151 to 175 of 341 Permanent TensorFlow Jobs

Strong Python programming skills: Strong programming skills in Python, including its ecosystem for AI/ML, with experience using libraries such as PyTorch, Hugging Face Transformers, scikit-learn, and TensorFlow to build and implement AI-driven solutions. Product mindset: Ability to think from the user's perspective and design solutions that align with developer needs, improving their experience and More ❯

Strong Python programming skills: Strong programming skills in Python, including its ecosystem for AI/ML, with experience using libraries such as PyTorch, Hugging Face Transformers, scikit-learn, and TensorFlow to build and implement AI-driven solutions. Product mindset: Ability to think from the user's perspective and design solutions that align with developer needs, improving their experience and More ❯

Strong Python programming skills: Strong programming skills in Python, including its ecosystem for AI/ML, with experience using libraries such as PyTorch, Hugging Face Transformers, scikit-learn, and TensorFlow to build and implement AI-driven solutions. Product mindset: Ability to think from the user's perspective and design solutions that align with developer needs, improving their experience and More ❯

Strong Python programming skills: Strong programming skills in Python, including its ecosystem for AI/ML, with experience using libraries such as PyTorch, Hugging Face Transformers, scikit-learn, and TensorFlow to build and implement AI-driven solutions. Product mindset: Ability to think from the user's perspective and design solutions that align with developer needs, improving their experience and More ❯

designing, developing & deploying scalable backend systems. Familiarity with CICD, containerisation, deployment technologies & cloud platforms (Jenkins, Kubernetes, Docker, AWS) or Familiarity with Big Data and Machine Learning technologies (NumPy, PyTorch, TensorFlow, Spark). Excellent communication, collaboration & problem solving skills, ideally with some experience in agile ways of working. Security clearance: You must be able to gain and maintain the highest More ❯

technologies. Collaborate with data and software engineers to deliver integrated solutions. Degree in Computer Science, Engineering, or a related field. Hands-on experience with AI technologies and frameworks (e.g., TensorFlow, PyTorch). Proficiency in programming languages such as Python, Java, or C#. Experience with API design and management, as well as data integration techniques. Strong experience of setup of More ❯

bayesian inference, causal reasoning & inference, transfer & multi-task learning, diffusion models, graph neural networks, active learning; Experience writing production-quality code with modern machine learning frameworks such as PyTorch, TensorFlow, JAX, or similar; Experience with multi-GPU and distributed training at scale; A team player who thrives in collaborative environments and is committed to enabling colleagues to reach their More ❯

development skills in R (including package development, deployment, advanced programming) and Python. Specialist expertise in one or more of the following: Deep learning & analytical frameworks such as pytorch, jax, tensorflow; LLM/LMM applications & agentic AI; bioinformatics & data science. Expertise in systems programming languages (e.g. C/C Rust) is optional but can be beneficial. Strong working knowledge of More ❯

developing embedded or cloud software (python, C/C++, or equivalent) with exposure to Linux or RTOSs. • Experience with data analysis & machine learning, including Python ML & data libraries (e.g. TensorFlow, Keras, PyTorch, NumPy, Pandas, or equivalent). • Experience developing, launching, or maintaining technical products in relevant commercial industries (e.g. industrial, medical, automotive, IoT, or related markets). • Track record More ❯

Java, C++, Python or related language - Experience with neural deep learning methods and machine learning 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. Amazon is an equal opportunity employer and does not discriminate on the basis of protected More ❯

throughput data pipelines and APIs using Go, Python, or similar. Hands-on NLP experience with both pre-built services (e.g., AWS Comprehend) and custom transformer models (Hugging Face, PyTorch, TensorFlow) with a strong grounding in evaluating NLP models using classification and ranking metrics, and experience running A/B or offline benchmarks. Proficient with MLOps and training infrastructure (MLflow More ❯

designing systems in modern cloud environments (e.g. AWS, GCP) Technologies and Tools Python ML and MLOps tooling (e.g. SageMaker, Databricks, TFServing, MLflow) Common ML libraries (e.g. scikit-learn, PyTorch, TensorFlow) Spark and Databricks AWS services (e.g. IAM, S3, Redis, ECS) Shell scripting and related developer tooling CI/CD tools and best practices Streaming and batch data systems (e.g. More ❯

of Design of Experiment (DoE) Solid understanding of unit operations and process-structure-property-performance relationships in foods. Hands-on experience with machine learning, preferably in Python (scikit-learn, TensorFlow, PyTorch, etc.). Experience with hybrid modelling approaches (combining mechanistic and data-driven models) is a plus. Familiarity with digital twin technologies and in silico experimentation concepts. Collaborative mindset More ❯

