26 to 50 of 300 Remote PyTorch Jobs

experience in machine learning, data science, or software development. Proficiency in Python, C#, and other relevant programming languages. Experience with ML frameworks like TensorFlow, PyTorch, and Scikit-learn. Hands-on experience with Microsoft Azure AI services. Knowledge of MLOps best practices. Experience with Azure data and analytics services such as More ❯

to explain complex ideas simply, and work well in cross-functional teams Tech You'll Work With ML & Data Science Python (primary language) TensorFlow, PyTorch, or Keras NumPy, pandas Data pipelines (Azure Data Factory, Airflow, etc.) Applied ML: NLP, CV, transformers, GANs, time series, etc. Engineering & Cloud Azure (or similar 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 ❯

Python, R, and SQL, and data analysis libraries (e.g., Pandas, NumPy, SciPy, Tidyverse). Strong knowledge of machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn, NLTK). Experience with NLP techniques, such as named entity recognition (NER), topic modeling, semantic similarity, and knowledge graph construction. Demonstrated ability to More ❯

science. Strong understanding of AI/ML algorithms and techniques, including LLMs, GenAI, and automated AI systems. Experience with machine learning frameworks (e.g., TensorFlow, PyTorch) and data science libraries (e.g., NumPy, pandas, scikit-learn). Proficiency in Python, R, or other relevant programming languages. Proficiency in working with large datasets More ❯

science. Strong understanding of AI/ML algorithms and techniques, including LLMs, GenAI, and automated AI systems. Experience with machine learning frameworks (e.g., TensorFlow, PyTorch) and data science libraries (e.g., NumPy, pandas, scikit-learn). Proficiency in Python, R, or other relevant programming languages. Proficiency in working with large datasets More ❯

science. Strong understanding of AI/ML algorithms and techniques, including LLMs, GenAI, and automated AI systems. Experience with machine learning frameworks (e.g., TensorFlow, PyTorch) and data science libraries (e.g., NumPy, pandas, scikit-learn). Proficiency in Python, R, or other relevant programming languages. Proficiency in working with large datasets More ❯

two different programming languages (e.g., Python, R, C/C++), including experience with reinforcement learning libraries in Python Experience using deep learning packages (TensorFlow, PyTorch, JAX) Experience cleaning data, prototyping, and fine-tuning state of the art deep learning models Experience with statistics, machine learning, and reinforcement learning Experience with More ❯

on-premises deployments. Required Qualifications: Strong experience in AI/ML development focusing on LLMs and biomedical NLP. Proficiency in deep learning frameworks (TensorFlow, PyTorch). Experience with MLOps tools and cloud environments (AWS, Azure, GCP). Expertise in model inference optimization techniques. Understanding of biomedical ontologies and healthcare data More ❯

record delivering ML/AI solutions in complex, real-world environments Strong Python skills and experience with key ML libraries (e.g., scikit-learn, XGBoost, PyTorch) Exposure to Generative AI technologies (e.g., LLMs, embeddings, RAG systems) Excellent communication skills and ability to engage senior stakeholders Nice to Have: Experience in consulting More ❯

record delivering ML/AI solutions in complex, real-world environments Strong Python skills and experience with key ML libraries (e.g., scikit-learn, XGBoost, PyTorch) Exposure to Generative AI technologies (e.g., LLMs, embeddings, RAG systems) Excellent communication skills and ability to engage senior stakeholders Nice to Have: Experience in consulting More ❯

record delivering ML/AI solutions in complex, real-world environments Strong Python skills and experience with key ML libraries (e.g., scikit-learn, XGBoost, PyTorch) Exposure to Generative AI technologies (e.g., LLMs, embeddings, RAG systems) Excellent communication skills and ability to engage senior stakeholders Nice to Have: Experience in consulting More ❯

Machine Learning, Cloud, DevOps & Software Good theoretical understanding of machine learning, neural networks, and other computer vision topics Hands-on experience with Python and PyTorch Hands-on experience with MLOps frameworks and platforms (We use ClearML!) Experience with additional programming languages and frameworks is a plus Experience working with cloud More ❯

