451 to 475 of 1,815 TensorFlow Jobs

MS with industry or research experience. Hands-on experience and solid understanding of machine learning and deep learning methods. Extensive experience with machine learning and deep learning toolkits (e.g., TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas). Scientific thinking and the ability to invent. Ability to design experiments and training frameworks, and evaluate metrics for model performance aligned with business More ❯

Master’s or PhD degree in a quantitative field (e.g., Computer Science, Machine Learning, Statistics, Physics, Mathematics) or equivalent industry experience. Strong background in deep learning frameworks (e.g., PyTorch, TensorFlow, JAX). Experience with distributed computing platforms (AWS, GCP, Azure, or on-prem clusters). Ideal: Kubernetes and Docker experience for scalable, reproducible workflows. Working at Lila Sciences, you More ❯

conduct literature research in unfamiliar fields. Hands-on experience and solid understanding of machine learning and deep learning methods. 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. More ❯

pricing, AI, data science, or algorithm design, with a track record of building and deploying real-time pricing or recommendation systems Deep technical knowledge of machine learning frameworks (e.g., TensorFlow, PyTorch), cloud platforms (AWS, GCP, Azure), and big data tools (e.g., Spark, Hadoop) Experience designing and/or implementing business-critical operational algorithms Clear communication skills; experienced in communicating More ❯

technical audiences Ideally you have: • Experience as a Customer Engineer, Forward Deployed Engineer, Sales Engineer, Solutions Architect, or Technical Product Manager • Familiarity with AI frameworks such as PyTorch or TensorFlow • Contributions to open-source projects, particularly in the space of DevOps or AI Benefits We have local offices in Paris, London, Marseille and Singapore. France Competitive cash salary and More ❯

and monitoring (e.g. Kubeflow) - Expert knowledge of automated artefact deployment using YAML based CI/CD pipelines and Terraform - Working knowledge of one or more ML engineering frameworks (e.g. TensorFlow, PyTorch, Keras, Scikit-Learn) - Working knowledge of object-oriented programming and unit testing in Python - Working knowledge of application and information security principles and practices (e.g. OWASP for Machine More ❯

and monitoring (e.g. Kubeflow) - Expert knowledge of automated artefact deployment using YAML based CI/CD pipelines and Terraform - Working knowledge of one or more ML engineering frameworks (e.g. TensorFlow, PyTorch, Keras, Scikit-Learn) - Working knowledge of object-oriented programming and unit testing in Python - Working knowledge of application and information security principles and practices (e.g. OWASP for Machine More ❯

and monitoring (e.g. Kubeflow) - Expert knowledge of automated artefact deployment using YAML based CI/CD pipelines and Terraform - Working knowledge of one or more ML engineering frameworks (e.g. TensorFlow, PyTorch, Keras, Scikit-Learn) - Working knowledge of object-oriented programming and unit testing in Python - Working knowledge of application and information security principles and practices (e.g. OWASP for Machine More ❯

software engineering concepts and best practices (e.g., versioning, testing, CI/CD, API design, MLOps) Building machine learning models and pipelines in Python, using common libraries and frameworks (e.g., TensorFlow, MLFlow) Distributed computing frameworks (e.g., Spark, Dask) Cloud platforms (e.g., AWS, Azure, GCP) and HP computing Containerization and orchestration (Docker, Kubernetes) Strong problem-solving skills and the ability to More ❯

and data-driven features into production. Your Profile: Experience in both data engineering and machine learning, with a strong portfolio of relevant projects. Proficiency in Python with libraries like TensorFlow, PyTorch, or Scikit-learn for ML, and Pandas, PySpark, or similar for data processing. Experience designing and orchestrating data pipelines with tools like Apache Airflow, Spark, or Kafka. Strong More ❯

the team. Qualifications Experience managing data pipelines and leading a data science team. Proficiency in Python and experience with LLMs and NLP frameworks (e.g., Hugging Face, Spacy, Pytorch/Tensorflow). Knowledge of Prompt Engineering, RAG techniques, and evaluation methodologies for integrating GenAI with search/retrieval systems. Experience with LangChain/LlamaIndex, vector databases (e.g., FAISS), and fine More ❯

s3). Experience with software development life cycle (sdlc) and agile/iterative methodologies. Experience in using Python and hands on experience building models with deep learning frameworks like Tensorflow, Keras, PyTorch, MXNet. Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your More ❯

