preprocessing, and feature engineering. Proven experience building and deploying RAG systems and/or LLM-powered applications in production environments. Proficiency in Python and ML libraries such as PyTorch, HuggingFace Transformers , or TensorFlow. Experience with vector search tools (e.g., FAISS, Pinecone, Weaviate) and retrieval frameworks (e.g., LangChain, LlamaIndex). Hands-on experience with fine-tuning and distillation More ❯
on expertise building and deploying deep learning models (eg, CNNs, Transformers, graph neural networks) in real-world applications. Proficiency in Python and core ML libraries (PyTorch, TensorFlow, scikit-learn, HuggingFace, etc.). Strong software engineering background: data structures, algorithms, distributed systems, and version control (Git). Experience designing scalable ML infrastructure on cloud platforms (AWS SageMaker, GCP More ❯
AI/ML services, especially Vertex AI (Workbench, Training, Prediction, Pipelines, Feature Store). • Proficiency in Python and strong experience with AI/ML frameworks (e.g., TensorFlow, PyTorch, JAX, HuggingFace Transformers). • Experience with data engineering and building robust data pipelines for AI/ML workloads on GCP (e.g., BigQuery, Dataflow). • Solid understanding of core AI More ❯
AI/ML services, especially Vertex AI (Workbench, Training, Prediction, Pipelines, Feature Store). • Proficiency in Python and strong experience with AI/ML frameworks (e.g., TensorFlow, PyTorch, JAX, HuggingFace Transformers). • Experience with data engineering and building robust data pipelines for AI/ML workloads on GCP (e.g., BigQuery, Dataflow). • Solid understanding of core AI More ❯
Gemini, Llama, Falcon, Mistral. 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, HuggingFace, LangChain. MLOps and deployment: Docker, Kubernetes, Azure ML Studio, MLFlow. Cloud and AI infrastructure: Experience with Azure Cloud for scalable deployment. Databases and data platforms: SQL, NoSQL More ❯
engineering. Demonstrated experience working closely with business stakeholders in R&D, translating complex scientific challenges into AI solutions. Proficiency in Python and ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn, HuggingFace). Experience building and deploying models in cloud environments (e.g. Azure, GCP). Solid understanding of statistics, optimization, and experimental design. Preferred Qualifications & Skills: Please note the More ❯
working relationships with cross-functional teams. Ability to clearly communicate and present to internal and external stakeholders. Nice to have, but not essential NLP/Deep learning experience (e.g. huggingface, spaCy) Deep learning framework experience (preferably PyTorch) MLOps experience (e.g. data and model versioning, model deployment CI/CD, MLFlow/DVC) Cloud platform experience, especially from an ML standpoint … to the NiCE-FLEX hybrid model, which enables maximum flexibility: 2 days working from the office and 3 days of remote work, each week. Naturally, office days focus on face-to-face meetings, where teamwork and collaborative thinking generate innovation, new ideas, and a vibrant, interactive atmosphere. Requisition ID: 7522 Reporting into: Director, Product, CX About NICE NICELtd. More ❯
define priorities and influence the product roadmap What we look for: Experience building Generative AI applications, including RAG, agents, text2sql, fine-tuning, and deploying LLMs, with tools such as HuggingFace, Langchain, and OpenAI Extensive hands-on industry data science experience, leveraging typical machine learning and data science tools including pandas, scikit-learn, and TensorFlow/PyTorch Experience building production-grade More ❯
LLM such as GPT, LLaMA, Claude, or similar, including fine-tuning, prompt engineering, and deploying models in production environments. Strong proficiency in Python, with expertise in using frameworks like HuggingFace Transformers, LangChain, OpenAI APIs, or other LLM orchestration tools. A solid understanding of tokenization, embedding models, vector databases (e.g., Pinecone, Weaviate, FAISS), and retrieval-augmented generation (RAG More ❯
LLM such as GPT, LLaMA, Claude, or similar, including fine-tuning, prompt engineering, and deploying models in production environments. Strong proficiency in Python, with expertise in using frameworks like HuggingFace Transformers, LangChain, OpenAI APIs, or other LLM orchestration tools. A solid understanding of tokenization, embedding models, vector databases (e.g., Pinecone, Weaviate, FAISS), and retrieval-augmented generation (RAG 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 (HuggingFace, LangChain, OpenAI APIs) Vector Understanding : Solid knowledge of embeddings, vector databases (Pinecone, Weaviate, FAISS), and RAG pipelines NLP Fundamentals : Text preprocessing, language modelling, and semantic similarity Cloud More ❯
or related technical field 2+ years of experience in AI/ML development with a focus on practical applications Strong proficiency in Python and relevant AI libraries (TensorFlow, PyTorch, HuggingFace) Hands-on experience with workflow automation platforms like N8N, AirTable, and proven track-record. Experience with AI agent development and testing methodologies using Google ADK, LangGraph, Llamaindex More ❯