Aimpoint Digital is a premier analytics consulting firm with a mission to drive business value for clients through expertise in data strategy, data analytics, decision sciences, and data engineering and infrastructure. This position is within our decision sciences practice which More ❯

with emerging AI trends and technologies Skills Needed 3+ years of experience in AI and machine learning development Strong knowledge of AI frameworks (TensorFlow, PyTorch, Keras) Experience with NLP and computer vision models Strong understanding of machine learning algorithms and statistical modeling Experience with cloud-based AI platforms (AWS SageMaker More ❯

active TS, SCI eligible Strong skills in Python, especially for data manipulation (e.g., Pandas, NumPy) and machine learning, natural language processing (e.g., Scikit-Learn, PyTorch, Spa Cy, NLTK) Fluency with data extraction, custom translation development, and loading including data prep and labeling to enable data analytics. Familiarity with various log More ❯

a related field. Proficiency in programming languages like Python, R, or SQL for data manipulation. Experience building machine learning models using libraries like TensorFlow, PyTorch, or scikit-learn. Familiarity with cloud platforms like AWS, GCP, or Azure. Strong written and spoken English skills. Bonus Experience: Experience with big data tools More ❯

experience with LLMs such as OpenAI GPT, Anthropic Claude, Mistral, Cohere, or similar. Proficiency in Python and AI/ML frameworks such as TensorFlow, PyTorch, Hugging Face Transformers, or LangChain. Experience in fine-tuning, model evaluation, and prompt engineering. Strong understanding of NLP techniques including text classification, summarization, sentiment analysis More ❯

complex technical concepts effectively to non-technical audiences Experience with cloud platforms (Azure, AWS, GCP) is desirable Experience with Machine Learning libraries (scikit-learn, PyTorch) and statistical techniques is desirable Knowledge of the electricity market is desirable Employee Benefits We offer a comprehensive benefits package, including: Performance bonus up to More ❯

complex technical concepts effectively to non-technical audiences Experience with cloud platforms (Azure, AWS, GCP) is desirable Experience with Machine Learning libraries (scikit-learn, PyTorch) and statistical techniques is desirable Knowledge of the electricity market is desirable Employee Benefits We offer a comprehensive benefits package, including: Performance bonus up to More ❯

Mistral. Model performance and optimization: Fine-tuning and optimizing LLMs for quality, latency, sustainability, and cost. Programming and NLP tools: Advanced Python, frameworks like PyTorch, TensorFlow, Hugging Face, LangChain. MLOps and deployment: Docker, Kubernetes, Azure ML Studio, MLFlow. Cloud and AI infrastructure: Experience with Azure Cloud for scalable deployment. Databases More ❯

techniques. Hands-on experience with NLP is a significant plus. Proficiency in cloud environments, particularly Azure. Familiarity with popular machine learning frameworks such as PyTorch or TensorFlow. Experience deploying AI/ML models into production and working with LLMs in a real-world setting. Knowledge of best practices in DevOps More ❯

An excellent command of the basic libraries for data science (e.g. NumPy, Pandas, Scikit-Learn) and familiarity with a deep-learning framework (e.g. TensorFlow, PyTorch, Caffe) A high level of mathematical competence and proficiency in statistics A solid grasp of essentially all of the standard data science techniques, for example More ❯

projects and mentoring junior team members. The ideal candidate will have strong expertise in Python, with hands-on experience using libraries such as TensorFlow, PyTorch, and Hugging Face Transformers, with a solid understanding of LLM architectures. You will also need to be well-versed in various machine learning techniques, including More ❯

to-end solutions Implement testing, monitoring, and performance optimisation of ML systems Contribute to architectural discussions and promote engineering best practices Technical Environment: Python, PyTorch or TensorFlow AWS (including SageMaker, S3, Lambda) or Azure ML Docker, Kubernetes, Airflow CI/CD tools (e.g. GitHub Actions, Jenkins) MLflow or similar frameworks More ❯