301 to 325 of 428 Permanent TensorFlow Jobs

problem-solving skills, a quick learning ability, and enthusiasm for tackling complex challenges. You are proficient in Python, with experience using PySpark and ML libraries such as scikit-learn, TensorFlow, or Keras . You are familiar with big data technologies (e.g., Hadoop, Spark), cloud platforms (AWS, GCP), and can effectively communicate technical concepts to non-technical stakeholders. Accommodation requests More ❯

extending all of this for the Neuron based system is key. Key job responsibilities This role will help lead the efforts building distributed training and inference support into Pytorch, Tensorflow, Jax using XLA and the Neuron compiler and runtime stacks. This role will help tune these models to ensure highest performance and maximize the efficiency of them running on More ❯

equivalent practical experience. 7 years of experience working in AI/ML as a technical sales engineer or in software engineering. Experience in Python and Machine learning frameworks (e.g., TensorFlow, PyTorch). Experience in Generative AI as a user or a developer. Experience delivering technical presentations and leading business value sessions to support client relationship management in this region. More ❯

Learning (policy optimisation, reward modelling, RLHF). Hands-on experience training/fine-tuning generative models (LLMs, diffusion, transformers, GANs). Strong knowledge of deep learning frameworks (PyTorch, JAX, TensorFlow). Proficiency in Python and standard ML libraries. Solid foundations in probability, optimisation, and statistics. Experience working with large-scale distributed training on GPUs/TPUs. If this sounds More ❯

Learning (policy optimisation, reward modelling, RLHF). Hands-on experience training/fine-tuning generative models (LLMs, diffusion, transformers, GANs). Strong knowledge of deep learning frameworks (PyTorch, JAX, TensorFlow). Proficiency in Python and standard ML libraries. Solid foundations in probability, optimisation, and statistics. Experience working with large-scale distributed training on GPUs/TPUs. If this sounds More ❯

Learning (policy optimisation, reward modelling, RLHF). Hands-on experience training/fine-tuning generative models (LLMs, diffusion, transformers, GANs). Strong knowledge of deep learning frameworks (PyTorch, JAX, TensorFlow). Proficiency in Python and standard ML libraries. Solid foundations in probability, optimisation, and statistics. Experience working with large-scale distributed training on GPUs/TPUs. If this sounds More ❯

Learning (policy optimisation, reward modelling, RLHF). Hands-on experience training/fine-tuning generative models (LLMs, diffusion, transformers, GANs). Strong knowledge of deep learning frameworks (PyTorch, JAX, TensorFlow). Proficiency in Python and standard ML libraries. Solid foundations in probability, optimisation, and statistics. Experience working with large-scale distributed training on GPUs/TPUs. If this sounds More ❯

Learning (policy optimisation, reward modelling, RLHF). Hands-on experience training/fine-tuning generative models (LLMs, diffusion, transformers, GANs). Strong knowledge of deep learning frameworks (PyTorch, JAX, TensorFlow). Proficiency in Python and standard ML libraries. Solid foundations in probability, optimisation, and statistics. Experience working with large-scale distributed training on GPUs/TPUs. If this sounds More ❯

/CD tools (e.g., Jenkins, GitHub Actions), and Infrastructure as Code. Experience in software design, architecture, and leading development teams. Familiarity with AI/ML tools and frameworks (e.g., TensorFlow, OpenAI, Azure Cognitive Services, etc. Expertise in various architectural models, including domain-driven design, microservices-architecture, event-driven-architecture, and micro-frontend-architecture. Excellent communication skills and the ability More ❯

the team. You Bring 5+ years of ML/AI engineering experience, including 3+ years deploying generative AI (LLMs, fine-tuning, RAG) in production. Strong technical grounding in Python, TensorFlow/PyTorch, transformer architectures (GPT, Llama, Mistral), vector databases, and prompt engineering frameworks. Proven record of delivering measurable ROI from AI projects. Solid engineering fundamentals: version control, CI/ More ❯

the team. You Bring 5+ years of ML/AI engineering experience, including 3+ years deploying generative AI (LLMs, fine-tuning, RAG) in production. Strong technical grounding in Python, TensorFlow/PyTorch, transformer architectures (GPT, Llama, Mistral), vector databases, and prompt engineering frameworks. Proven record of delivering measurable ROI from AI projects. Solid engineering fundamentals: version control, CI/ More ❯

