1 to 25 of 36 Remote Permanent Hugging Face Jobs

publish. What We’re Looking For 0–3 years of experience in Machine Learning, Data Science, or NLP/LLM. Strong Python skills; exposure to PyTorch/TensorFlow/Hugging Face. (Bonus) understand fundamentals of deep learning, LLMs, and MLOps, vector databases, embeddings, or retrieval-augmented generation (RAG). Loves solving complex problems and thrives in a fast-moving … Get Hands-on mentorship from senior ML engineers, AI researchers, and founders. Freedom to experiment with state-of-the-art models, tools, and frameworks. Modern tech stack (Python, LangChain, Hugging Face, OpenAI API, Pinecone, Kubernetes, etc.). Flexible working — remote-first culture with in-person team sessions for collaboration. Career acceleration — opportunities to own projects, lead development, and … genuinely moves the needle. Machine Learning Engineer, LLM Engineer, AI Engineer, Artificial Intelligence, Deep Learning, NLP, Natural Language Processing, Large Language Models, Generative AI, GenAI, Neural Networks, PyTorch, TensorFlow, Hugging Face, OpenAI, LangChain, RAG, Retrieval-Augmented Generation, Python, Data Science, AI Research, MLOps, Data Pipelines, Prompt Engineering, Model Fine-Tuning, Cloud Computing, AWS, Azure, Google Cloud, AI Infrastructure More ❯

deployed through a fully automated AWS environment (Terraform, Ansible, GitHub Actions). Alongside this, we're building the next generation of our data and AI infrastructure - exploring frameworks like Hugging Face, LangChain, LlamaIndex and agent orchestration systems. We use Cursor and Copilot to speed iteration and experimentation. We're always open to new approaches, whether it's a … message brokers (Kafka, SQS/SNS, RabbitMQ). Knowledge of real-time streaming (Kafka Streams, Apache Flink, etc.). Exposure to big-data or machine-learning frameworks (TensorFlow, PyTorch, Hugging Face, LangChain). Experience working with AI-driven development tools such as Cursor, Copilot, or Replit Ghostwriter. Understanding of infrastructure and DevOps (Terraform, Ansible, AWS, Kubernetes). Interest More ❯

deployed through a fully automated AWS environment (Terraform, Ansible, GitHub Actions). Alongside this, we're building the next generation of our data and AI infrastructure — exploring frameworks like Hugging Face, LangChain, LlamaIndex and agent orchestration systems. We use Cursor and Copilot to speed iteration and experimentation. We're always open to new approaches, whether it's a … balance speed, security, and reliability in a growing platform. You're passionate about AI and LLMs — from using tools like Cursor and Copilot to experimenting with frameworks such as Hugging Face or LangChain. You communicate clearly, collaborate across disciplines, and translate technical complexity into business context. You enjoy guiding direction while staying hands-on when needed. Nice to More ❯

tool use, memory and hand-offs; build resilient multi-agent journeys for discovery → advice → purchase. LLM training & tuning: Run LoRA/QLoRA/full fine-tunes with PyTorch/Hugging Face on Vertex AI ; own data curation and the evaluation harness. Measurement: Set and track KPIs (task completion, hand-off success, latency/cost/factuality, business outcomes … Classical ML where it counts: Ship intent classifiers, outcome forecasters and recommendation pipelines with scikit-learn/XGBoost/LightGBM . Stack (core) Python (production-grade) LLM tooling: PyTorch, Hugging Face, TensorFlow Fine-tuning: LoRA/QLoRA/full training GCP/Vertex AI: Training, Pipelines, Registry/Deploy Experimentation: SQL, A/B test design, causal thinking More ❯

MSc or equivalent experience) Hands-on experience building and deploying Agentic AI or multi-agent systems Proficiency in Python and popular AI/ML frameworks (e.g., PyTorch, TensorFlow, LangChain, Hugging Face) Familiarity with LLM fine-tuning, reasoning, and retrieval-augmented generation (RAG) techniques Experience integrating AI models into production systems or orchestration platforms Strong analytical and problem-solving … at least the next 5 years. Profile 29 recruitment keywords: Artificial intelligence large language models AI machine learning Agentic AI multi-agent Python AI/ML PyTorch TensorFlow LangChain Hugging Face LLM retrieval augmented generation RAG AI models orchestration platforms Public sector SC Security Clearance agent architectures ReAct AutoGen CrewAI BabyAGI reasoning loops memory systems governance frameworks public More ❯

