experience leading projects or teams is a plus for a lead role Programming & ML Skills: Advanced programming skills in Python (including libraries such as pandas, scikit-learn, TensorFlow/PyTorch). Solid understanding of ML algorithms, model evaluation techniques, and optimisation. Experience with NLP techniques, generative AI or financial data modelling is advantageous Cloud & DevOps: Proven experience with AWS cloud More ❯
experience leading projects or teams is a plus for a lead role Programming & ML Skills: Advanced programming skills in Python (including libraries such as pandas, scikit-learn, TensorFlow/PyTorch). Solid understanding of ML algorithms, model evaluation techniques, and optimisation. Experience with NLP techniques, generative AI or financial data modelling is advantageous Cloud & DevOps: Proven experience with AWS cloud More ❯
Who You Are 2+ Programming experience, from either an engineering role, a computer science degree, or personal projects Python proficiency Experience using any of the following: Keras, Tensorborad, Tensorflow, Pytorch, Pytorch Lightning, Jupyter notebooks, colabs, matplotlib and other ML frameworks and tools A passion for connecting with real users and enabling them to be power users of the product Good More ❯
related quantitative field), or equivalent industry research experience. • Ideally 3+ years in machine learning/deep learning/LLMs or adjacent advanced AI research. • Proficient in Python; experience with PyTorch or JAX. • Understanding of reinforcement learning, multi-agent systems, probabilistic/Bayesian methods, or large-scale training. • Curiosity-driven mindset, strong problem solving, and the ability to work cross-functionally. More ❯
5+ years in AI/ML engineering with a track record of deploying AI into production at scale. Technical Skills: Strong backend Python; expertise with ML frameworks (TensorFlow, PyTorch, Scikit-Learn, etc.); familiarity with modern data pipeline tools (Airflow, Spark, Kafka) and workflow orchestration frameworks such as n8n or LangGraph. Applied AI: Background in enterprise applications such as chatbots, workflow More ❯
participate in the upside of an ultra-growth venture. Have fun Apply if: You have experience with our stack: Python, FastAPI, Postgres, SQLAlchemy, Alembic, Typescript, React, LlamaIndex/LangChain, PyTorch, HuggingFace, OpenAI, Docker, Azure, You have taken entire products or features from ideation to deployment and you've measured their impact. You enjoy diving deep into the domain, understanding the More ❯
learning models, particularly for sequential data (e.g. time series, language) using techniques such as LSTMs or transformers. Hands-on experience with modern Machine/Deep Learning frameworks such as PyTorch, TensorFlow, or Hugging Face Transformers. Familiarity with both pre-training and fine-tuning of large-scale models. Experience working with structured and unstructured data, such as text, logs, or time More ❯
of taking responsibility for projects from conception over implementation to production use Strong experience in Python, including its bindings to native code in C++ or Rust Deep familiarity with PyTorch and the AI software ecosystem. Key technologies include the PyTorch Distributed library, large-scale training frameworks like Megatron-LM or TorchTitan and highly-optimized inference libraries such as TensorRT-LLM More ❯
