76 to 100 of 766 Remote PyTorch Jobs

of AI/ML concepts applied to Digital Twin, with extensive hands-on experience in training and fine-tuning models using frameworks such as PyTorch or TensorFlow Proficiency with Generative AI tools such as GPT, DALL-E, Gemini, and a solid understanding of underlying Machine Learning pipelines Exceptional analytical and More ❯

track record of delivering impactful results. Extensive programming skills in Python, with a specialization in distributed computing libraries such as PySpark. Extensive experience with PyTorch (preferred) and/or TensorFlow. Hands-on experience with deploying machine learning models in production using cloud platforms, especially Microsoft Azure ML/Databricks ML More ❯

track record of delivering impactful results. Extensive programming skills in Python, with a specialization in distributed computing libraries such as PySpark. Extensive experience with PyTorch (preferred) and/or TensorFlow. Hands-on experience with deploying machine learning models in production using cloud platforms, especially Microsoft Azure ML/Databricks ML More ❯

track record of delivering impactful results. Extensive programming skills in Python, with a specialization in distributed computing libraries such as PySpark. Extensive experience with PyTorch (preferred) and/or TensorFlow. Hands-on experience with deploying machine learning models in production using cloud platforms, especially Microsoft Azure ML/Databricks ML More ❯

git, and github for collaboration and review). Machine/Deep Learning development skills, including experiment tracking (we use AWS SageMaker, Hugging Face, transformers, PyTorch, scikit-learn, Jupyter, Weights & Biases). An understanding of Language Models, using and training/fine-tuning and a familiarity with industry-standard LM families. More ❯

git, and github for collaboration and review). Machine/Deep Learning development skills, including experiment tracking (we use AWS SageMaker, Hugging Face, transformers, PyTorch, scikit-learn, Jupyter, Weights & Biases). An understanding of Language Models, using and training/fine-tuning and a familiarity with industry-standard LM families. More ❯

git, and github for collaboration and review). Machine/Deep Learning development skills, including experiment tracking (we use AWS SageMaker, Hugging Face, transformers, PyTorch, scikit-learn, Jupyter, Weights & Biases). An understanding of Language Models, using and training/fine-tuning and a familiarity with industry-standard LM families. More ❯

git, and github for collaboration and review). Machine/Deep Learning development skills, including experiment tracking (we use AWS SageMaker, Hugging Face, transformers, PyTorch, scikit-learn, Jupyter, Weights & Biases). An understanding of Language Models, using and training/fine-tuning and a familiarity with industry-standard LM families. More ❯

practices Requirements Proven experience as a Machine Learning Engineer or similar role Strong proficiency in Python and ML libraries such as scikit-learn, TensorFlow, PyTorch, XGBoost, etc. Hands-on experience with data pipelines, model training, evaluation, and deployment Solid understanding of statistics, data structures, and algorithms Familiarity with cloud platforms More ❯

Proven experience in a startup or fast-paced environment. Strong proficiency in Python, SQL, and data science libraries (e.g., scikit-learn, pandas, TensorFlow/PyTorch). Experience working with financial data, risk modelling, or algorithmic trading is a plus. Familiarity with cloud platforms (AWS, GCP, or Azure) and modern data More ❯

Proven experience in a startup or fast-paced environment. Strong proficiency in Python, SQL, and data science libraries (e.g., scikit-learn, pandas, TensorFlow/PyTorch). Experience working with financial data, risk modelling, or algorithmic trading is a plus. Familiarity with cloud platforms (AWS, GCP, or Azure) and modern data More ❯

Proven experience in a startup or fast-paced environment. Strong proficiency in Python, SQL, and data science libraries (e.g., scikit-learn, pandas, TensorFlow/PyTorch). Experience working with financial data, risk modelling, or algorithmic trading is a plus. Familiarity with cloud platforms (AWS, GCP, or Azure) and modern data More ❯

Proven experience in a startup or fast-paced environment. Strong proficiency in Python, SQL, and data science libraries (e.g., scikit-learn, pandas, TensorFlow/PyTorch). Experience working with financial data, risk modelling, or algorithmic trading is a plus. Familiarity with cloud platforms (AWS, GCP, or Azure) and modern data More ❯

to address business challenges (e.g., process automation, predictive analytics, customer service optimisation) Develop and deploy machine learning models using modern tools (e.g., Python, TensorFlow, PyTorch, Scikit-learn) Collaborate with data engineers to prepare and manage training datasets Integrate AI solutions with existing applications and infrastructure Partner with stakeholders to understand More ❯

Essential Skills: 5+ years in AI/ML and data science development. Proficient in Python, R, and relevant ML frameworks/libraries (e.g., TensorFlow, PyTorch, scikit-learn). Strong grasp of LLMs, GenAI, and AI system architectures. Experienced with large-scale datasets and preprocessing pipelines. Skilled in statistical modelling and More ❯

Essential Skills: 5+ years in AI/ML and data science development. Proficient in Python, R, and relevant ML frameworks/libraries (e.g., TensorFlow, PyTorch, scikit-learn). Strong grasp of LLMs, GenAI, and AI system architectures. Experienced with large-scale datasets and preprocessing pipelines. Skilled in statistical modelling and More ❯

Essential Skills: 5+ years in AI/ML and data science development. Proficient in Python, R, and relevant ML frameworks/libraries (e.g., TensorFlow, PyTorch, scikit-learn). Strong grasp of LLMs, GenAI, and AI system architectures. Experienced with large-scale datasets and preprocessing pipelines. Skilled in statistical modelling and More ❯

of experience in data science, machine learning, or a related role Proficiency in programming languages such as Python or R, and libraries like TensorFlow, PyTorch, Scikit-learn, or Pandas Strong understanding of statistical modeling, probability, and optimization techniques Ability to work with messy, real-world datasets and perform feature engineering More ❯

Expertise in NLP libraries such as spaCy, Transformers, Sentence Transformers, LangChain, LangGraph, LlamaIndex, BERTopic. Hands-on experience with machine learning libraries (scikit-learn, TensorFlow, PyTorch). Experience with cloud platforms (AWS, Google Cloud, Azure) and version control systems (Git). Knowledge of SQL and database management. NLP Competencies : Strong understanding More ❯

business solutions and workflows. Proficient with Python and libraries such as NumPy, Pandas, and one or more ML frameworks (e.g., Scikit-learn, TensorFlow, or PyTorch). Understanding of how machine learning models are trained, evaluated, and deployed. Exposure to cloud platforms (especially Azure). Interest in cybersecurity, identity management, or More ❯

in Python and/or another high-level language commonly used in machine learning. Experience with NLP and Machine Learning frameworks and libraries (e.g., PyTorch, HuggingFace, LangChain, spaCy, NLTK, scikit-learn, etc.). Demonstrated understanding of various techniques for extracting structured data from unstructured sources, indicating expertise in information retrieval. More ❯

in Python and/or another high-level language commonly used in machine learning. Experience with NLP and Machine Learning frameworks and libraries (e.g., PyTorch, HuggingFace, LangChain, spaCy, NLTK, scikit-learn, etc.). Demonstrated understanding of various techniques for extracting structured data from unstructured sources, indicating expertise in information retrieval. More ❯

expertise in Machine Learning and Deep Learning, with exposure to Reinforcement Learning as a plus. Proficiency in Python and modern ML libraries (e.g., TensorFlow, PyTorch, JAX, or Keras). Experience with version control systems (GitHub, GitLab) and knowledge of clean, maintainable coding practices. Familiarity with CI/CD pipelines for 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 ❯

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 ❯