351 to 375 of 778 Remote TensorFlow Jobs

or equivalent industry experience. Deep expertise in voice conversion, generative models, deep learning, or statistical modeling. Strong hands-on experience with ML frameworks (PyTorch, TensorFlow, Keras). Proficiency in Python and C/C++. Experience with scalable data tools (e.g., PySpark, Kubernetes, Databricks, Apache Arrow). Proven ability to More ❯

preferable. You'll be highly numerate with a statistical 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 ❯

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 ❯

through their development journey while fostering a culture of continuous learning and growth. Must Have: Base de Datos: PostgreSQL, MySQL, Snowflake, BigQuery MLOps: MLflow, TensorFlow, PyTorch, Scikit-learn. Cloud Expertise: Familiar with Kubernetes, Microservices, REST, OpenAPI, AWS, Docker, Containers, Terraform, CI/CD, Prometheus, Grafana, IaC, GitOps, Zero Trust More ❯

Excellent problem-solving skills and attention to detail. Proficiency in Python and strong programming skills. Experience with LLMs and AI frameworks: Transformers, Pytorch/Tensorflow as well as RAG frameworks: Llama-index/LangChain. Ability to integrate new functional AI systems with APIs, low latency backends and production deployment. More ❯

Experience with tabular data, computer vision, imagery, point clouds, and game datasets. Proficiency with ML libraries like NumPy, OpenCV, scikit-learn, PyTorch/PyTorch3D, TensorFlow, Keras; familiarity with CI/CD, version control (GitLab, Perforce), and cloud platforms (preferably AWS). Benefits include: 22 days holidays + Christmas closure More ❯

you'll know your way around Git, SQL, and common Python data science libraries (like pandas/polars, scikit-learn, xgboost/lightGBM, and TensorFlow/PyTorch). Bonus points if you've worked with linear programming, or have experience in time series forecasting, agent-based modelling, and space More ❯

with knowledge representation, ontology design and semantic or LLM based reasoning is desirable but not essential. Essential: Experience with at least one ML framework: TensorFlow, Pytorch. Ability to work in a secure environment is essential. Desirable: Experience with one or more graph machine learning packages (PyTorch-Geometric, PyKeen etc. More ❯

Skills Required: LLM Experience : Production experience with GPT, Claude, LLaMA, including fine-tuning, prompt engineering, and deployment Python Proficiency : Strong skills with ML frameworks (TensorFlow, PyTorch) and LLM tools (Hugging Face, LangChain, OpenAI APIs) Vector Understanding : Solid knowledge of embeddings, vector databases (Pinecone, Weaviate, FAISS), and RAG pipelines NLP More ❯

design methods, in arts or health settings Experience with Image and/or audio-based AI development and familiar with libraries such as: SciPy, TensorFlow, PyTorch, Hugging Face Experience with Image and/or audio-based AI development Familiarity with research projects productivity timelines Knowledge of the peer review More ❯

design methods, in arts or health settings Experience with Image and/or audio-based AI development and familiar with libraries such as: SciPy, TensorFlow, PyTorch, Hugging Face Experience with Image and/or audio-based AI development Familiarity with research projects productivity timelines Knowledge of the peer review More ❯

to translate user needs into elegant front-end solutions AI Tool Development Develop and integrate AI/ML models into production systems using Python, TensorFlow, PyTorch, or similar frameworks. Build APIs and services that expose AI capabilities to internal and external consumers Data Tool Development Design and implement data More ❯

engineers, data scientists, or similar) Expert knowledge of ML fundamentals: supervised/unsupervised learning, time series, causal inference Experience with modern ML frameworks (PyTorch, TensorFlow, scikit-learn, CatBoost) Growth & Product Experience Experience with growth analytics, attribution modeling, or marketing effectiveness Understanding of user acquisition funnels and retention optimization Comfortable More ❯

or LLM based reasoning is desirable but not essential. Essential: Experience in software development in Python Essential: Experience with at least one ML framework: TensorFlow, Pytorch. Ability to work in a secure environment is essential. Desirable: Experience with one or more graph machine learning packages (PyTorch-Geometric, PyKeen etc. More ❯

of developing and deploying LLM-based solutions in an enterprise setting as a senior/staff scientist. Proficiency in Python and libraries such as TensorFlow, PyTorch, Hugging Face Transformers, and spaCy. Strong understanding of LLM architectures (e.g., GPT, BERT, T5) and experience fine-tuning them for specific tasks. Demonstrable More ❯

