Head of Software & Data and another senior stakeholder - to dig into the day to day of the role more and answer any questions you may have for us.

  3. Present a short demo of an ML project followed by brief Q&A.

  4. Final introduction to key stakeholders in the business to better build your understanding of your future function, as well as discuss our core values.

Diversity & Inclusion

We are very proud of the culture we have built to support diversity & inclusion and will do everything we can to continue to be an inclusive company where all team members are comfortable, supported and empowered to succeed. 

We seek to ensure that all employees are afforded equal opportunities and treatment, irrespective of any qualifier, in all aspects of recruitment, employment, training and determination of benefits. 

For sake of clarity, all team members and candidates will receive equal treatment regardless of age, disability, gender reassignment, marital or civil partner status, pregnancy or maternity, race, colour, nationality, ethnic or national origin, religion or belief, sex or sexual orientation. 

If you require any accommodations for the interview process, please include them in your application or in scheduling requests for a first call. 

About us
Protecting our planet by developing materials for clean & closed material loops. 

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