26 to 50 of 653 Permanent PyTorch Jobs

for building more effective autonomous agents for complex property management workflows and decision-making processes Hands-on experience with AI/ML frameworks (TensorFlow, PyTorch), LLM orchestration tools (LangChain, LangGraph), MLOps practices and tooling (such as MLflow, Kubeflow, or similar), vector databases, and cloud platforms (AWS, Azure, GCP) with their More ❯

and fine-tuning foundation models. Experience working with LLM models from OpenAI, Mistral, Anthropic etc. Expertise in AI/ML frameworks such as TensorFlow, PyTorch, Keras, LangChain, and Hugging Face Transformers a big plus. Skilled in Python and Java, with a focus on writing efficient and scalable code for AI More ❯

Requirements: Bachelor’s, Master’s, or PhD in Computer Science, Data Science, Bioinformatics, or related field. Proficiency in Python and ML frameworks (e.g., TensorFlow, PyTorch). Experience with bioinformatics tools (e.g., Biopython, RDKit). Strong knowledge of statistical models, deep learning, and data preprocessing. Familiarity with cloud platforms (AWS, GCP More ❯

to 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 ❯

to 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 ❯

years of hands-on experience in AI and machine learning. Technical Expertise: Strong proficiency in Python. Expertise in machine learning frameworks such as TensorFlow, PyTorch, Keras, or similar. Machine Learning: Solid understanding of supervised and unsupervised learning, deep learning (CNNs, RNNs, GANs), and reinforcement learning. Data Handling: Proficient in data More ❯

advanced AI leaders. Strong programming skills in languages such as Python, Java, or C++. Experience with AI and machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn. What You'll Bring Preferred qualifications: Experience with cloud platforms such as AWS, Azure, or Google Cloud. Familiarity with data visualization tools More ❯

learning, probabilistic modeling, and/or NLP. Proficiency in programming languages such as Python, R, or Julia, with experience using ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). Familiarity with biological datasets such as genomic, transcriptomic, proteomic, or imaging data. Experience working with large-scale datasets and cloud computing platforms More ❯

will bring: Essential: 5+ years of experience in data science, machine learning, or AI innovation. Strong coding skills in Python (e.g., Pandas, NumPy, TensorFlow, PyTorch) and SQL. Proven experience deploying ML models in production environments. 3+ years in a leadership or mentorship role within AI or data teams. Clear communicator More ❯

DevOps, or ML Engineering roles Proven expertise deploying and scaling Generative AI models (GPT, Stable Diffusion, BERT) Proficiency with Python and ML frameworks (TensorFlow, PyTorch, Hugging Face) Strong cloud platform experience (AWS, GCP, Azure) and managed AI/ML services Practical experience with Docker, Kubernetes, and container orchestration Databricks expertise More ❯

DevOps, or ML Engineering roles Proven expertise deploying and scaling Generative AI models (GPT, Stable Diffusion, BERT) Proficiency with Python and ML frameworks (TensorFlow, PyTorch, Hugging Face) Strong cloud platform experience (AWS, GCP, Azure) and managed AI/ML services Practical experience with Docker, Kubernetes, and container orchestration Databricks expertise More ❯

Azure). Stay up-to-date with the latest research and advancements in AI, Image processing, and Computer Vision. Familiarity with deep learning frameworks (PyTorch, TensorFlow) including OpenCV. Strong communication and analytical skills. Ability to work in teams in a diverse, multi-stakeholder environment comprising of Business and Technology teams. More ❯

developing custom solutions using large language models (LLMs) for business use cases. Proficient in Python-based AI/ML development using frameworks like TensorFlow, PyTorch, and Scikit-learn. LLM Orchestration and Development Expertise in building LLM-powered applications using frameworks such as LangChain and LangGraph, including prompt engineering, fine-tuning More ❯

