our product and community. Engineering Design, develop, and optimize AI/ML features in Qdrant's core engine and SDKs. Prototype and implement integrations with popular ML frameworks (e.g., HuggingFace, OpenAI, LangChain). Analyze performance, identify bottlenecks, and implement scalable solutions in real-world AI pipelines. Collaborate with product and engineering teams to define and deliver impactful … inform product development. Requirements Strong proficiency in Python. Solid understanding of machine learning concepts, embeddings, and vector search. Experience with at least one modern ML framework (e.g., PyTorch, TensorFlow, HuggingFace). Excellent communication skills; ability to explain technical topics to diverse audiences. Prior experience contributing to open-source projects or engaging with developer communities. Comfortable presenting and More ❯
on expertise building and deploying deep learning models (e.g., 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. Able to contextualise these techniques in industry settings, such as financial forecasting, operations optimisation, or customer segmentation. Comfortable with key ML frameworks (such as Scikit-learn, TensorFlow, PyTorch, HuggingFace) and data manipulation tools (Pandas, NumPy), as well as version control, containerisation, and ML deployment pipelines. Understands how to apply MLOps principles in production environments To be … essential. Staying updated on the latest trends and research is important. Motivation Techniques - Being able to motivate and inspire learners to stay committed to their programme, even in the face of challenges. Self-awareness - Ability to understand your own biases, values, and beliefs, which can impact your coaching approach. Time Management - Effective time management skills are essential for structuring More ❯
Cambridge, Cambridgeshire, United Kingdom Hybrid / WFH Options
Arm Limited
applications. Proficiency in Python and common ML/AI libraries; comfortable with full-stack system design from prototyping to production deployment. Familiarity with one or more LLM stacks (OpenAI, HuggingFace Transformers, LangChain etc) Experience with model serving frameworks and scalable deployment strategies Experience with containerisation and orchestration "Nice To Have" Skills and Experience : Exposure to hardware design … at Arm Arm's approach to hybrid working is designed to create a working environment that supports both high performance and personal wellbeing. We believe in bringing people together face to face to enable us to work at pace, whilst recognizing the value of flexibility. Within that framework, we empower groups/teams to determine their own hybrid More ❯
London, South East, England, United Kingdom Hybrid / WFH Options
Opus Recruitment Solutions Ltd
principles and version control (Git) Experience working in cloud environments (AWS, GCP, or Azure) Ability to work independently and communicate effectively in a remote team Bonus Points Experience with HuggingFace Transformers , LangChain , or RAG pipelines Knowledge of MLOps tools (e.g. MLflow, Weights & Biases, Docker, Kubernetes) Exposure to data engineering or DevOps practices Contributions to open-source AI More ❯
data lake architectures, data integration, and data governance, and at least 2 years of experience with cloud-based AI/ML technologies (such as tools from AWS, Azure, Google, HuggingFace, OpenAI and Databricks) building ML or applied AI solutions. A passion for Generative AI, and an understanding of strengths and weaknesses of Generative LLM's Fundamental knowledge of ML, and 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 ❯
pipelines Working knowledge of embedding compliance and security in ML systems, including governance, access controls, and regulatory alignment (e.g., GDPR, HIPAA) Proficient with modern AI tooling and ecosystems, including HuggingFace, Cursor, vector DBs, and productivity tools that accelerate GenAI development Expertise in GenAI and LLMs, with hands-on experience in RAG solutions and agentic frameworks; capable of More ❯
deployment tools (e.g., Docker, Kubernetes). Excellent problem-solving skills and the ability to work on complex AI challenges. Nice to Have: Experience with NLP frameworks, transformer architectures, and HuggingFace libraries. Knowledge of AI ethics, data privacy, and model interpretability. Previous experience working on AI-based translation, automation, or localization projects. Roadmap for Success First 90 Days More ❯
