analysis, and statistical methodologies. Strong grasp of supervised/unsupervised methods, evaluation metrics, feature engineering, and model tuning. Proficiency in Python (pandas, NumPy, Scikit-learn); experience with PyTorch or TensorFlow for deep learning. Experience with API development and connecting AI systems to external platforms. Working knowledge in deep learning techniques, including CNNs, RNNs, and transformers. Hands-on experience in More ❯
RNN, LSTM), and generative models (GAN, VAE) to enhance predictive accuracy, interpretability, and automation. Engineer scalable analytical frameworks and reusable ML assets, integrating Python-based (or other) ML pipelines (TensorFlow, PyTorch, Scikit-learn, Pandas) with enterprise data platforms (Snowflake, Azure, Google Vertex AI) to standardise insight generation and model delivery. Collaborate with Data Architecture and Engineering to operationalise models More ❯
Proven experience designing and deploying MLOps pipelines (MLflow, Azure ML, Azure DevOps etc). Strong programming skills in Python and familiarity with common ML/AI libraries (scikit-learn, tensorflow, Keras etc.). Experience implementing machine learning and large language models (LLMs), encompassing deployment, monitoring, and retraining. Familiarity with software engineering guidelines: version control (e.g., Git), CI/CD More ❯
systems and deep learning architectures Strong understanding of two-tower neural networks, embedding techniques, and ranking models Proficiency in Python and ML libraries (e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) Familiarity with cloud platforms (GCP, AWS, Azure) and tools like Dataiku Experience with ML Ops, including deployment, monitoring, and retraining pipelines Ability to work cross-functionally with marketing More ❯
Transformers, OpenAI API, LangChain, or similar Experience fine-tuning large transformer models or implementing retrieval-augmented generation systems Strong Python programming skills and familiarity with ML libraries (e.g., PyTorch, TensorFlow) Knowledge of prompt engineering best practices and prompt optimization Understanding of LLM evaluation methods, including human-in-the-loop and automated metrics Familiarity with deploying LLMs in cloud or More ❯
weekends 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 More ❯
design Experience with game engine audio implementation and middleware (e.g., Wwise, FMOD Studio, Unreal MetaSounds) Understanding of DSP and audio signal processing Hands-on experience integrating machine learning models (TensorFlow, PyTorch, ONNX) into production pipelines for tasks such as inference, data processing, and generative workflows Experience debugging code across various development environments Experience managing collaboration tools and version control More ❯
system architecture, mentoring junior team members, and conducting thorough code reviews Strong programming skills in Python and C++, with experience using libraries and frameworks such as PyTorch, NumPy, Pandas, TensorFlow, and OpenCV for computer vision and data processing Familiarity with front-end technologies including JavaScript and HTML for building user-facing interfaces or tools Practical, hands-on experience in More ❯
Experience: 3–5+ 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 More ❯
and implementing mobile applications using Flutter for both iOS and Android platforms (native experience is a big plus). Integrating and optimizing Apple CoreML YOLO models for iOS and TensorFlow Lite and Tencent NCNN YOLO models for Android. Ensuring high performance and responsiveness of the applications for real-time AI processing. Collaborating with cross-functional teams to define, design … native mobile development for iOS and Android. Familiarity with machine learning and computer vision models, particularly YOLO models. Experience with iOS frameworks such as CoreML, and Android frameworks like TensorFlow Lite and Tencent NCNN. Excellent problem-solving skills and the ability to perform in a fast-paced, high-intensity environment. Strong communication skills to effectively collaborate with multi-disciplinary More ❯
