26 to 50 of 647 PyTorch Jobs

and AI Required Skills & Qualifications: Strong experience in C#, .NET Framework, .NET Core/6/7, ASP.NET Experience with AI/ML frameworks such as: ML.NET TensorFlow/PyTorch (for integration with .NET) Azure Cognitive Services/OpenAI/AI APIs Knowledge of RESTful APIs , microservices, and cloud platforms (Azure, AWS, or GCP) Familiarity with SQL and NoSQL databases More ❯

and AI Required Skills & Qualifications: Strong experience in C#, .NET Framework, .NET Core/6/7, ASP.NET Experience with AI/ML frameworks such as: ML.NET TensorFlow/PyTorch (for integration with .NET) Azure Cognitive Services/OpenAI/AI APIs Knowledge of RESTful APIs , microservices, and cloud platforms (Azure, AWS, or GCP) Familiarity with SQL and NoSQL databases More ❯

experience in AI engineering or a related role. Technical Skills: Proficiency in programming languages such as Python, R, or Java. Experience with AI frameworks and libraries such as TensorFlow, PyTorch, or scikit-learn. Machine Learning Knowledge: Strong understanding of machine learning algorithms, neural networks, and deep learning techniques. Analytical Skills: Excellent analytical and problem-solving skills, with the ability to More ❯

or a related technical field Strong proficiency in Python is a must 2 - 4 years of experience in machine learning or backend software development Experience using frameworks like TensorFlow, PyTorch, or Scikit-learn Solid understanding of ML workflows: data cleaning, model development, tuning, evaluation Familiar with model deployment, API development, or real-world ML integration Experience with tools like Google More ❯

products. For this role, we're looking for skills across the following: Strong Python proficiency with hands-on experience in AI/ML frameworks including RAG, LangChain, TensorFlow, and PyTorch Practical experience with Generative AI and exposure to leading LLM platforms (Anthropic, Meta, Amazon , OpenAI) Proficiency with essential data science libraries including Pandas, NumPy, scikit-learn, Plotly/Matplotlib, and More ❯

ML models into products. Contribute to improving infrastructure, tooling, and best practices for ML development and deployment. Skills & Experience Essential: Strong programming skills in Python (and frameworks such as PyTorch, TensorFlow, or Scikit-learn). Proven experience in developing and deploying machine learning models in production. Solid understanding of data structures, algorithms, and software engineering principles. Experience with ML pipelines More ❯

ML models into products. Contribute to improving infrastructure, tooling, and best practices for ML development and deployment. Skills & Experience Essential: Strong programming skills in Python (and frameworks such as PyTorch, TensorFlow, or Scikit-learn). Proven experience in developing and deploying machine learning models in production. Solid understanding of data structures, algorithms, and software engineering principles. Experience with ML pipelines More ❯

ML models into products. Contribute to improving infrastructure, tooling, and best practices for ML development and deployment. Skills & Experience Essential: Strong programming skills in Python (and frameworks such as PyTorch, TensorFlow, or Scikit-learn). Proven experience in developing and deploying machine learning models in production. Solid understanding of data structures, algorithms, and software engineering principles. Experience with ML pipelines More ❯

ML models into products. Contribute to improving infrastructure, tooling, and best practices for ML development and deployment. Skills & Experience Essential: Strong programming skills in Python (and frameworks such as PyTorch, TensorFlow, or Scikit-learn). Proven experience in developing and deploying machine learning models in production. Solid understanding of data structures, algorithms, and software engineering principles. Experience with ML pipelines More ❯

ML models into products. Contribute to improving infrastructure, tooling, and best practices for ML development and deployment. Skills & Experience Essential: Strong programming skills in Python (and frameworks such as PyTorch, TensorFlow, or Scikit-learn). Proven experience in developing and deploying machine learning models in production. Solid understanding of data structures, algorithms, and software engineering principles. Experience with ML pipelines More ❯

foundation in statistics, machine learning, and experimental design Proven ability to communicate technical solutions clearly to non-technical stakeholders Technical skills (a big plus): Knowledge of deep learning frameworks (PyTorch, TensorFlow), transformers, or LLMs Familiarity with MLOps tools (MLflow, SageMaker, Airflow, etc.) Experience with streaming data (Kafka, Kinesis) and distributed computing (Spark, Dask) Skills in data visualization apps (Streamlit, Dash More ❯

associated concepts, such as transformer architecture and retrieval augmented generation. Strong programming ability with demonstrated experience in Python and one or more associated machine learning frameworks, such as TensorFlow, PyTorch, or SKLearn. Knowledge of and experience working with open-source AI models. Demonstrated ability to perform the essential duties of the position with or without accommodation. Authorization to work in More ❯

scalable AI systems) 1+ years 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 of software systems within AI More ❯

scalable AI systems) 1+ years 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 of software systems within AI More ❯

scalable AI systems) 1+ years 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 of software systems within AI More ❯

scalable AI systems) 1+ years 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 of software systems within AI More ❯

scalable AI systems) 1+ years 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 of software systems within AI More ❯

scalable AI systems) 1+ years 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 of software systems within AI More ❯

and understands the full ML lifecycle. Can design for long-term scalability, reliability, and resilience. Has strong programming skills with Python – essential. Has hands-on experience with ML frameworks (PyTorch, TensorFlow, Scikit-learn). Is experienced with cloud platforms (ideally GCP: BigQuery, Vertex AI, Dataflow), but AWS/SageMaker or similar is also valued. Has operated in distributed computing environments More ❯

and understands the full ML lifecycle. Can design for long-term scalability, reliability, and resilience. Has strong programming skills with Python – essential. Has hands-on experience with ML frameworks (PyTorch, TensorFlow, Scikit-learn). Is experienced with cloud platforms (ideally GCP: BigQuery, Vertex AI, Dataflow), but AWS/SageMaker or similar is also valued. Has operated in distributed computing environments More ❯

and understands the full ML lifecycle. Can design for long-term scalability, reliability, and resilience. Has strong programming skills with Python – essential. Has hands-on experience with ML frameworks (PyTorch, TensorFlow, Scikit-learn). Is experienced with cloud platforms (ideally GCP: BigQuery, Vertex AI, Dataflow), but AWS/SageMaker or similar is also valued. Has operated in distributed computing environments More ❯

Programming: Solid experience in Python and SQL. Experience with R is a nice-to-have. ML and AI: Practical experience using ML modeling libraries like Scikit-Learn, Keras, Tensorflow, PyTorch and similar Generative AI: Some hands-on experience with LLMs for prompt engineering or agents is preferred Cloud Expertise: Building, deploying and monitoring models on cloud like Azure, AWS or More ❯

Data Scientist or in a similar role. Strong programming skills in Python, R, or SQL . Hands-on experience with machine learning libraries such as scikit-learn, TensorFlow, or PyTorch . Solid understanding of statistics, predictive modeling, and data mining techniques. Experience with data visualization tools such as Tableau, Power BI, or matplotlib/seaborn . Familiarity with cloud platforms More ❯

a consistent track record of shipping models to production and supporting them post-deployment. Strong Python programming skills, including object-oriented design and proficiency with key ML libraries (e.g., PyTorch, TensorFlow, Scikit-Learn). Solid understanding of probability and statistical modeling to support robust model development and interpretation. Experience with cloud platforms (especially Azure and/or AWS) and modern More ❯

years of experience building production-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 for ML models 2+ years of people More ❯