AI and data-driven architecture design. Extensive experience in enterprise architecture frameworks (e.g., TOGAF, Zachman). Expertise in AI/ML technologies (e.g., TensorFlow, PyTorch, Scikit-learn, Keras) and understanding of deep learning and natural language processing (NLP). Strong understanding of big data platforms such as Hadoop, Apache Spark More ❯

engineering or a related degree. Experience in building AI models/platforms including Gen AI. Experience with Python, ML libraries (such as scikit-learn, pytorch, etc), SQL, Spark, pandas and cloud technologies. Experience in designing and running live model tests. Have strong knowledge of the whole model lifecycle from exploring More ❯

developing custom solutions using large language models (LLMs) for business use cases. Proficient in Python-based AI/ML development using frameworks like TensorFlow, PyTorch, and Scikit-learn. LLM Orchestration and Development Expertise in building LLM-powered applications using frameworks such as LangChain and LangGraph, including prompt engineering, fine-tuning More ❯

challenging business problems. We prioritise clean, well-tested code with a culture of documentation and knowledge sharing. Our tech stack includes GCP, Python, GitHub, PyTorch, TensorFlow, Scikit-learn, and XGBoost. With mature infrastructure and dedicated teams for Data Engineering, Analytics, and Platform Engineering, our Data Scientists enjoy high autonomy. We More ❯

CD) automation, rigorous code reviews, documentation as communication. Preferred Qualifications Familiar with data manipulation and experience with Python libraries like Flask, FastAPI, Pandas, PySpark, PyTorch, to name a few. Proficiency in statistics and/or machine learning libraries like NumPy, matplotlib, seaborn, scikit-learn, etc. Experience in building ETL/ More ❯

and how to fine-tune those models e.g. XGBoost, Deep Neural Networks, Transformers, etc. Experience using specialized machine learning libraries e.g. Fastai, Keras, Tensorflow, pytorch, sci-kit learn, etc. Must demonstrate the capacity of reading, understanding and implementing new techniques in the field of machine learning as they emerge. Experience More ❯

/ML practices, including experience with model deployment, monitoring, and lifecycle management. Experience with tools and frameworks for AI/ML such as MLflow, pytorch, tensorflow, or similar frameworks/tools. Strong problem-solving skills with the ability to address complex technical challenges effectively. Excellent verbal and written communication skills More ❯

to fine-tune those models e.g. XGBoost, Deep Neural Networks, Transformers, Markov chains, etc. Experience using specialized machine learning libraries e.g. Fastai, Keras, Tensorflow, pytorch, sci-kit learn, huggingface, etc. Must demonstrate the capacity of reading, understanding and implementing new techniques in the field of machine learning as they emerge. More ❯

to fine-tune those models eg. XGBoost, Deep Neural Networks, Transformers, Markov chains, etc. Experience using specialized machine learning libraries e.g. Fastai, Keras, Tensorflow, pytorch, sci-kit learn, huggingface, etc. Must demonstrate the capacity of reading, understanding and implementing new techniques in the field of machine learning as they emerge. More ❯

of experience developing applications that leverage Generative AI Implementation approaches like LLM Prompt (or Data) Frameworks (LangChain/LlamaIndex/Semantic Kernel), Transformers/PyTorch frameworks, Retrieval-Augmented Generation (RAG), and API Integration via Chaining Agents (e.g. APIChain) 1+ years of experience designing and implementing benchmarks to measure the performance More ❯

of experience developing applications that leverage Generative AI Implementation approaches like LLM Prompt (or Data) Frameworks (LangChain/LlamaIndex/Semantic Kernel), Transformers/PyTorch frameworks, Retrieval-Augmented Generation (RAG), and API Integration via Chaining Agents (e.g. APIChain) 1+ years of experience designing and implementing benchmarks to measure the performance More ❯

and/or Prefect Experience applying supervised and unsupervised machine learning techniques to real-world problems Proficient with machine learning libraries such as TensorFlow, PyTorch, and Scikit-Learn Familiarity with neural network architectures for sequence modeling (LSTM-RNN, Transformers), classification (CNN), and data generation (GANs) Experience with cloud platforms and More ❯