development tools such as Cursor, Claude Code, Codex, and GitHub Copilot for technical analysis, code generation and code review. Hands-on experience with AI/ML frameworks (PyTorch, TensorFlow, HuggingFace) and LLM orchestration tools (LangChain, LangGraph, or similar) Experience deploying ML models using containerised solutions (Docker, Kubernetes) and frameworks like BentoML or equivalent. Familiarity with vector databases and retrieval pipelines More ❯
Saffron Walden, Essex, South East, United Kingdom Hybrid / WFH Options
Smile Digital Talent Ltd
AI researchers, and data scientists, driving end-to-end AI solution delivery. Designing and implementing AI architectures across cloud and on-prem environments, leveraging tools like PyTorch, TensorFlow, and Hugging Face. Spearheading the development of production ready AI models, from foundational LLMs to custom built cognitive agents, solving real world business challenges. Establishing scalable ML/AI pipelines and 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 ❯
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 ❯
audiences What we need from you: Strong background in NLP and AI, particularly with LLMs and RAG-based solutions Proficiency in Python and modern AI/ML libraries (e.g. HuggingFace, LangChain, TensorFlow, PyTorch) Experience with data exchange and storage frameworks (e.g. APIs, SQL, NoSQL, Parquet) Track record of delivering technical solutions in Agile environments Excellent communication skills and a collaborative More ❯
and implemention synchronous, asynchronous and batch data processing operations Expert level programming skills in Python, along with experience in using relevant tools and frameworks such as PyTorch, FastAPI and Huggingface; strong programming skills in Java are a plus Expert level know-how of ML Ops systems, data pipeline design and implementation, and working with ML platforms (preferably AWS SageMaker) Strong More ❯
and Demonstrate Build proof-of-concepts (PoCs) or demos to validate solution approaches and inspire client confidence. Showcase AI capabilities using relevant tools (e.g. Power BI + Azure ML, HuggingFace, LangChain, GPT APIs). 5. Track Industry Trends and Use Cases Stay ahead of market trends in Generative AI, Responsible AI, and emerging AI use cases across … ML concepts: supervised and unsupervised learning, GenAI, LLMs, embeddings, MLOps, vector search. Experience designing solutions using tools such as Azure ML, AWS SageMaker, Google Vertex AI, Databricks, LangChain, and Hugging Face. Ability to develop architecture artefacts (e.g., HLDs), estimate effort and cost, and contribute to proposal writing. Strong storytelling and presentation skills; able to build confidence with senior business More ❯
London, South East, England, United Kingdom Hybrid / WFH Options
Opus Recruitment Solutions Ltd
ML workflows with platforms such as Benchling , PubMed APIs , and internal R&D systems Supporting model validation, performance benchmarking, and regulatory documentation Key Technologies & Tools: ML Frameworks: PyTorch, TensorFlow, HuggingFace Transformers Bio-AI Tools: AlphaFold, RoseTTAFold, BioBERT, DeepCell, Cellpose Data Sources: Genomic datasets, microscopy images, biomedical literature Cloud & DevOps: AWS/GCP, Docker, Kubernetes, MLflow Languages: Python More ❯
pipelines (GitLab), and containerization (Docker). Strong Python programming skills: Strong programming skills in Python, including its ecosystem for AI/ML, with experience using libraries such as PyTorch, HuggingFace Transformers, scikit-learn, and TensorFlow to build and implement AI-driven solutions. Product mindset: Ability to think from the user's perspective and design solutions that align More ❯
pipelines (GitLab), and containerization (Docker). Strong Python programming skills: Strong programming skills in Python, including its ecosystem for AI/ML, with experience using libraries such as PyTorch, HuggingFace Transformers, scikit-learn, and TensorFlow to build and implement AI-driven solutions. Product mindset: Ability to think from the user's perspective and design solutions that align More ❯
tune those models eg. XGBoost, Deep Neural Networks, Transformers, ResNets, VAEs, GANs, Markov chains, etc. Experience using specialized machine learning libraries eg. Fastai, Keras, Tensorflow, pytorch, sci-kit learn, huggingface, etc. Must demonstrate the capacity of reading, understanding and implementing new techniques in the field of machine learning as they emerge. Experience of using Cloud technologies eg. AWS, GCP or More ❯
