126 to 150 of 3,115 Permanent TensorFlow Jobs

models like GANs, VAEs, transformers, or diffusion models. Proficiency in programming languages such as Python, R, or Julia, and experience with ML frameworks like TensorFlow, PyTorch, or Keras. Strong understanding of deep learning architectures, neural networks, and statistical modeling techniques. Experience with cloud platforms (AWS, Azure, Google Cloud) and More ❯

or R. Experience with SQL and familiarity with database management practices to handle and query large datasets efficiently. Knowledge of machine learning frameworks like TensorFlow or PyTorch and libraries such as scikit-learn. Proficiency in using data analysis and visualization tools to interpret data and present insights effectively. Proven More ❯

of experience in AI development. Strong understanding of machine learning, deep learning, and other AI techniques. Proficiency in Python and relevant AI libraries (e.g., TensorFlow, PyTorch). Experience with data processing and analysis tools (e.g., Pandas, SQL). Experience with cloud platforms such as Amazon Web Services, Azure, or More ❯

attention to detail, and a commitment to quality. Strong communication, leadership, and mentorship abilities. Preferred, but not required: Experience with machine learning frameworks (e.g., TensorFlow, PyTorch). Familiarity with containerization and orchestration technologies (Docker, Kubernetes). Knowledge of front-end technologies (HTML, CSS, JavaScript) is a plus. We offer More ❯

of experience in AI development. Strong understanding of machine learning, deep learning, and other AI techniques. Proficiency in Python and relevant AI libraries (e.g., TensorFlow, PyTorch). Experience with data processing and analysis tools (e.g., Pandas, SQL). Experienced with cloud platforms such as Amazon Web Services, Azure, or More ❯

and Experience Academic Background: Advanced degree in AI, statistics, mathematics, computer science, or a related field. Programming and Frameworks: Hands-on experience with Python, TensorFlow or PyTorch , and NLP libraries such as spaCy and Hugging Face. GenAI Tools: Practical experience with LangChain , Hugging Face Transformers, and embedding models for More ❯

of experience in AI development. Strong understanding of machine learning, deep learning, and other AI techniques. Proficiency in Python and relevant AI libraries (e.g., TensorFlow, PyTorch). Experience with data processing and analysis tools (e.g., Pandas, SQL). Experienced with cloud platforms such as Amazon Web Services, Azure, or More ❯

bidder, documented bids and face to face presentations. Experience of data science platforms (e.g. Databricks, Dataiku, AzureML, SageMaker) and machine learning frameworks (e.g. Keras, Tensorflow, PyTorch, scikit-learn) Cloud platforms - demonstrable experience of building and deploying solutions to Cloud (e.g. AWS, Azure, Google Cloud) including Cloud provisioning tools (e.g. More ❯

and MLOps best practices Hands-on experience with cloud services (Azure ML, AWS SageMaker, GCP Vertex AI) Proficient in Python and common ML libraries (TensorFlow, PyTorch, Scikit-learn) Familiarity with data engineering workflows and tools (Spark, Airflow, Databricks, etc.) Experience with GenAI, LLMs, or NLP is a strong plus More ❯

algorithms, data structures, parsing, optimization, data mining, parallel computing, neural networks, and machine learning. Hands-on experience with Python and deep learning frameworks like TensorFlow, Keras, PyTorch, MXNet. Knowledge of machine learning libraries such as scikit-learn, NumPy, Pandas, MLlib. Strong data engineering, communication, and presentation skills. PhD or More ❯

data science. Strong understanding of AI/ML algorithms and techniques, including LLMs, GenAI, and automated AI systems. Experience with machine learning frameworks (e.g., TensorFlow, PyTorch) and data science libraries (e.g., NumPy, pandas, scikit-learn). Proficiency in Python, R, or other relevant programming languages. Proficiency in working with More ❯

objectives. Stay informed on advancements in AI and integrate the latest technologies into solutions. Key Skills & Experience: Strong programming skills in Python (experience with TensorFlow, PyTorch, or similar frameworks). Expertise in deploying models on cloud platforms (Azure) or containerised environments (Docker, Kubernetes). Proficiency in machine learning algorithms More ❯

computational linguistics are highly desirable, either from a research academic or commercial perspective. Proficiency in Python and ML libraries such as Hugging Face, PyTorch, TensorFlow, and Scikit-learn. Experience deploying AI solutions into production environments using AWS/GCP/Azure. Hands-on with MLOps, CI/CD for More ❯