Engineer with a strong interest and practical experience in applied AI or machine learning. Strong programming skills in Python (or similar languages) with familiarity in AI/ML libraries (TensorFlow, PyTorch, etc.). Experience working with large-scale models (LLM/VLM) and deploying AI-driven solutions into production. Solid understanding of cloud technologies, containerization, and building scalable AI More ❯

field (e.g. Statistics, Mathematics, Physics, Machine Learning) You're confident in Python (production-level) and SQL, and at home with modern ML libraries such as Pandas, scikit-learn, and TensorFlow You have practical experience with MLOps frameworks and deploying models You're skilled at bringing data to life through visualisation, and tools like Tableau feel natural to you You More ❯

solutions Proficiency in Python and SQL and familiarity with good software engineering practices Excellent written and verbal communication Strong experience developing, testing machine learning solutions using frameworks such as TensorFlow, PyTorch or scikit-learn Solid intuitive grasp of fundamental concepts from probability, statistics, linear algebra and calculus Collaborative, humble and enthusiastic attitude Preferred qualifications, capabilities and skills Experience deploying More ❯

desirable in a model. Familiarity with Python and the packages widely used in data science and machine learning. Developers should be familiar with libraries like NumPy, pandas, scikit-learn, TensorFlow, and PyTorch. Familiarity with best practice in Machine Learning workflows and MLOps tools. Fluency in validation and evaluation framework and metrics frameworks for machine learning such as Accuracy, Recall More ❯

desirable in a model. Familiarity with Python and the packages widely used in data science and machine learning. Developers should be familiar with libraries like NumPy, pandas, scikit-learn, TensorFlow, and PyTorch. Familiarity with best practice in Machine Learning workflows and MLOps tools. Fluency in validation and evaluation framework and metrics frameworks for machine learning such as Accuracy, Recall More ❯

desirable in a model. Familiarity with Python and the packages widely used in data science and machine learning. Developers should be familiar with libraries like NumPy, pandas, scikit-learn, TensorFlow, and PyTorch. Familiarity with best practice in Machine Learning workflows and MLOps tools. Fluency in validation and evaluation framework and metrics frameworks for machine learning such as Accuracy, Recall More ❯

desirable in a model. Familiarity with Python and the packages widely used in data science and machine learning. Developers should be familiar with libraries like NumPy, pandas, scikit-learn, TensorFlow, and PyTorch. Familiarity with best practice in Machine Learning workflows and MLOps tools. Fluency in validation and evaluation framework and metrics frameworks for machine learning such as Accuracy, Recall More ❯

desirable in a model. Familiarity with Python and the packages widely used in data science and machine learning. Developers should be familiar with libraries like NumPy, pandas, scikit-learn, TensorFlow, and PyTorch. Familiarity with best practice in Machine Learning workflows and MLOps tools. Fluency in validation and evaluation framework and metrics frameworks for machine learning such as Accuracy, Recall More ❯

regulatory requirements, and operational challenges. Hands-on expertise with cloud platforms (AWS, Azure, Google Cloud) and scalable, secure data infrastructures. Skilled in analytics, problem-solving, and applying machine learning (TensorFlow, PyTorch, Scikit-learn) to business use cases. Excellent communication and stakeholder management, comfortable engaging with C-level executives. Please note that this role does not offer visa sponsorship If More ❯

regulatory requirements, and operational challenges. Hands-on expertise with cloud platforms (AWS, Azure, Google Cloud) and scalable, secure data infrastructures. Skilled in analytics, problem-solving, and applying machine learning (TensorFlow, PyTorch, Scikit-learn) to business use cases. Excellent communication and stakeholder management, comfortable engaging with C-level executives. Please note that this role does not offer visa sponsorship If More ❯

regulatory requirements, and operational challenges. Hands-on expertise with cloud platforms (AWS, Azure, Google Cloud) and scalable, secure data infrastructures. Skilled in analytics, problem-solving, and applying machine learning (TensorFlow, PyTorch, Scikit-learn) to business use cases. Excellent communication and stakeholder management, comfortable engaging with C-level executives. Please note that this role does not offer visa sponsorship If More ❯

regulatory requirements, and operational challenges. Hands-on expertise with cloud platforms (AWS, Azure, Google Cloud) and scalable, secure data infrastructures. Skilled in analytics, problem-solving, and applying machine learning (TensorFlow, PyTorch, Scikit-learn) to business use cases. Excellent communication and stakeholder management, comfortable engaging with C-level executives. Please note that this role does not offer visa sponsorship If More ❯

regulatory requirements, and operational challenges. Hands-on expertise with cloud platforms (AWS, Azure, Google Cloud) and scalable, secure data infrastructures. Skilled in analytics, problem-solving, and applying machine learning (TensorFlow, PyTorch, Scikit-learn) to business use cases. Excellent communication and stakeholder management, comfortable engaging with C-level executives. Please note that this role does not offer visa sponsorship If More ❯

where it counts: Ship intent classifiers, outcome forecasters and recommendation pipelines with scikit-learn/XGBoost/LightGBM . Stack (core) Python (production-grade) LLM tooling: PyTorch, Hugging Face, TensorFlow Fine-tuning: LoRA/QLoRA/full training GCP/Vertex AI: Training, Pipelines, Registry/Deploy Experimentation: SQL, A/B test design, causal thinking Predictive: scikit-learn More ❯