1 to 25 of 243 PyTorch Jobs

Technical Skills Working production experience in Python, and at least two of: C#, C/C++, Java, Go Machine Learning & AI stacks, including: TensorFlow, PyTorch, Scikit-learn, Transformers, LLMs. Customization: fine-tuning, RAG, other related methods. MLOps & DevOps: MLflow, TFX, Kubeflow, Docker, Kubernetes, CI/CD terminology and pipelines ...

GenAI Ecosystem Lead the design and deployment of scalable AI solutions across Python, .NET, and cloud-native platforms Drive adoption of advanced frameworks (PyTorch, TensorFlow, Hugging Face, LangChain) Oversee integration of LLMs (OpenAI, Anthropic, Gemini, Mistral) via enterprise platforms (Azure OpenAI, Vertex AI) Implement RAG architectures and manage vector databases ...

initiatives Required Skills Strong commercial experience in Data Science/Machine Learning Advanced Python skills with ML frameworks such as Scikit-learn, TensorFlow, or PyTorch Experience with LLMs, Generative AI, RAG, or Agentic AI solutions Strong SQL and data manipulation experience Experience working with cloud platforms (AWS, Azure ...

GenAI Ecosystem Lead the design and deployment of scalable AI solutions across Python, .NET, and cloud-native platforms Drive adoption of advanced frameworks (PyTorch, TensorFlow, Hugging Face, LangChain) Oversee integration of LLMs (OpenAI, Anthropic, Gemini, Mistral) via enterprise platforms (Azure OpenAI, Vertex AI) Implement RAG architectures and manage vector databases ...

models, or LLM-based analytics. Strong proficiency in Python (preferred) and/or JavaScript/TypeScript. Hands-on experience with AI frameworks (e.g. TensorFlow, PyTorch and/or LangChain) and LLM APIs (e.g. Azure OpenAI, OpenAI API, Anthropic and/or AWS Bedrock). Experience with Microsoft Bot Framework, Dialogflow ...

Stay up to date with the latest advancements in machine learning and AI technologies Required Skills & Experience Strong programming skills in Python (e.g., TensorFlow, PyTorch, Scikit-learn) Experience deploying ML models using cloud platforms (AWS, Azure, or GCP) Solid understanding of machine learning algorithms, data structures, and software engineering principles ...

into domain-specific use cases Retrieval-Augmented Generation (RAG) fundamentals and context engineering Hands-on or strong exposure to Python and common AI libraries (PyTorch, TensorFlow). Familiarity with: LLMs (OpenAI, Anthropic, Hugging Face, LLaMA models) Vector databases (Pinecone, Weaviate, FAISS , Qudrant) Agentic AI frameworks (exposure to LangGraph, AutoGen, CrewAI ...

Node.js, or Java, Go, with strong coding and software engineering practices. Expertise with AI/ML libraries and frameworks such as LangChain, OpenAI APIs, PyTorch, TensorFlow, commercial or open source LLMs. Hands-on experience with LLMs, prompt engineering, and natural language processing (NLP). Knowledge of agent orchestration platforms ...

pipelines and manage model deployment using Kubernetes/OpenShift and MLOps principles. Technical Requirements Core Programming: Expert-level Python (Pandas, NumPy, scikit-learn, PyTorch/TensorFlow, FastAPI, LangChain, LlamaIndex). Generative AI: Deep experience with LLMs (Gemini, OpenAI, Claude, Llama) and evaluating model safety/performance via Guardrails. Data Science ...

through metrics like Character Error Rate (CER) and Word Error Rate (WER) is also crucial. Strong proficiency in Python and ML frameworks (e.g., TensorFlow, PyTorch). Understanding of ML architectures, hyperparameter tuning, and performance optimisation. Experience with MLOps tools and CI/CD pipelines. Familiarity with data engineering concepts ...

data workflows for maximum scalability and cost-efficiency. Insurance Domain experience is added advantage. Your Technical Toolkit AI/ML: Expert proficiency in Python, PyTorch/TensorFlow, and GenAI frameworks like LangChain, LlamaIndex, or CrewAI. Data Architecture: Hands-on experience with Vector Databases (e.g., Pinecone, Milvus, Weaviate) and SQL/ ...

