101 to 125 of 765 Remote PyTorch Jobs

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 ❯

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 ❯

and practical application. Strong understanding of statistical concepts (e.g., hypothesis testing, sampling, probability distributions). Experience with ML libraries (e.g., scikit-learn; TensorFlow or PyTorch a plus). Proven track record of deploying ML models to production environments. Experience with software development concepts including Version Control (e.g., Git), CI/ More ❯

and delivering complex software projects. Strong programming skills in languages such as Python, Java, or C++. Applying machine learning frameworks and tools (e.g., TensorFlow, PyTorch). Excellent problem-solving and analytical skills. Strong communication and collaboration skills. Ability to work in a fast-paced, dynamic environment. Hands-on involvement with More ❯

And Experience Technical proficiency You write production-grade, scalable Python code, ensuring that your models are robust, maintainable, and optimised for performance Comfortable with PyTorch Knowledge of Transformer-based models Knowledge of Large Language Models (LLMs) Proven experience of having delivered successful Computer Vision or LLM projects into production Strong More ❯

Experience with the analysis or application of data in finance, economics, or related fields is a plus. • Experience with machine learning libraries such as PyTorch, TensorFlow, JAX is a plus. • Experience applying generative AI solutions (via open source tools or through Azure, Amazon Bedrock, Nvidia etc.) is a plus. • Experience 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 ❯

with version control, testing frameworks, and CI/CD pipelines Experience building ML pipelines and deploying models in production Familiarity with ML frameworks (TensorFlow, PyTorch, scikit-learn) Understanding of LLMs, vector databases, and retrieval systems Experience with Model Context Protocol (MCP) integration and server development Full-Stack Capabilities Experience building More ❯

variety of companies & industries Provide hands-on coding sessions and real-world project mentorship using Python and relevant ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch etc) Incorporate cloud-based tools and services (e.g., AWS, GCP, or Azure) into training to simulate modern ML engineering environments (Cloud Training can be provided More ❯

variety of companies & industries Provide hands-on coding sessions and real-world project mentorship using Python and relevant ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch etc) Incorporate cloud-based tools and services (e.g., AWS, GCP, or Azure) into training to simulate modern ML engineering environments (Cloud Training can be provided More ❯

5+ years of experience in AI development Strong understanding of AI principles, machine learning algorithms, and natural language processing Experience with Python, TensorFlow, and PyTorch Excellent communication and teamwork skills Seniority level Seniority level Mid-Senior level Employment type Employment type Full-time Job function Job function Information Technology, Engineering More ❯

asset management, or fintech. Experience with LLMs (e.g., GPT, LLaMA), prompt tuning, and embedding-based retrieval systems. Proficiency in Python and ML libraries (e.g., PyTorch, Hugging Face Transformers, LangChain). Familiarity with cloud platforms (AWS, GCP, or Azure), ML Ops practices, and secure data handling. What We Offer: Up to More ❯

from data exploration and model development to deployment and evaluation. Expert-level proficiency in Python and ML libraries such as Scikit-learn, XGBoost, TensorFlow, PyTorch, and/or Hugging Face. Experience working with large-scale datasets, cloud platforms (AWS/GCP), and ML Ops tools is a plus. Excellent communication More ❯

from data exploration and model development to deployment and evaluation. Expert-level proficiency in Python and ML libraries such as Scikit-learn, XGBoost, TensorFlow, PyTorch, and/or Hugging Face. Experience working with large-scale datasets, cloud platforms (AWS/GCP), and ML Ops tools is a plus. Excellent communication 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 ❯

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 ❯

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 ❯

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 ❯

or statistical models at scale, ideally within product environments or a data-rich business. Tech-savvy : Proficient in Python and modern ML frameworks (e.g., PyTorch, TensorFlow, JAX). Strong command of cloud- AI tooling (e.g., AWS SageMaker, GCP Vertex AI, AzureML/AzureAI, MLflow, Weights & Biases). Well-rounded Engineer More ❯

design, with a track record of building and deploying real-time pricing or recommendation systems Deep technical knowledge of machine learning frameworks (e.g., TensorFlow, PyTorch), cloud platforms (AWS, GCP, Azure), and big data tools (e.g., Spark, Hadoop) Experience designing and/or implementing business-critical operational algorithms Clear communication skills More ❯

or statistical models at scale, ideally within product environments or a data-rich business. Tech-savvy : Proficient in Python and modern ML frameworks (e.g., PyTorch, TensorFlow, JAX). Strong command of cloud-native AI tooling (e.g., AWS SageMaker, GCP Vertex AI, AzureML/AzureAI, MLflow, Weights & Biases). Well-rounded More ❯

Python, C#, JavaScript, Kotlin, Java, Go). Experience with Gen AI tools (e.g., LangGraph, CrewAI, Hugging Face, OpenAI APIs) and ML frameworks such as PyTorch/TensorFlow. Experience in building and optimising systems for performance, scalability, and reliability. Strong understanding of ML fundamentals (training, evaluation, deployment) and LLM-specific challenges More ❯

problem-solving skills is considered as a plus. Technical Skills: Strong programming skills in Python and SQL . Expertise in machine learning frameworks (e.g., PyTorch, TensorFlow, Scikit-learn). Hands-on experience with big data technologies and cloud platforms (AWS preferred; Azure is a plus). Experience deploying ML models More ❯

computer algorithms for mission-critical systems. Proficiency in creating computer programs, including integration with larger software systems. Knowledge of machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and algorithm development tools. Experience with rapid-response R&D, including prototyping and experimental evaluation in dynamic environments. Strong problem-solving skills and More ❯