51 to 75 of 432 PyTorch Jobs

Level 6 or Level 7 AI/ML/Data Science apprenticeship programme. Core Skills & Competencies Technical Skills Programming proficiency in Python and common ML libraries such as TensorFlow, PyTorch, or similar. Experience with Jupyter Notebooks and version control (Git/GitHub). Basic understanding of supervised/unsupervised learning, neural networks, or clustering. Analytical Abilities Ability to interpret data More ❯

implementation. Experience with CSS frameworks and responsive design. Strong problem-solving skills and attention to detail. Nice to Have Experience with ML and/or computer vision frameworks like PyTorch, Numpy or OpenCV. Knowledge of ML model serving infrastructure (TensorFlow Serving, TorchServe, MLflow). Knowledge of WebGL, Canvas API, or other graphics programming technologies. Familiarity with big data technologies (Kafka More ❯

An honest approach to problem-solving, and ability to collaborate with peers, stakeholders and management Industry experience with machine learning teams Working knowledge of common ML frameworks such as PyTorch, ONNX, DeepSpeed etc. Prior experience with cloud-native technologies like Kubernetes, Argo Workflows, Buildpacks, etc. Experience with cloud providers such as AWS, GCP or Azure A track record of collaboration More ❯

and information retrieval (RAG), language translation, NER, summarization and topic modeling Familiarity with LLM training and efficient finetuning (PEFT, LoRA, Quantization) Experience with NLP/CV libraries such as PyTorch, TensorFlow, Scikit-learn, spaCy, HuggingFace Transformers/Diffusers, OpenAI, LangChain, Semantic Kernel & OpenCV Experience using Cloud solutions (AWS, Azure, etc.) for building and deploying applications Experience in a fast-paced More ❯

ML lifecycle management (source control, CI/CD for models, model registries, etc.) on Azure or similar platforms. Proficiency in Python and common ML frameworks (scikit-learn, TensorFlow/PyTorch) and experience with code review and DevOps processes. Leadership & Communication: Excellent leadership and interpersonal skills. Able to interface with client stakeholders to explain complex AI concepts in business terms, gather More ❯

ML lifecycle management (source control, CI/CD for models, model registries, etc.) on Azure or similar platforms. Proficiency in Python and common ML frameworks (scikit-learn, TensorFlow/PyTorch) and experience with code review and DevOps processes. Leadership & Communication: Excellent leadership and interpersonal skills. Able to interface with client stakeholders to explain complex AI concepts in business terms, gather More ❯

ML lifecycle management (source control, CI/CD for models, model registries, etc.) on Azure or similar platforms. Proficiency in Python and common ML frameworks (scikit-learn, TensorFlow/PyTorch) and experience with code review and DevOps processes. Leadership & Communication: Excellent leadership and interpersonal skills. Able to interface with client stakeholders to explain complex AI concepts in business terms, gather More ❯

. Advanced experience with SQL 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, including Snowflake. Understanding of personalization More ❯

NumPy, scikit-learn, etc.). Comfort working with large and complex datasets, including data wrangling and exploratory analysis. Experience (or strong interest) in GPU-powered model development (e.g. using PyTorch, TensorFlow, JAX, or similar). Demonstrated ability to work independently on real-world projects. Strong communicator, with the ability to share ideas, take feedback, and collaborate effectively. A master’s More ❯

NumPy, scikit-learn, etc.). Comfort working with large and complex datasets, including data wrangling and exploratory analysis. Experience (or strong interest) in GPU-powered model development (e.g. using PyTorch, TensorFlow, JAX, or similar). Demonstrated ability to work independently on real-world projects. Strong communicator, with the ability to share ideas, take feedback, and collaborate effectively. A master’s More ❯

NumPy, scikit-learn, etc.). Comfort working with large and complex datasets, including data wrangling and exploratory analysis. Experience (or strong interest) in GPU-powered model development (e.g. using PyTorch, TensorFlow, JAX, or similar). Demonstrated ability to work independently on real-world projects. Strong communicator, with the ability to share ideas, take feedback, and collaborate effectively. A master’s More ❯

NumPy, scikit-learn, etc.). Comfort working with large and complex datasets, including data wrangling and exploratory analysis. Experience (or strong interest) in GPU-powered model development (e.g. using PyTorch, TensorFlow, JAX, or similar). Demonstrated ability to work independently on real-world projects. Strong communicator, with the ability to share ideas, take feedback, and collaborate effectively. A master’s More ❯