Develop and optimize AI/ML models with a focus on Generative AI, embeddings, and vector search. Implement deep learning models using frameworks like TensorFlow, PyTorch, or JAX. Collaborate with data scientists to integrate AI models into production systems. Maintain and enhance AI pipelines, ensuring efficiency and scalability. Conduct More ❯

computational linguistics are highly desirable, either from a research academic or commercial perspective. Proficiency in Python and ML libraries such as Hugging Face, PyTorch, TensorFlow, and Scikit-learn. Experience deploying AI solutions into production environments using AWS/GCP/Azure. Hands-on with MLOps, CI/CD for More ❯

re a flat, fast-moving team What You’ll Bring to the team Strong Python skills and experience with ML frameworks like scikit-learn, TensorFlow, PyTorch, Hugging Face Solid grasp of data wrangling , feature engineering , and model evaluation techniques Proficiency in designing and deploying production-ready ML pipelines Familiarity More ❯

of the mathematical foundations of deep learning, including multivariate calculus, linear algebra, and optimization techniques. Proficient in Python and deep learning frameworks such as TensorFlow and PyTorch. Experience with CUDA kernels and GPU profiling is a plus. Excellent communication skills, with the ability to present complex technical ideas to More ❯

of the mathematical foundations of deep learning, including multivariate calculus, linear algebra, and optimization techniques. Proficient in Python and deep learning frameworks such as TensorFlow and PyTorch. Experience with CUDA kernels and GPU profiling is a plus. Excellent communication skills, with the ability to present complex technical ideas to More ❯

NumPy, or Spark. At least 2 years' experience with machine learning, deep learning, or AI systems. Familiarity with key libraries and frameworks such as TensorFlow, Scikit-learn, PyTorch, Transformers, LangChain, BeautifulSoup, and OpenCV. Experience with AI APIs and platforms (e.g., OpenAI, Bedrock, Gemini, Anthropic). Knowledge of cloud infrastructure More ❯

NumPy, or Spark. At least 2 years' experience with machine learning, deep learning, or AI systems. Familiarity with key libraries and frameworks such as TensorFlow, Scikit-learn, PyTorch, Transformers, LangChain, BeautifulSoup, and OpenCV. Experience with AI APIs and platforms (e.g., OpenAI, Bedrock, Gemini, Anthropic). Knowledge of cloud infrastructure More ❯

NumPy, or Spark. At least 2 years' experience with machine learning, deep learning, or AI systems. Familiarity with key libraries and frameworks such as TensorFlow, Scikit-learn, PyTorch, Transformers, LangChain, BeautifulSoup, and OpenCV. Experience with AI APIs and platforms (e.g., OpenAI, Bedrock, Gemini, Anthropic). Knowledge of cloud infrastructure More ❯

NumPy, or Spark. At least 2 years' experience with machine learning, deep learning, or AI systems. Familiarity with key libraries and frameworks such as TensorFlow, Scikit-learn, PyTorch, Transformers, LangChain, BeautifulSoup, and OpenCV. Experience with AI APIs and platforms (e.g., OpenAI, Bedrock, Gemini, Anthropic). Knowledge of cloud infrastructure More ❯

NumPy, or Spark. At least 2 years' experience with machine learning, deep learning, or AI systems. Familiarity with key libraries and frameworks such as TensorFlow, Scikit-learn, PyTorch, Transformers, LangChain, BeautifulSoup, and OpenCV. Experience with AI APIs and platforms (e.g., OpenAI, Bedrock, Gemini, Anthropic). Knowledge of cloud infrastructure More ❯

Strong experience in machine learning, deep learning, and statistical analysis. Expertise in Python, with proficiency in ML and NLP libraries such as Scikit-learn, TensorFlow, Faiss, LangChain, Transformers and PyTorch. Experience with big data tools such as Hadoop, Spark, and Hive. Familiarity with CI/CD and MLOps frameworks More ❯

experience in data science engineering. Proficiency in programming languages such as Python and SQL. Experience with data processing and analysis tools and technologies like TensorFlow, Keras, Scikit-learn. Strong understanding of large language models (LLMs) and machine learning (ML) algorithms and techniques. Familiarity with data visualization tools such as More ❯