A tech-focused environmental company are seeking a full-time Machine Learning engineer to help deliver on their ambitious roadmap for using AI to alleviate the R&D bottlenecks experienced by researchers and entrepreneurs in the exciting area of biomaterials. You’ll partner closely with their full-stack developers and AI lead on a broad range of tasks, from creating some of their first prototypes and validating different approaches through to building and deploying robust user-facing solutions.
If you are a dedicated, passionate, and hardworking technology professional in the early stages of your career, this presents a fantastic opportunity to join a distinctive and ambitious startup environment. You will have the chance to develop your skills with the guidance of experienced mentors in the fields of generative AI.
Responsibilities:
- Carry out end-to-end development of AI-powered software tools for biomaterial researchers and entrepreneurs, with a special focus on generative AI and LLMs.
- Build prototypes and tools using the latest AI offerings from large cloud providers or the open-source ecosystem.
- Co-design, run and analyse experiments to compare alternative models/approaches, and iterate to reach quality and safety goals.
- Generate and analyse ideas for new datasets to leverage for model adaptation and evaluation.
- Use user feedback to improve the system.
- Develop and manage data pipelines that power model adaptation and evaluation.
- Deploy, monitor and manage the resulting new AI-based software.
- Communicate efficiently with the rest of the team to share findings, feed into planning and share ML expertise.
- Bachelor’s degree in a technical field (e.g. Computer Science), or equivalent foundational training.
- 3+ years of professional experience in a data-driven environment.
- Strong grasp of ML fundamentals and LLMs in particular.
- Practical experience building and evaluating NLP/ML-based systems, especially LLMs for conversational settings.
- Strong Python programming skills.
- Familiarity with best practices in version control, software engineering, testing and deployment.
- Familiarity with a cloud computing platform (e.g. GCP/AWS/Azure).
- Excellent problem-solving and analytical skills.
- Strong communication and collaboration skills, with the ability to convey technical concepts to non-technical audiences.
- Masters or PhD degree in a related field.
- Practical experience with any of the following techniques: prompt design and optimization, LLM fine-tuning, vector search (RAG), LLM tool-use, data augmentation, model distillation.
- Familiarity with open-source LLM models and frameworks, e.g. HuggingFace, LlamaIndex, LangChain.
- Familiarity with GCP/Vertex AI APIs.
- Experience with deep learning frameworks such as TensorFlow/PyTorch/Jax.
- Background in chemistry, polymer or materials science is highly advantageous.
- Experience working in a small startup.