data workflows for maximum scalability and cost-efficiency. Insurance Domain experience is added advantage. Your Technical Toolkit AI/ML: Expert proficiency in Python , PyTorch/TensorFlow, and GenAI frameworks like LangChain, LlamaIndex, or CrewAI . Data Architecture: Hands-on experience with Vector Databases (e.g., Pinecone, Milvus, Weaviate ...

data workflows for maximum scalability and cost-efficiency. Insurance Domain experience is added advantage. Your Technical Toolkit AI/ML: Expert proficiency in Python , PyTorch/TensorFlow, and GenAI frameworks like LangChain, LlamaIndex, or CrewAI . Data Architecture: Hands-on experience with Vector Databases (e.g., Pinecone, Milvus, Weaviate ...

data workflows for maximum scalability and cost-efficiency. Insurance Domain experience is added advantage. Your Technical Toolkit AI/ML: Expert proficiency in Python , PyTorch/TensorFlow, and GenAI frameworks like LangChain, LlamaIndex, or CrewAI . Data Architecture: Hands-on experience with Vector Databases (e.g., Pinecone, Milvus, Weaviate ...

consulting incl software development with a strong track record of delivering business value Proficiency in Python and ML/DL frameworks (e.g., scikit-learn, PyTorch, TensorFlow) Experience with AI/ML tools (e.g., Jupyter, MLflow, Vertex AI, Azure ML, Amazon SageMaker Experience of creating delivery client-facing proof of concepts ...

with emerging machine learning technologies and best practices Skills and Experience • Strong programming skills in Python • Experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn • Experience working with SQL and large datasets • Familiarity with data pipelines, feature engineering, and model optimisation • Understanding of MLOps practices, model deployment ...

. Published research, patents, or conference presentations in AI or data science related to finance. Technical Skills Programming: Python (pandas, scikit‐learn, TensorFlow/PyTorch), R, SQL, notebooks, Git. Machine Learning: regression, classification, clustering, tree‐based models, neural networks; MLOps, model deployment, automated testing. Data Platforms: relational databases, NoSQL, time ...

enthusiastic, and naturally able to teach diverse stakeholders about AI topics. Comfort with Python and familiarity with common AI/ML libraries (scikit-learn, PyTorch, HuggingFace, OpenAI API). Bonus Points Experience with data engineering tools (SQL, pandas, dbt, Airflow). Exposure to LLMs or generative AI in a practical ...

clinical workflows experience strongly preferred; oncology a plus. Technical Must Haves Expert level Python + strong software engineering practices. Deep learning experience with PyTorch or TensorFlow (LLMs and/or CV). Data engineering: PySpark, SQL, Postgres, data modeling, query tuning. Cloud data platforms (Databricks, S3/Snowflake/Azure ...

clinical workflows experience strongly preferred; oncology a plus. Technical Must Haves Expert level Python + strong software engineering practices. Deep learning experience with PyTorch or TensorFlow (LLMs and/or CV). Data engineering: PySpark, SQL, Postgres, data modeling, query tuning. Cloud data platforms (Databricks, S3/Snowflake/Azure ...

Experience Essential BSc in Machine Learning, Data Science, Computer Science, Mathematics or related field. Experience coding in Python and associated ML packages (HuggingFace, TensorFlow, PyTorch). Have experience of delivering ML solutions to stakeholders. Demonstrate good understanding of AI/ML algorithms for different data types and tasks including Generative ...

Azure, or Google Cloud Platform 4+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 3+ years of experience developing performant, resilient, and maintainable code 3+ years of experience with data gathering and preparation for ML models 3+ ...

Azure, or Google Cloud Platform 4+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 3+ years of experience developing performant, resilient, and maintainable code 3+ years of experience with data gathering and preparation for ML models 3+ ...

Azure, or Google Cloud Platform 4+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 3+ years of experience developing performant, resilient, and maintainable code 3+ years of experience with data gathering and preparation for ML models 3+ ...

ready data pipelines that feed ML models 3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 2+ years of experience developing performant, resilient, and maintainable code 2+ years of experience with data gathering and preparation ...