Data Science and across Jazz Research and Development. Required Knowledge, Skills And Abilities Strong programming skills in Python, R, or similar languages, with experience in modern ML frameworks (PyTorch, TensorFlow). Demonstrated experience with generative AI technologies, including LLM architectures and frameworks. Experience with natural language processing and generative AI for medical text analysis, generation, and interpretation. Demonstrated ability More ❯

skills. Nice to have Experience deploying LLMs and agent-based systems Our technology stack Python and associated ML/DS libraries (scikit-learn, numpy, pandas, LightGBM, LangChain/LangGraph, TensorFlow, etc ) PySpark AWS cloud infrastructure: EMR, ECS, ECR, Athena, etc. MLOps: Terraform, Docker, Spacelift, Airflow, MLFlow Monitoring: New Relic CI/CD: Jenkins, Github Actions More information: Enjoy fantastic More ❯

AI, Azure Stream Analytics, Cognitive services, Event Hubs, Synapse, and Data Factory). Fluency in common data science coding capabilities such as Python and modelling frameworks such as Pytorch, Tensorflow etc. Excellent communication skills, both verbal and written. Ability to explain technical concepts to a non-technical audience. Ability to influence stakeholders and broaden others thinking in the area More ❯

quality outputs within set timelines. And any experience of these would be a plus: Proficiency in Python programming and experience using AI-specific frameworks or libraries such as PyTorch, TensorFlow, LangChain, LlamaIndex, or similar tools; proficiency in SQL. Hands-on experience or strong theoretical knowledge of AI and GenAI techniques and methodologies. Familiarity with cloud AI platforms such as More ❯

quality outputs within set timelines. And any experience of these would be a plus: Proficiency in Python programming and experience using AI-specific frameworks or libraries such as PyTorch, TensorFlow, LangChain, LlamaIndex, or similar tools; proficiency in SQL. Hands-on experience or strong theoretical knowledge of AI and GenAI techniques and methodologies. Familiarity with cloud AI platforms such as More ❯

quality outputs within set timelines. And any experience of these would be a plus: Proficiency in Python programming and experience using AI-specific frameworks or libraries such as PyTorch, TensorFlow, LangChain, LlamaIndex, or similar tools; proficiency in SQL. Hands-on experience or strong theoretical knowledge of AI and GenAI techniques and methodologies. Familiarity with cloud AI platforms such as More ❯

quality outputs within set timelines. And any experience of these would be a plus: Proficiency in Python programming and experience using AI-specific frameworks or libraries such as PyTorch, TensorFlow, LangChain, LlamaIndex, or similar tools; proficiency in SQL. Hands-on experience or strong theoretical knowledge of AI and GenAI techniques and methodologies. Familiarity with cloud AI platforms such as More ❯

quality outputs within set timelines. And any experience of these would be a plus: Proficiency in Python programming and experience using AI-specific frameworks or libraries such as PyTorch, TensorFlow, LangChain, LlamaIndex, or similar tools; proficiency in SQL. Hands-on experience or strong theoretical knowledge of AI and GenAI techniques and methodologies. Familiarity with cloud AI platforms such as More ❯

Own critical platform components from conception through production deployment Who You Are Expert proficiency in Python, JavaScript, and modern web frameworks Deep experience with AI/ML frameworks (PyTorch, TensorFlow, Transformers, LangChain) Mastery of prompt engineering and fine-tuning Large Language Models Proficient in vector databases (Pinecone, Weaviate, Milvus) and embedding technologies Expert in building RAG (Retrieval-Augmented Generation More ❯

of experience in AI/ML development. • Strong understanding of AI/ML algorithms and techniques, including LLMs, GenAI, and automated AI systems. • Experience with machine learning frameworks (e.g., TensorFlow, PyTorch). • Proficiency in Python, R, or other relevant programming languages. • Experience with data analysis and visualization tools (e.g., Matplotlib, Seaborn, Tableau). • Ability to work independently and lead More ❯

Own critical platform components from conception through production deployment Who You Are Expert proficiency in Python, JavaScript, and modern web frameworks Deep experience with AI/ML frameworks (PyTorch, TensorFlow, Transformers, LangChain) Mastery of prompt engineering and fine-tuning Large Language Models Proficient in vector databases (Pinecone, Weaviate, Milvus) and embedding technologies Expert in building RAG (Retrieval-Augmented Generation More ❯

/non-linear optimization. Experience working with Java and Python, and strong understanding of data structures, algorithms, and software design patterns. Experience with AI and Gen AI frameworks (e.g., TensorFlow or PyTorch). Experience with at least one cloud-based platform (e.g., AWS SageMaker or Azure Machine Learning). Adept at translating business problems into solution statements. Strong communication More ❯

and monitoring (e.g. Kubeflow) Expert knowledge of automated artefact deployment using YAML based CI/CD pipelines and Terraform Working knowledge of one or more ML engineering frameworks (e.g. TensorFlow, PyTorch, Keras, Scikit-Learn) Working knowledge of object-oriented programming and unit testing in Python Working knowledge of application and information security principles and practices (e.g. OWASP for Machine More ❯