51 to 75 of 130 Remote Hugging Face Jobs

projects—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 skills and the ability to translate technical insights More ❯

projects—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 skills and the ability to translate technical insights More ❯

building services with Flask. 5-8+ years of relevant AI/ML and/or software development experience Experience working with model libraries such as ScikitLearn, spaCy, and Hugging Face. Experience with MLOps including preparing data, training, evaluating, and deploying models. Design, build, and maintain scalable data pipelines and infrastructure to support our data-driven initiatives. Work closely More ❯

ML and/or software development experience. Proficiency in Python, including experience in or knowledge of building services with Flask. Understanding of model libraries such as ScikitLearn, spaCy, and Hugging Face. Understanding of MLOps concepts including preparing data, training, evaluating, and deploying models. Understanding of how data pipelines and infrastructure supports large scale systems. Ability to research, establish, and More ❯

a leadership role . Strong understanding of software architecture, design patterns, and cloud-native development (preferably AWS or GCP). Experience with AI/ML frameworks (e.g., TensorFlow, PyTorch, Hugging Face) and deploying models in production. Proficiency in building RESTful APIs, microservices, and working with asynchronous frameworks (e.g., FastAPI, asyncio). Familiarity with containerization (Docker, Kubernetes) and CI More ❯

training frameworks, libraries and tools. Deep knowledge of state-of-the-art transformer and non-transformer modifications aimed at enhancing intelligence, efficiency and scalability. Strong expertise in PyTorch and Hugging Face libraries with practical experience in model development, continual pretraining, and deployment. More ❯

training frameworks, libraries and tools. Deep knowledge of state-of-the-art transformer and non-transformer modifications aimed at enhancing intelligence, efficiency and scalability. Strong expertise in PyTorch and Hugging Face libraries with practical experience in model development, continual pretraining, and deployment. More ❯

will have a strong focus on delivering code that is observable, resilient, and secure. Required Skill set: Highly Skilled in Python and familiarity with libraries and frameworks TensorFlow, PyTorch, Hugging Face Transformers, etc. Proven experience designing, develop, and implement machine learning models with a focus on NLP and LLM applications. Extensive experience with NLP techniques and tools such More ❯

for transformer architectures as well as alternative approaches. Your expertise should emphasize techniques that enhance model intelligence, efficiency, and scalability within fine-tuning workflows. Strong expertise in PyTorch and Hugging Face libraries with practical experience in developing fine-tuning pipelines, continuously adapting models to new data, and deploying these refined models in production on target platforms. Demonstrated ability More ❯

essential 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 engineering pipelines or big data technologies (e.g., Kafka More ❯

the road is unpaved and you have free rein (with the CTO as sparring partner and advisor). Steer buy vs build calls -Evaluate third party APIs (OpenAI, Anthropic, Hugging Face, etc.) versus in house models; drive clear recommendations on cost, performance, and time to value. Drive commercial impact -Measure and iterate on ML powered adoption, upsell ARR More ❯

not essential 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 engineering pipelines or big data technologies (e.g., Kafka, Spark More ❯

fine tuning, RAG). Experience building and fine-tuning various ML Models (supervised and unsupervised models, classification, clustering, regression etc) Hands on experience with common ML libraries such as Hugging Face, XGBoost, PyTorch, TensorFlow) Track record of building and deploying ML models in production with ability to monitor and remediate model decay of production ML models. Can provide More ❯

power AI use cases. You will design and implement high performance data I/O, work with open source teams to identify and resolve issues in popular libraries like Huggingface, Horovod and PyTorch, enable distributed training over 100s of billions of parameter models, debug and optimize deep learning training, and provide advanced support for internal AI teams in areas like … and helping to build a fast-growing team. -Working closely with the open-source community to participate and influence cutting edge open-source projects (e.g., vLLMs, PyTorch, GNNs, DeepSpeed, Huggingface, etc.). -Functioning as the tech-lead for several concurrent key initiatives AI Infrastructure and defining the future of AI Platforms. Basic Qualifications: - BS/BA in Computer Science or More ❯

or a related language Strong skills in algorithm development to solve optimisation problems Familiarity with core tools for a typical ML-focused work environment (e.g. Git, IDE, common libraries, HuggingFace). Ability to work as part of a team Be comfortable with a fast-paced, high-risk, and a high reward environment Experience creating data sets Experience coordinate development of More ❯

or a related language Strong skills in algorithm development to solve optimisation problems Familiarity with core tools for a typical ML-focused work environment (e.g. Git, IDE, common libraries, HuggingFace). Ability to work as part of a team Be comfortable with a fast-paced, high-risk, and a high reward environment Experience creating data sets Experience coordinate development of More ❯