or Neocloud space. Practical knowledge of AI/ML technologies and their applications, including understanding language models (LLMs), and experience with training and fine-tuning LLMs using frameworks like TensorFlow, PyTorch, or Hugging Face Transformers. Good understanding of programming/scripting: (e.g., Python, Go) for customizing solutions, creating scripts, or automating tasks. Experience with AI relevant infrastructure, including Networking More ❯

re looking for: PhD (or equivalent experience) in a relevant discipline Deep knowledge of machine learning and statistical signal processing Strong Python skills and familiarity with frameworks like PyTorch, TensorFlow, and scikit-learn Experience working with time-series, sensor, or RF data Track record of delivering innovative solutions in complex technical domains Please note: Due to the nature of More ❯

Looking For: 2–4 years of experience in data science, machine learning, or commercial/pricing analytics. Proficiency in Python/R, SQL , and ML libraries (e.g., scikit-learn, TensorFlow, XGBoost). Experience with data visualisation tools (Tableau, Power BI) and statistical methods. Ability to communicate insights clearly to non-technical stakeholders. Passion for applying AI/ML to More ❯

Looking For: 2–4 years of experience in data science, machine learning, or commercial/pricing analytics. Proficiency in Python/R, SQL , and ML libraries (e.g., scikit-learn, TensorFlow, XGBoost). Experience with data visualisation tools (Tableau, Power BI) and statistical methods. Ability to communicate insights clearly to non-technical stakeholders. Passion for applying AI/ML to More ❯

re looking for: PhD (or equivalent experience) in a relevant discipline Deep knowledge of machine learning and statistical signal processing Strong Python skills and familiarity with frameworks like PyTorch, TensorFlow, and scikit-learn Experience working with time-series, sensor, or RF data Track record of delivering innovative solutions in complex technical domains Please note: Due to the nature of More ❯

functional teams to turn real-world problems into working software. 🛠️ What You Bring: Fluency in Python and strong grasp of ML/DL concepts. Experience with frameworks like PyTorch, TensorFlow, Scikit-learn, and HuggingFace Transformers. Comfort designing production-ready AI systems—optimising for speed, cost, and value. Passion for leveraging AI assistants and agentic tools to maximise impact. Bonus More ❯

functional teams to turn real-world problems into working software. 🛠️ What You Bring: Fluency in Python and strong grasp of ML/DL concepts. Experience with frameworks like PyTorch, TensorFlow, Scikit-learn, and HuggingFace Transformers. Comfort designing production-ready AI systems—optimising for speed, cost, and value. Passion for leveraging AI assistants and agentic tools to maximise impact. Bonus More ❯

bring: Experience in Data Science, or a related field Solid skills in Python and SQL for data manipulation and modelling Familiarity with ML libraries like Scikit-learn, PyTorch or TensorFlow Awareness of cloud platforms (Azure, AWS, or GCP) and data governance practices A strong analytical mindset, team spirit, and eagerness to learn from senior peers To speak in absolute More ❯

from pipelining to model deployment , Experience with some of the following tools and technologies (or an eagerness to learn): , Python and its data science ecosystem (e.g., pandas, scikit-learn, TensorFlow/PyTorch) , Statistical methods and machine learning (e.g., A/B testing, model validation) , Data pipelining tools like SQL, dbt, BigQuery, or Spark , A strong communicator with the ability More ❯

place team. Development of VBA/Python tools to expediate the change management review process. Skills Knowledge and Experience Technical Skills: Proficiency in Python, including ML libraries such as TensorFlow, PyTorch, Scikit-learn, Keras, etc. Expert Level in programming such as VBA, Python, JAVA and other coding tools. Familiarity with data processing, feature engineering, and model evaluation techniques. Soft More ❯

custom tools). Strong understanding of computer architecture fundamentals : memory systems, interconnects, queuing theory, Amdahl's and Gustafson's laws. Familiarity with machine learning workloads and frameworks like PyTorch, TensorFlow, or JAX. Ability to interpret RTL/schematics and discuss micro-architectural trade-offs with hardware engineers. Excellent data visualization and communication skills - capable of distilling millions of simulation More ❯

custom tools). Strong understanding of computer architecture fundamentals : memory systems, interconnects, queuing theory, Amdahl's and Gustafson's laws. Familiarity with machine learning workloads and frameworks like PyTorch, TensorFlow, or JAX. Ability to interpret RTL/schematics and discuss micro-architectural trade-offs with hardware engineers. Excellent data visualization and communication skills — capable of distilling millions of simulation More ❯