similar Python frameworks like Streamlit) for dashboard creation. Experience with Machine Learning model development and data science workflows (including frameworks such as scikit-learn, PyTorch, or TensorFlow). Experience in Quantitative Finance or strong interest in mathematical/financial modeling, derivatives pricing, or algorithmic trading. Familiarity with ETRM platforms (e.g. More ❯
similar Python frameworks like Streamlit) for dashboard creation. Experience with Machine Learning model development and data science workflows (including frameworks such as scikit-learn, PyTorch, or TensorFlow). Experience in Quantitative Finance or strong interest in mathematical/financial modeling, derivatives pricing, or algorithmic trading. Familiarity with ETRM platforms (e.g. More ❯
CD pipelines, monitoring frameworks). Strong proficiency in Python and libraries like Pandas, NumPy, and scikit-learn, with familiarity in frameworks like TensorFlow or PyTorch being a plus Cloud experience—AWS preferred - including deploying and managing models in cloud environments (will still consider GCP/Azure) Curious and pragmatic mindset More ❯
prior industry experience. We are happy to consider candidates with a Ph.D and industry experience through internships Experience with deep learning frameworks such as PyTorch Proficiency in software engineering An understanding of Computer Science and software engineering fundamentals such as data structures and algorithms and a data oriented approach to More ❯
for data querying and manipulation. Experience with Git, Bash, Docker, and machine learning pipelines. Experience with open-source machine learning libraries like scikit-learn, PyTorch, TensorFlow, and SciPy. Hands-on experience working with multi-modal data (images, text) and relevant ML techniques. Experience with cloud technologies and data storage solutions More ❯
role is for you if: Python for API and Model development (Machine learning frameworks and tooling e.g. Sklearn) and (Deep learning frameworks such as Pytorch and Tensorflow). Understanding of machine learning techniques. Experience with data manipulation libraries (e.g. Pandas, Spark, SQL). Git for version control. Cloud experience (we More ❯
role is for you if: Python for API and Model development (Machine learning frameworks and tooling e.g. Sklearn) and (Deep learning frameworks such as Pytorch and Tensorflow). Understanding of machine learning techniques. Experience with data manipulation libraries (e.g. Pandas, Spark, SQL). Git for version control. Cloud experience (we More ❯
role is for you if: Python for API and Model development (Machine learning frameworks and tooling e.g. Sklearn) and (Deep learning frameworks such as Pytorch and Tensorflow). Understanding of machine learning techniques. Experience with data manipulation libraries (e.g. Pandas, Spark, SQL). Git for version control. Cloud experience (we More ❯
role is for you if: Python for API and Model development (Machine learning frameworks and tooling e.g. Sklearn) and (Deep learning frameworks such as Pytorch and Tensorflow). Understanding of machine learning techniques. Experience with data manipulation libraries (e.g. Pandas, Spark, SQL). Git for version control. Cloud experience (we More ❯
experience). 2-3 years of experience in machine learning, with a strong understanding of core ML algorithms and frameworks (e.g., scikit-learn, TensorFlow, PyTorch). Hands-on experience with data preprocessing, feature engineering, and model training for real-world problems. Strong Python and Java programming skills and familiarity with More ❯
Newcastle Upon Tyne, Tyne And Wear, United Kingdom
Newcastle University
methodologies, including supervised and unsupervised learning on image and tabular data. Familiarity with some of the latest AI frameworks and libraries, such as TensorFlow, PyTorch, Keras, etc Programming skills : Experience with scripting languages such as Python for data analysis and machine learning applications and software development Data management skills : Proficiency More ❯
or setting up and scaling MLOps platforms in global organizations. Technical Expertise: Strong understanding of AI/ML technologies, algorithms, and frameworks (e.g., TensorFlow, PyTorch, ONNX), as well as experience with AI/ML workload optimization and deployment. Deep expertise in data architecture and engineering principles, data modelling, ETL processes More ❯
