how to fine-tune those models eg. XGBoost, Deep Neural Networks, Transformers, Markov chains, etc. Experience using specialized machine learning libraries e.g. Fastai, Keras, Tensorflow, pytorch, sci-kit learn, huggingface, etc. Must demonstrate the capacity of reading, understanding and implementing new techniques in the field of machine learning as More ❯
techniques and how to fine-tune those models e.g. XGBoost, Deep Neural Networks, Transformers, etc. Experience using specialized machine learning libraries e.g. Fastai, Keras, Tensorflow, pytorch, sci-kit learn, etc. Must demonstrate the capacity of reading, understanding and implementing new techniques in the field of machine learning as they More ❯
related field. Proficiency in programming languages such as Python, R, or Java. Strong understanding of mathematics and statistics. Experience with machine learning frameworks like TensorFlow, Keras, or PyTorch. Knowledge of data analysis and visualization tools (e.g., Pandas, NumPy, Matplotlib). Familiarity with big data technologies (e.g., Hadoop, Spark). More ❯
related field. Proficiency in programming languages such as Python, R, or Java. Strong understanding of mathematics and statistics. Experience with machine learning frameworks like TensorFlow, Keras, or PyTorch. Knowledge of data analysis and visualization tools (e.g., Pandas, NumPy, Matplotlib). Familiarity with big data technologies (e.g., Hadoop, Spark). More ❯
on experience with ML techniques such as XGBoost, deep neural networks, and transformers Practical knowledge of ML libraries and frameworks such as Fastai, Keras, TensorFlow, PyTorch, and Scikit-learn Ability to research, understand, and apply emerging machine learning techniques Programming & Data Engineering Proficiency in programming languages such as Python More ❯
or related field research - Experience programming in Java, C++, Python or related language - 3+ years' experience with modeling languages and tools like PyTorch/TensorFlow, R, scikit-learn, numpy, scipy, etc - Solid ML background and familiar with standard NLU, NLG, and LLM techniques PREFERRED QUALIFICATIONS - PhD in Computer Sciences More ❯
foundation in both machine learning and software engineering. Experience deploying machine learning models in production environments. Proficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch, scikit-learn). Familiarity with cloud platforms like GCP, AWS, or Azure. Experience with CI/CD pipelines for machine learning (e.g., Vertex More ❯
edinburgh, central scotland, united kingdom Hybrid / WFH Options
ADLIB
projects Strong track record of delivering machine learning or AI projects end-to-end Hands-on skills in Python, with frameworks like Scikit-learn, TensorFlow, PyTorch, or PySpark Deep understanding of data science best practices, including MLOps Strong stakeholder communication skillsable to translate complex insights into business impact Experience More ❯
methods and machine learning - Experience with prompting techniques for LLMs PREFERRED QUALIFICATIONS - Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc. - Experience with large scale distributed systems such as Hadoop, Spark etc. - PhD in math/statistics/engineering or other equivalent More ❯
or other equivalent quantitative discipline - Experience building machine learning models or developing algorithms for business application - Experience with deep learning libraries such as PyTorch, TensorFlow, MxNet Research publications in computer vision, deep learning or machine learning at peer-reviewed workshops, conferences or journals - Proven achievements of developing and managing More ❯
such as profiling and debugging and understanding of system performance and scalability Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc. PREFERRED QUALIFICATIONS Experience with popular deep learning frameworks such as MxNet and Tensor Flow. PhD Amazon is an equal opportunities employer. More ❯
Sr. Applied Scientist, Last Mile Science Are you passionate about solving complex logistics challenges that directly impact millions of customers? Our Logistics Analytics team is at the forefront of revolutionizing delivery experiences through data-driven solutions and innovative technology. As More ❯