a culture of invention: small team, big ambition, zero bureaucracy. This is applied AI with teeth. We move fast, experiment often, and ship real value. Our stack spans OpenAI, HuggingFace, Python, React, AWS - but tools are just the start. Your Unique Mission As an Engineer in our AI team, you'll engineer AI-driven products from scratch … self-directed approach to tackling ambiguous problems, consistently delivering high-impact results. Your toolkit includes: Solid Python programming skills, and comfort working with popular ML libraries like PyTorch or HuggingFace (even if not deeply experienced yet). Some experience developing software through the full development lifecycle. Exposure to building and experimenting with machine learning models - with personal More ❯
Production Experience: Demonstrated success in shipping and maintaining ML models in production, including performance monitoring and optimization. Strong Programming: Proficiency in Python and ML libraries (e.g., PyTorch, scikit-learn, HuggingFace, etc.); familiarity with MLOps tooling and cloud environments (AWS/GCP/Azure). Analytical & Communication Skills: Ability to clearly explain complex ideas, trade-offs, and results More ❯
cost and delivery timelines What we're looking for 4-5 years relevant experience Proficiency in Python or similar programming languages Experience with GenAI tools (LangGraph, CrewAI, OpenAI APIs, HuggingFace) ML fundamentals and LLM expertise (prompt engineering, cost optimization) Cloud platforms (AWS/GCP/Azure) and infrastructure-as-code DevOps tooling (CI/CD, Docker, Kubernetes More ❯
City of London, London, United Kingdom Hybrid / WFH Options
Understanding Recruitment
cost and delivery timelines What we're looking for 4-5 years relevant experience Proficiency in Python or similar programming languages Experience with GenAI tools (LangGraph, CrewAI, OpenAI APIs, HuggingFace) ML fundamentals and LLM expertise (prompt engineering, cost optimization) Cloud platforms (AWS/GCP/Azure) and infrastructure-as-code DevOps tooling (CI/CD, Docker, Kubernetes More ❯
sharing and technical discussions Skills and experience required Proven experience delivering ML and/or Generative AI projects from concept to deployment Hands-on experience with frameworks such as HuggingFace, LangChain, and open-source LLMs Familiarity with tools such as Databricks and modern MLOps workflows Strong Python skills and familiarity with common data science tools and libraries More ❯
sharing and technical discussions Skills and experience required Proven experience delivering ML and/or Generative AI projects from concept to deployment Hands-on experience with frameworks such as HuggingFace, LangChain, and open-source LLMs Familiarity with tools such as Databricks and modern MLOps workflows Strong Python skills and familiarity with common data science tools and libraries More ❯
Practical knowledge of AI/ML technologies and their applications, including understanding language models (LLMs), and experience with training and fine-tuning LLMs using frameworks like TensorFlow, PyTorch, or HuggingFace Transformers. Good understanding of programming/scripting: (e.g., Python, Go) for customizing solutions, creating scripts, or automating tasks. Experience with AI relevant infrastructure, including Networking (InfiniBand and 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 ❯
City of London, London, United Kingdom Hybrid / WFH Options
Intellect Group
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 ❯
of relevant pipeline and processes. Work experience with working in Linux and Microsoft Azure. Nice to Have Experience with deep learning, machine learning and NLP frameworks such as PyTorch, HuggingFace Transformer, Scikit-learn. Experience with multiple cloud platforms such as AWS, Google Cloud Platform, Oracle, NVIDIA, or on-prem environments. Perks and Benefits Salary dependent on experience Package of attractive More ❯
Vector Search: Use FAISS, Weaviate, Pinecone, ChromaDB, OpenSearch Required skills & experience: 3–5+ years of experience in ML engineering and software development Deep Python proficiency, with PyTorch, TensorFlow or HuggingFace Proven experience with LLMs, RAG, and deploying cloud-native AI on AWS Strong full-stack skills (React, TypeScript, Node.js) and API development Familiarity with vector databases and More ❯
Vector Search: Use FAISS, Weaviate, Pinecone, ChromaDB, OpenSearch Required skills & experience: 3–5+ years of experience in ML engineering and software development Deep Python proficiency, with PyTorch, TensorFlow or HuggingFace Proven experience with LLMs, RAG, and deploying cloud-native AI on AWS Strong full-stack skills (React, TypeScript, Node.js) and API development Familiarity with vector databases and More ❯
Experience or coursework in machine learning, deep learning, or AI techniques (e.g., supervised learning, neural networks, NLP). Proficiency in Python and libraries like Scikit-learn, TensorFlow, PyTorch, or HuggingFace Transformers. Familiarity with data preprocessing, model evaluation, and deploying models in real-world environments. A passion for AI innovation and a desire to build systems that learn More ❯
