What is Human Native?
At Human Native, we’re building an AI data marketplace that ensures creators and rights holders are fairly compensated for their work while providing AI developers with high-quality, responsibly licensed training data.
We believe in building AI the right way - ensuring transparency, fairness, and accessibility. This is a hard problem, and we need brilliant minds to help us solve it.
The Opportunity
As an ML Engineer, you’ll help us index, benchmark, and evaluate training datasets at scale. Your expertise with data, AI and ML training methodologies and evaluation techniques will advance the state of the art for developing AI.
You will work across:
- Designing and developing benchmarks that allow our customers to understand their value of data for training ML (quantifying dataset quality and biases).
- Deploy these benchmarks by implementing end-to-end data evaluation pipelines to be run on different datasets and ML models.
- Tools to visualise, analyze, and understand the attributes of datasets based on the evaluations.
- Develop ML models to transform, clean and understand data.
- Collaborating with cross-functional teams, including operations, software engineering, and product management, to integrate data evaluation tools and insights into product development.
Key Responsibilities
Engineering and Development
- Build scalable, high performance systems to support our AI data marketplace.
- Optimise data pipelines to improve data discovery and quality evaluation.
- Maintain cloud based ML infrastructure and ensure system reliability.
Collaboration and Product Thinking
- Work cross functionally to translate business needs into technical solutions.
- Advocate for pragmatic, simple solutions over unnecessary complexity.
- Communicate trade-offs and engineering decisions clearly.
Growth and Impact
- Help to define the engineering culture and best practices as we grow.
- Improve developer experience by building internal tools and automation.
- Ensure AI licensing remains fair, transparent, and responsible.
Our Ideal Candidate
Must Haves:
- Hands on experience developing and deploying ML models and ML data pipelines in production.
- Strong Statistical Analysis & Data Evaluation, you’re comfortable developing or learning to develop custom metrics, identify biases, and quantify data quality.
- Strong Python skills for Data & Machine Learning, familiarity with PyTorch and TensorFlow.
- Experience with distributed computing and big data — scaling ML pipelines for large datasets.
- Familiarity with cloud-based deployment (such AWS, GCP, Azure, or Modal).
- Experience in fast moving AI, ML or high growth environments, such as startups, research labs, or AI-driven product teams.
- Bachelor’s, Master’s, or PhD in Computer Science, Mathematics or a related field.
Nice to Haves:
- Experience with LLMs, NLP, or synthetic data generation.
- Familiarity with Rust or C++ for high performance ML applications.
- Experience working on search, ranking, or large scale data ingestion pipelines.
- Experience working with AI data management, responsible AI, or large-scale dataset processing.
Our Benefits
- A fast-growing company with opportunities for career advancement and learning.
- Competitive salary + stock options.
- Private medical insurance.
- Generous holiday allowance.
- Regular team offsites + social events.
- A small but mighty team making a real impact.
If you don't meet 100% of the qualifications but are excited about the role and feel you could be a good fit, we encourage you to apply. Studies have shown that women and people from underrepresented groups are less likely to apply for jobs unless they meet every qualification. At Human Native AI, we value diversity of thought and recognise that skills and experiences can be built in many ways. We look forward to hearing from you.
Apply for the job
Do you want to join our team as our new Machine Learning Engineer? Then we'd love to hear about you!
#J-18808-Ljbffr
