201 to 225 of 663 Remote TensorFlow Jobs

DSP) and machine learning applied to audio. Proficiency in programming languages such as Python, C++, and MATLAB. Hands-on experience with deep learning frameworks (TensorFlow, PyTorch, etc.). Understanding of real-time and embedded audio processing techniques. Experience working with generative AI models for audio synthesis and transformation. Strong More ❯

DSP) and machine learning applied to audio. Proficiency in programming languages such as Python, C++, and MATLAB. Hands-on experience with deep learning frameworks (TensorFlow, PyTorch, etc.). Understanding of real-time and embedded audio processing techniques. Experience working with generative AI models for audio synthesis and transformation. Strong More ❯

DSP) and machine learning applied to audio. Proficiency in programming languages such as Python, C++, and MATLAB. Hands-on experience with deep learning frameworks (TensorFlow, PyTorch, etc.). Understanding of real-time and embedded audio processing techniques. Experience working with generative AI models for audio synthesis and transformation. Strong More ❯

DSP) and machine learning applied to audio. Proficiency in programming languages such as Python, C++, and MATLAB. Hands-on experience with deep learning frameworks (TensorFlow, PyTorch, etc.). Understanding of real-time and embedded audio processing techniques. Experience working with generative AI models for audio synthesis and transformation. Strong More ❯

DSP) and machine learning applied to audio. Proficiency in programming languages such as Python, C++, and MATLAB. Hands-on experience with deep learning frameworks (TensorFlow, PyTorch, etc.). Understanding of real-time and embedded audio processing techniques. Experience working with generative AI models for audio synthesis and transformation. Strong More ❯

DSP) and machine learning applied to audio. Proficiency in programming languages such as Python, C++, and MATLAB. Hands-on experience with deep learning frameworks (TensorFlow, PyTorch, etc.). Understanding of real-time and embedded audio processing techniques. Experience working with generative AI models for audio synthesis and transformation. Strong More ❯

DSP) and machine learning applied to audio. Proficiency in programming languages such as Python, C++, and MATLAB. Hands-on experience with deep learning frameworks (TensorFlow, PyTorch, etc.). Understanding of real-time and embedded audio processing techniques. Experience working with generative AI models for audio synthesis and transformation. Strong More ❯

DSP) and machine learning applied to audio. Proficiency in programming languages such as Python, C++, and MATLAB. Hands-on experience with deep learning frameworks (TensorFlow, PyTorch, etc.). Understanding of real-time and embedded audio processing techniques. Experience working with generative AI models for audio synthesis and transformation. Strong More ❯

DSP) and machine learning applied to audio. Proficiency in programming languages such as Python, C++, and MATLAB. Hands-on experience with deep learning frameworks (TensorFlow, PyTorch, etc.). Understanding of real-time and embedded audio processing techniques. Experience working with generative AI models for audio synthesis and transformation. Strong More ❯

DSP) and machine learning applied to audio. Proficiency in programming languages such as Python, C++, and MATLAB. Hands-on experience with deep learning frameworks (TensorFlow, PyTorch, etc.). Understanding of real-time and embedded audio processing techniques. Experience working with generative AI models for audio synthesis and transformation. Strong More ❯

DSP) and machine learning applied to audio. Proficiency in programming languages such as Python, C++, and MATLAB. Hands-on experience with deep learning frameworks (TensorFlow, PyTorch, etc.). Understanding of real-time and embedded audio processing techniques. Experience working with generative AI models for audio synthesis and transformation. Strong More ❯

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 ❯

statistics. Experience in data science within financial services, insurance, or E-commerce (not essential). Familiarity with cloud-based deployment. Knowledge of neural networks, TensorFlow, CatBoost, XGBoost, SKlearn, or Pandas. Experience with API development. Proficiency in SQL. Background in software engineering or DevOps/MLOps. Understanding of CI/ More ❯

statistics. Experience in data science within financial services, insurance, or E-commerce (not essential). Familiarity with cloud-based deployment. Knowledge of neural networks, TensorFlow, CatBoost, XGBoost, SKlearn, or Pandas. Experience with API development. Proficiency in SQL. Background in software engineering or DevOps/MLOps. Understanding of CI/ More ❯

statistics. Experience in data science within financial services, insurance, or E-commerce (not essential). Familiarity with cloud-based deployment. Knowledge of neural networks, TensorFlow, CatBoost, XGBoost, SKlearn, or Pandas. Experience with API development. Proficiency in SQL. Background in software engineering or DevOps/MLOps. Understanding of CI/ More ❯

languages (e.g., Go, Ruby). Minimum 3 years experience with cloud environments and/or CNCF concepts. Proficiency with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn. Strong understanding of data science principles. GitHub values Customer-obsessed Ship to learn Growth mindset Own the outcome Better together More ❯

be highly preferable. You’ll be highly numeratewith astatistical background, with strong expertise in Python essential. Exposure to ML Frameworks like Scikit Learn/TensorFlow/PyTorch would be beneficial. You’ll have a deep understanding of data analytics technologies and an eagerness to explore new tools and techniques. More ❯

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 ❯

in leading the development and deployment of big data solutions on Cloud platforms (essential) Programming for modelling and/or data analysis e.g. Python, Tensorflow (essential) Database experience, preferably SQL (essential) Expertise in cutting-edge AI methodologies, including Generative AI and Reinforcement Learning Machine learning - Supervised/unsupervised learning More ❯

roles, preferably in a fast-paced tech or enterprise environment. Proficient in Python or R, SQL, and common machine learning frameworks (e.g., scikit-learn, TensorFlow, XGBoost, PyTorch). Strong foundation in statistics, probability, and hypothesis testing. Experience with cloud platforms (AWS, GCP, Azure) and big data tools (Spark, Hive More ❯

Machine Learning Use Case Development, including: Practical experience with a statistical programming language (e.g., Python), applied machine learning techniques, and using OSS frameworks (e.g., TensorFlow, PyTorch). Building AI applications (e.g., deep learning, LLM/RAG, NLP, computer vision, or pattern recognition). Machine Learning Operations design, including: Previous More ❯

Demonstrable interest in Artificial Intelligence, Machine Learning, Deep Learning, or Natural Language Processing. Some hands-on experience with AI concepts, libraries, or frameworks (e.g., TensorFlow, PyTorch, scikit-learn, Hugging Face Transformers, Keras, etc.). Familiarity with Python for AI/ML development is a significant advantage. Experience with data More ❯

Counterfactuals Estimation, Optimization and Scenarios simulation Good experience with Probabilistic Programming and Bayesian Methods Experience using machine learning frameworks such as scikit-learn, Pymc, TensorFlow, PyTorch, Databricks ML, Keras etc..., Experience with ML at scale Proven attention to detail, critical thinking, and the ability to work both independently and More ❯

in leading the development and deployment of big data solutions on Cloud platforms (essential) Programming for modelling and/or data analysis e.g. Python, Tensorflow (essential) Database experience, preferably SQL (essential) Expertise in cutting-edge AI methodologies, including Generative AI and Reinforcement Learning Machine learning - Supervised/unsupervised learning More ❯

languages such as Python or Java. Understanding of cloud platforms (Google Cloud, AWS, Vertex AI, Sagemaker). Bonus points! Experience with ML frameworks like TensorFlow, PyTorch, or scikit-learn. Experience with data analysis or data science The experience, skills, and attributes listed above reflect what we believe will contribute More ❯