MSc or equivalent experience) Hands-on experience building and deploying Agentic AI or multi-agent systems Proficiency in Python and popular AI/ML frameworks (e.g., PyTorch, TensorFlow, LangChain, Hugging Face) Familiarity with LLM fine-tuning, reasoning, and retrieval-augmented generation (RAG) techniques Experience integrating AI models into production systems or orchestration platforms Strong analytical and problem-solving … at least the next 5 years. Profile 29 recruitment keywords: Artificial intelligence large language models AI machine learning Agentic AI multi-agent Python AI/ML PyTorch TensorFlow LangChain Hugging Face LLM retrieval augmented generation RAG AI models orchestration platforms Public sector SC Security Clearance agent architectures ReAct AutoGen CrewAI BabyAGI reasoning loops memory systems governance frameworks public More ❯

MSc or equivalent experience) Hands-on experience building and deploying Agentic AI or multi-agent systems Proficiency in Python and popular AI/ML frameworks (e.g., PyTorch, TensorFlow, LangChain, Hugging Face) Familiarity with LLM fine-tuning, reasoning, and retrieval-augmented generation (RAG) techniques Experience integrating AI models into production systems or orchestration platforms Strong analytical and problem-solving … at least the next 5 years. Profile 29 recruitment keywords: Artificial intelligence large language models AI machine learning Agentic AI multi-agent Python AI/ML PyTorch TensorFlow LangChain Hugging Face LLM retrieval augmented generation RAG AI models orchestration platforms Public sector SC Security Clearance agent architectures ReAct AutoGen CrewAI BabyAGI reasoning loops memory systems governance frameworks public More ❯

MSc or equivalent experience) Hands-on experience building and deploying Agentic AI or multi-agent systems Proficiency in Python and popular AI/ML frameworks (e.g., PyTorch, TensorFlow, LangChain, Hugging Face) Familiarity with LLM fine-tuning, reasoning, and retrieval-augmented generation (RAG) techniques Experience integrating AI models into production systems or orchestration platforms Strong analytical and problem-solving … at least the next 5 years. Profile 29 recruitment keywords: Artificial intelligence large language models AI machine learning Agentic AI multi-agent Python AI/ML PyTorch TensorFlow LangChain Hugging Face LLM retrieval augmented generation RAG AI models orchestration platforms Public sector SC Security Clearance agent architectures ReAct AutoGen CrewAI BabyAGI reasoning loops memory systems governance frameworks public More ❯

field (Master's a plus) Extensive experience in professional software development Strong Python skills and a track record of delivering maintainable, well-tested code Experience with LLM APIs (OpenAI, Hugging Face, Anthropic) or ML frameworks (PyTorch, TensorFlow) Solid understanding of CI/CD, Git, testing, and agile methodologies Hands-on experience with Linux, Docker, and containerized deployments Familiarity More ❯

programming skills in Python and SQL, and fluency with leading ML/AI frameworks (e.g., scikit-learn, TensorFlow, PyTorch) Direct experience with GenAI/LLM technologies, including tools like Hugging Face, LangChain, OpenAI APIs, vector databases, and fine-tuning methods Deep knowledge of machine learning algorithms (supervised, unsupervised, deep learning), including model evaluation, explainability, and selection for business More ❯

programming skills in Python and SQL, and fluency with leading ML/AI frameworks (e.g., scikit-learn, TensorFlow, PyTorch) Direct experience with GenAI/LLM technologies, including tools like Hugging Face, LangChain, OpenAI APIs, vector databases, and fine-tuning methods Deep knowledge of machine learning algorithms (supervised, unsupervised, deep learning), including model evaluation, explainability, and selection for business More ❯

Exposure to tools like KServe, Ray Serve, Triton, or vLLM a big plus Bonus Points: Experience with observability frameworks like Prometheus or OpenTelemetry Knowledge of ML libraries: TensorFlow, PyTorch, HuggingFace Exposure to Azure or GCP Passion for financial services Requirements: Degree in Computer Science, Engineering, Data Science or similar What We Offer A collaborative and innovative work environment with awesome More ❯

foundational understanding and subsequent practical application of ML techniques, preferably NLPs, LLMs, Bayesian Optimisation and MCMCs Strong proficiency in Python and ML frameworks and tools (e.g. PyTorch, TensorFlow, JAX, Hugging Face, vLLM, MCP, prompt engineering) Excellent communication skills and ability to explain ML concepts to non-technical stakeholders Ability to work effectively in multi-disciplinary teams, collaborating across More ❯