or a related language Strong skills in algorithm development to solve optimisation problems Familiarity with core tools for a typical ML-focused work environment (e.g. Git, IDE, common libraries, HuggingFace). Ability to work as part of a team Be comfortable with a fast-paced, high-risk, and a high reward environment Experience creating data sets Experience coordinate development of More ❯

computational reasoning, with hands-on experience in symbolic AI techniques, knowledge representation, and rule-based systems. Experience with large language models (LLMs) and associated tooling( for example OpenAI, Anthropic, Huggingface), and a solid grasp of natural language processing techniques to enhance machine understanding and interaction. Knowledge of vector databases, embeddings, and retrieval-augmented generation style architectures. A proven track record More ❯

Machine Learning Engineer - SaaS - London (Tech stack: Machine Learning Engineer, Python, TensorFlow, PyTorch, scikit-learn, Keras, Natural Language Processing (NLP), Hugging Face Transformers, Pandas, NumPy, Jupyter Notebooks, Matplotlib, Seaborn, Flask (for building APIs), FastAPI, Docker, MLflow, DVC (Data Version Control), AWS SageMaker, Azure Machine Learning, Google Cloud AI Platform, TensorFlow Serving, ONNX (Open Neural Network Exchange) We have … of the following (full training will be provided to fill any gaps in your skill set): Machine Learning Engineer, Python, TensorFlow, PyTorch, scikit-learn, Keras, Natural Language Processing (NLP), Hugging Face Transformers, Pandas, NumPy, Jupyter Notebooks, Matplotlib, Seaborn, Flask (for building APIs), FastAPI, Docker, MLflow, DVC (Data Version Control), AWS SageMaker, Azure Machine Learning, Google Cloud AI Platform More ❯

collaborate closely with a cross-functional team of ML engineers, data scientists, and product managers to build robust and scalable ML systems. Our team relies on tools like PyTorch, Hugging Face, and internal infrastructure for model training, deployment, and experimentation. Requirements Strong understanding of machine learning fundamentals and the practical trade-offs involved in applying them … z2bz0 years' experience with deep learning and NLP Experience with Pytorch or other deep learning frameworks Hands-on experience fine-tuning LLMs or working with frameworks such as Hugging Face Transformers Proven experience deploying ML models to production and maintaining end-to-end ML pipelines Solid communication skills - in person, in writing, in code, and code-review; to More ❯

Cloud AI (AWS/Azure): Experience deploying AI solutions on cloud platforms. Python: Proficient in writing clean, production-quality code. AI Model Management: Familiarity with platforms such as MLFlow, Hugging Face, or LangChain. Data Processing: Experience with Databricks/Spark. SQL: Solid querying and data preparation skills. Data Architectures: Understanding of modern data systems (lakehouses, data lakes). More ❯

delivering AI solutions in production cloud environments. Advanced Python: Expertise in developing efficient, production-grade AI/ML code. LLMOps & AI Model Management: Experience with tools like MLFlow, LangChain, Hugging Face, Kubeflow, or similar platforms. Data Processing: Proficient with Databricks/Spark for large-scale AI data processing. SQL: Strong capabilities in data querying and preparation. Data Architectures More ❯

environment Experience with Agile software development methodologies Familiar with GPU acceleration tools such as PyTorch Familiar with HPC workload managers such as Slurm Familiar with ML frameworks such as Hugging Face Qualifications Master's degree in computer science or related discipline from an accredited college or university, plus ten (10) years of experience as a SWE, in programs More ❯

cost-effectiveness, and sustainability Guide junior team members and improve engineering best practices 🧠 Your skillset: Expert Python dev (pandas, FastAPI, Pydantic) Strong ML/AI experience incl. AutoML, LLMs, HuggingFace, LangChain Proficiency in Linux, Git, PostgreSQL, and API development Experience deploying AI models in containerised, cloud-based environments Bonus: agentic AI (smolagents, AutoGen), fine-tuning, MLOps know-how If you More ❯

cost-effectiveness, and sustainability Guide junior team members and improve engineering best practices Your skillset: Expert Python dev (pandas, FastAPI, Pydantic) Strong ML/AI experience incl. AutoML, LLMs, HuggingFace, LangChain Proficiency in Linux, Git, PostgreSQL, and API development Experience deploying AI models in containerised, cloud-based environments Bonus: agentic AI (smolagents, AutoGen), fine-tuning, MLOps know-how If you More ❯