Machines (GBMs), Neural Networks and Large language models (LLMs). Hands-on experience with popular machine learning libraries such as Scikit-learn, XGBoost, LightGBM, TensorFlow, or PyTorch. Knowledge of AWS products and services including Sagemaker. Deep knowledge of Microsoft Excel in a commercial setting. You enjoy being Agile - you More ❯

Machines (GBMs), Neural Networks and Large language models (LLMs). Hands-on experience with popular machine learning libraries such as Scikit-learn, XGBoost, LightGBM, TensorFlow, or PyTorch. Knowledge of AWS products and services including Sagemaker. Deep knowledge of Microsoft Excel in a commercial setting. You enjoy being Agile - you More ❯

continuous integration Exposure to machine learning methodology and best practices Preferred but not must have: Exposure to deep learning approaches and modeling frameworks (PyTorch, Tensorflow, Keras, etc.) Education & Experience: 2–5 years experience building production-quality software. Bachelors or Masters degree and/or equivalent professional experience About Pandora More ❯

strong emphasis on threat detection. Solid experience in machine learning and data science, proficient in both supervised and unsupervised algorithms and frameworks such as TensorFlow, PyTorch, or Scikit-learn. Experience working with large, real-world datasets that require pre-processing, data visualization, and a great dose of analytical skills. More ❯

and vigilant monitoring. Expertise in C#, Python, and the tools and libraries that make AI magic happen like Semantic Kernel, Langchain/LangGraph, Keras, TensorFlow, Pytorch, etc. Experience in creating and delivering multi-tenant cloud solutions at scale using Docker, Kubernetes and Cloud services. Experience with Azure stack will More ❯

and Continuous Delivery (CI/CD), Test-Driven Development (TDD), SDLC, etc. Familiarity working within an agile team. Developing machine learning models (Python or TensorFlow). Familiarity with natural language processing or AI technologies (e.g. LLMs such as ChatGPT or BARD, Embeddings, Prompt Engineering). Experience with data pipelines More ❯

deployment, monitoring, and CI/CD pipelines for ML models (MLOps best practices). Example Tools & Technologies: Frameworks & Libraries: LangChain, Hugging Face Transformers, PyTorch, TensorFlow, Scikit-learn Agentic AI Tools: OpenAI GPT models, Crew,AI, Cohere, Pinecone (for vector databases), AutoGPT Data Engineering & ML Pipelines: Apache Airflow, MLflow, Kubeflow More ❯

in government, intelligence community, or other relevant decision-making offices Proficiency in Python or other popular programming languages and machine learning frameworks ( e.g. PyTorch , TensorFlow) Experience working on AI research, ML model training, and/or model deployment Experience in high-intensity fast-paced environments and/or navigating More ❯

post doctoral roles, a proven track record of publications, or contributions to machine learning codebases. Experience using ML frameworks such as JAX, PyTorch, or TensorFlow, and scientific software such as NumPy, SciPy, or Pandas Strong knowledge of linear algebra, calculus and statistics Experience working in a scientific environment across More ❯

ideally 3+ years within AI/Machine Learning. Experience of Swarming, Swarm Intelligence and/or Multi-agent systems. Python, C++, Java or Rust. TensorFlow, TensorFlow Lite, TensorRT, PyTorch, Scikit-Learn. ROS/ROS2, Real-time & Embedded Systems. Simulation tools such as Gazebo or Webots. Edge AI/ More ❯