NumPy, scikit-learn, etc.). Comfort working with large and complex datasets, including data wrangling and exploratory analysis. Experience (or strong interest) in GPU-powered model development (e.g. using PyTorch, TensorFlow, JAX, or similar). Demonstrated ability to work independently on real-world projects. Strong communicator, with the ability to share ideas, take feedback, and collaborate effectively. A master’s More ❯

across departments and navigate large organisations. Strong project management and organizational skills. Proficiency in programming languages such as Python, Java and Scala, and experience with ML frameworks like TensorFlow, PyTorch, and scikit-learn. Experience with cloud platforms (e.g., AWS), big data technologies (e.g., Spark) as well as other technologies used to deploy models to production (e.g., Kubernetes, GHA, Airflow, Docker More ❯

conferences (e.g., NeurIPS, ICML, ICLR, ACL,EMNLP, NAACL, ICLR) with specific focus on agent systems, tool use, or multi-agentcoordination Familiarity with one or more deep learning frameworks (e.g. pytorch, jax, tensorflow, ) Excellent communication skills to report and present research findings anddevelopments clearly, both orally and in writing. Curious and innovative disposition capable of devising novel, well-founded algorithmicsolutions to More ❯

essential skills and qualifications: Hold an active Security clearance (Ideally Top Secret with SCI Poly) Strong programming skills in Python, with experience in machine learning libraries such as TensorFlow, PyTorch, or scikit-learn Proficient in data manipulation, feature engineering, and model evaluation techniques Solid understanding of different machine learning algorithms and their applications Experience deploying machine learning models into production More ❯

machine learning engineers, AI researchers, and data scientists, driving end-to-end AI solution delivery. Designing and implementing AI architectures across cloud and on-prem environments, leveraging tools like PyTorch, TensorFlow, and Hugging Face. Spearheading the development of production ready AI models, from foundational LLMs to custom built cognitive agents, solving real world business challenges. Establishing scalable ML/AI More ❯

and implementing solutions defined by project leads. Desirable Experience Strong Python expertise. Experience with GNU/Linux environments. Familiarity with key data science and ML frameworks (e.g., scikit-learn, PyTorch, TensorFlow, XGBoost, Hugging Face). Experience in natural language processing, tabular data analysis, or computer vision. SQL proficiency. Exposure to containerisation (Docker, Kubernetes) and cloud-native architectures. Experience with CI More ❯

and implementing solutions defined by project leads. Desirable Experience Strong Python expertise. Experience with GNU/Linux environments. Familiarity with key data science and ML frameworks (e.g., scikit-learn, PyTorch, TensorFlow, XGBoost, Hugging Face). Experience in natural language processing, tabular data analysis, or computer vision. SQL proficiency. Exposure to containerisation (Docker, Kubernetes) and cloud-native architectures. Experience with CI More ❯

and implementing solutions defined by project leads. Desirable Experience Strong Python expertise. Experience with GNU/Linux environments. Familiarity with key data science and ML frameworks (e.g., scikit-learn, PyTorch, TensorFlow, XGBoost, Hugging Face). Experience in natural language processing, tabular data analysis, or computer vision. SQL proficiency. Exposure to containerisation (Docker, Kubernetes) and cloud-native architectures. Experience with CI More ❯

flexibly on projects that push the boundaries of technology. Key Skills - Proficiency in Python and/or R for developing machine learning models. - Experience with frameworks such as TensorFlow, PyTorch, or Scikit-learn. - Strong understanding of data preprocessing, feature engineering, and model evaluation techniques. - Familiarity with cloud platforms like AWS, GCP, or Azure for deploying ML solutions. - Knowledge of version More ❯

Data Science with reasonable industry experience, or an MS with significant industry or research experience in the field • Extensive experience with machine learning and deep learning toolkits (e.g.: TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas) • Ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals • Experience with big More ❯

or a related field. 5+ years' experience in data science, with proven success delivering end-to-end projects. Proficiency in Python, R, SQL, and machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). Strong skills in data storytelling, problem-solving, and working with both structured and unstructured data. Experience with APIs, cloud platforms (especially AWS), and MLOps practices is a More ❯

data science or software engineering. An excellent command of the basic libraries for data science (e.g. NumPy, Pandas, Scikit-Learn) and familiarity with a deep-learning framework (e.g. TensorFlow, PyTorch, Caffe) A high level of mathematical competence and proficiency in statistics A solid grasp of essentially all of the standard data science techniques, for example, supervised/unsupervised machine learning More ❯

or a relevant field or MSc in CS, ML, Math, Statistics, Engineering, or related fields. and 2+ years of relevant work experience Experience with deep learning frameworks such as PyTorch Proficiency in software engineering An understanding of Computer Science fundamentals such as data structures and algorithms and a data oriented approach to problem-solving Excellent communication skills and the ability More ❯