Machine Learning Engineer

What is Human Native? At Human Native, we’re buildingan AI data marketplace that ensures creators and rights holders arefairly compensated for their work while providing AI developerswith high-quality, responsibly licensed training data. We believein building AI the right way - ensuring transparency, fairness, andaccessibility. This is a hard problem, and we need brilliant mindsto help us solve it. The Opportunity As an ML Engineer, you’ll helpus index, benchmark, and evaluate training datasets at scale. Yourexpertise with data, AI and ML training methodologies andevaluation techniques will advance the state of the art fordeveloping AI. You will work across: - Designing and developingbenchmarks that allow our customers to understand their value ofdata for training ML (quantifying dataset quality and biases). -Deploy these benchmarks by implementing end-to-end data evaluationpipelines to be run on different datasets and ML models. - Tools tovisualise, analyze, and understand the attributes of datasets basedon the evaluations. - Develop ML models to transform, clean andunderstand data. - Collaborating with cross-functional teams,including operations, software engineering, and product management,to integrate data evaluation tools and insights into productdevelopment. Key Responsibilities Engineering and Development -Build scalable, high performance systems to support our AI datamarketplace. - Optimise data pipelines to improve data discoveryand quality evaluation. - Maintain cloud based ML infrastructureand ensure system reliability. Collaboration and Product Thinking -Work cross functionally to translate business needs into technicalsolutions. - Advocate for pragmatic, simple solutions overunnecessary complexity. - Communicate trade-offs and engineeringdecisions clearly. Growth and Impact - Help to define theengineering culture and best practices as we grow. - Improvedeveloper experience by building internal tools and automation. -Ensure AI licensing remains fair, transparent, and responsible. OurIdeal Candidate Must Haves: - Hands on experience developing anddeploying ML models and ML data pipelines in production. - StrongStatistical Analysis & Data Evaluation, you’re comfortabledeveloping 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 MLpipelines for large datasets. - Familiarity with cloud-baseddeployment (such AWS, GCP, Azure, or Modal). - Experience in fastmoving 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 toHaves: - 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 dataingestion pipelines. - Experience working with AI data management,responsible AI, or large-scale dataset processing. Our Benefits - Afast-growing company with opportunities for career advancement andlearning. - Competitive salary + stock options. - Private medicalinsurance. - Generous holiday allowance. - Regular team offsites +social events. - A small but mighty team making a real impact. Ifyou don't meet 100% of the qualifications but are excited about therole and feel you could be a good fit, we encourage you to apply.Studies have shown that women and people from underrepresentedgroups are less likely to apply for jobs unless they meet everyqualification. At Human Native AI, we value diversity of thoughtand recognise that skills and experiences can be built in manyways. We look forward to hearing from you. Apply for the job Do youwant to join our team as our new Machine Learning Engineer? Thenwe'd love to hear about you! #J-18808-Ljbffr