required: Programming: Proficiency in Python (preferred) and/or other relevant languages (e.g., R, Java, C++). Machine Learning & AI Frameworks: Experience with TensorFlow, PyTorch, Scikit-learn, or similar libraries. Data Manipulation & Analysis: Strong skills in Pandas, NumPy, and SQL for handling and analysing large datasets. Cloud Computing: Familiarity with More ❯
london (camden town), south east england, united kingdom
Wowcher
required: Programming: Proficiency in Python (preferred) and/or other relevant languages (e.g., R, Java, C++). Machine Learning & AI Frameworks: Experience with TensorFlow, PyTorch, Scikit-learn, or similar libraries. Data Manipulation & Analysis: Strong skills in Pandas, NumPy, and SQL for handling and analysing large datasets. Cloud Computing: Familiarity with More ❯
match you must have: 1+ years in a Machine Learning or ML Engineering role, with hands-on experience in deep learning frameworks (e.g., TensorFlow, PyTorch). Motivated recent graduates are encouraged to apply! A degree in Mathematics, Engineering, Statistics, Computer Science, Physics, or a related field. An advanced degree is More ❯
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 AI). More ❯
variety of distributed computing, enterprise environments. Experience with at least one of the modern distributed Machine Learning and Deep Learning frameworks such as TensorFlow, PyTorch, MxNet Caffe, and Keras. Experience building large-scale machine-learning infrastructure that have been successfully delivered to customers. Experience defining system architectures and exploring technical More ❯
publication record in top-tier conferences (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, NAACL, ICLR). Familiarity with one or more deep learning frameworks (e.g. pytorch, jax, tensorflow, ) Experience in ML Research beyond completing a PhD (e.g. supervision, industry experience, leading academic initiatives, ). Excellent communication skills to report and present More ❯
to Apache Spark or Hadoop is beneficial. Cloud Platforms : Proficiency with AWS , GCP , or Azure . ML Frameworks : Hands-on with scikit-learn , TensorFlow , PyTorch , or related libraries. More ❯
communicating across technical and non-technical audiences. - Experience in using Python and hands-on experience building models with deep learning frameworks like TensorFlow, Keras, PyTorch, MXNet. - Fluency in written and spoken English. PREFERRED QUALIFICATIONS - Knowledge of AWS tech stack (e.g., AWS Redshift, S3, EC2, Glue). - PhD or Master's More ❯
a related field. Proficiency in programming languages like Python, R, or SQL for data manipulation. Experience building machine learning models using libraries like TensorFlow, PyTorch, or scikit-learn. Familiarity with cloud platforms like AWS, GCP, or Azure. Strong written and spoken English skills. Bonus Experience: Experience with big data tools More ❯
degree in computer science, or related technical, math, or scientific field. Proven knowledge of deep learning and experience using Python and frameworks such as Pytorch, TensorFlow. Proven knowledge of Generative AI and hands-on experience of building applications with large foundation models. Experiences related to AWS services such as SageMaker More ❯
plus. Hands-on experience with Google Cloud AI tools, such as Vision AI, Speech-to-Text, or AutoML. Proficiency in ML frameworks like TensorFlow, PyTorch, or Scikit-learn. Expertise in container orchestration for AI workloads using Google Kubernetes Engine (GKE) or Kubernetes. Background in software engineering, data science, or AI More ❯
plus. Hands-on experience with Google Cloud AI tools, such as Vision AI, Speech-to-Text, or AutoML. Proficiency in ML frameworks like TensorFlow, PyTorch, or Scikit-learn. Expertise in container orchestration for AI workloads using Google Kubernetes Engine (GKE) or Kubernetes. Background in software engineering, data science, or AI More ❯
experience in designing, developing and deploying production-level deep learning recommendation models with a proven business impact. Fluency in Python, Pandas/Dask, SQL, PyTorch or Tensorflow. Ability to write readable and maintainable code. Strong communication and storytelling skills with both technical and non-technical audiences. Ability to present complex More ❯