foundational understanding and subsequent practical application of ML techniques, preferably NLPs, LLMs, Bayesian Optimisation and MCMCs Strong proficiency in Python and ML frameworks and tools (e.g. PyTorch, TensorFlow, JAX, Hugging Face, vLLM, MCP, prompt engineering) Excellent communication skills and ability to explain ML concepts to non-technical stakeholders Ability to work effectively in multi-disciplinary teams, collaborating across More ❯

crew of agents etc.). Ability to move quickly while maintaining code quality, test coverage, and operational excellence. Preferred: Familiarity with AI/ML tools such as LangChain, Haystack, Hugging Face, Weaviate, or similar ecosystems. Hands-on experience with Retrieval Augmented Generation applications, AI agents and systems built around them. Experience using GenAI frameworks such as LlamaIndex, Crew More ❯

crew of agents etc.). Ability to move quickly while maintaining code quality, test coverage, and operational excellence. Preferred: Familiarity with AI/ML tools such as LangChain, Haystack, Hugging Face, Weaviate, or similar ecosystems. Hands-on experience with Retrieval Augmented Generation applications, AI agents and systems built around them. Experience using GenAI frameworks such as LlamaIndex, Crew More ❯

crew of agents etc.). Ability to move quickly while maintaining code quality, test coverage, and operational excellence. Preferred: Familiarity with AI/ML tools such as LangChain, Haystack, Hugging Face, Weaviate, or similar ecosystems. Hands-on experience with Retrieval Augmented Generation applications, AI agents and systems built around them. Experience using GenAI frameworks such as LlamaIndex, Crew More ❯

with LLMs and AI-powered search systems. Design and implement Retrieval-Augmented Generation (RAG) pipelines using open-source tools like LangChain, Langflow, and DataStax Vector Search. Fine-tune LLMs (Hugging Face, OpenAI, Cohere, or similar) to improve response quality and domain-specific performance. Optimize embedding models for better semantic search and document retrieval. Integrate AI-driven solutions with More ❯

Degree in Computer Science, AI, or related field (or equivalent practical experience). Cloud, AI/ML, or CX vendor certifications (AWS/Azure/GCP, Genesys Cloud, OpenAI, Hugging Face, etc.) are a plus. Flexible/remote working options Private healthcare and life insurance Pension plan Cycle-to-work scheme 28 days paid annual leave (including company More ❯

Degree in Computer Science, AI, or related field (or equivalent practical experience). Cloud, AI/ML, or CX vendor certifications (AWS/Azure/GCP, Genesys Cloud, OpenAI, Hugging Face, etc.) are a plus. Flexible/remote working options Private healthcare and life insurance Pension plan Cycle-to-work scheme 28 days paid annual leave (including company More ❯

Degree in Computer Science, AI, or related field (or equivalent practical experience). Cloud, AI/ML, or CX vendor certifications (AWS/Azure/GCP, Genesys Cloud, OpenAI, Hugging Face, etc.) are a plus. Flexible/remote working options Private healthcare and life insurance Pension plan Cycle-to-work scheme 28 days paid annual leave (including company More ❯

Degree in Computer Science, AI, or related field (or equivalent practical experience). Cloud, AI/ML, or CX vendor certifications (AWS/Azure/GCP, Genesys Cloud, OpenAI, Hugging Face, etc.) are a plus. Flexible/remote working options Private healthcare and life insurance Pension plan Cycle-to-work scheme 28 days paid annual leave (including company More ❯

Degree in Computer Science, AI, or related field (or equivalent practical experience). Cloud, AI/ML, or CX vendor certifications (AWS/Azure/GCP, Genesys Cloud, OpenAI, Hugging Face, etc.) are a plus. Flexible/remote working options Private healthcare and life insurance Pension plan Cycle-to-work scheme 28 days paid annual leave (including company More ❯

track record of impactful research, evidenced by publications, patents, or significant contributions to open-source projects. Deep expertise in deep learning frameworks (e.g., TensorFlow, PyTorch) and NLP libraries (e.g., Hugging Face Transformers). Proficiency in programming languages such as Python. Experience with large-scale data processing and distributed computing. Strong analytical and problem-solving skills. Excellent communication and More ❯

learning or transformer based architectures • Hands on experience building and maintaining Frontend applications - React, Typescript • Strong programming background in Python and or relevant frameworks such as TensorFlow, PyTorch or Hugging Face • Fluent in cloud native development, containerisation, orchestration (for example Docker or Kubernetes) and CI/CD • Exceptional problem solver with an entrepreneurial mindset who is comfortable with More ❯