Responsibilities: Design, train, and optimise machine learning models for drug discovery applications, including compound screening, target identification, and lead optimisation. Using PyTorch, TensorFlow, and HuggingFace Apply state-of-the-art techniques such as deep learning, reinforcement learning, and generative models to solve complex biological and chemical problems. … a PhD is preferred within computer science, operational research, computational biology, bioinformatics etc Strong proficiency in Python and experience with ML frameworks (PyTorch, TensorFlow, HuggingFace, etc.) Experience in distributed computing and scalable model training Familiarity with synthetic data generation and data augmentation techniques Experience working with large More ❯
AWS/GCP/Azure) to significantly reduce engineering time and effort. Lead AI-powered automation efforts, integrating LLMs with external APIs (OpenAI, Anthropic, HuggingFace), databases (PostgreSQL, Pinecone, Weaviate, ChromaDB), and business logic to improve operational efficiency. Develop scalable and cost-efficient AI systems, optimizing LLM inference … always seeking new LLM advancements and finding creative ways to apply them in a fast-paced, evolving AI ecosystem using cutting-edge frameworks like HuggingFace, OpenAI API, and retrieval-augmented generation (RAG) techniques. Strong problem-solving mindset, comfortable working autonomously on high-stakes AI engineering projects, pushing More ❯
Excellent communication skills and ability to explain complex technical concepts Experience with containerization (Docker) and orchestration (Kubernetes) Familiarity with modern AI tools and frameworks (HuggingFace, OpenAI, etc.) Nice to have: Experience with generative AI and large language models Contributions to open-source ML projects Published research papers More ❯
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 More ❯
we’re looking for. Technical Skills: Strong proficiency in Python and relevant frameworks/libraries (NumPy, Pandas, Scikit-Learn, TensorFlow/PyTorch, LangChain, LangGraph, HuggingFace, etc.). Experience working with LLMs and AI models in production environments. Experience building RAG-based applications and vector databases Experience with More ❯
in deploying and managing Generative AI models (e.g., GPT, Stable Diffusion, BERT). Proficient in Python and ML libraries such as TensorFlow, PyTorch, or Hugging Face. Skilled in cloud platforms (AWS, GCP, Azure) and managed AI/ML services. Hands-on experience with Docker, Kubernetes, and container orchestration. Expertise More ❯
making systems. NLP Applications : Implement state-of-the-art NLP solutions for sentiment analysis, document processing, and customer interaction enhancements using tools like spaCy, HuggingFace Transformers , and OpenAI APIs. Vector Search and Semantic Retrieval : Build systems utilizing vector databases like Weaviate, Pinecone , and Milvus to enable real More ❯
pipelines, containerisation using Docker, and API development. Familiarity with MLOps and LLMOps practices, along with applied experience using Large Language Models (e.g., OpenAI, Anthropic, HuggingFace) to enhance business solutions. Practical knowledge of interfacing tools such as Streamlit for building interactive data applications and dashboards. Solid experience with More ❯
native Machine Learning platform Extensive experience with programming languages such as Python, Java, Scala etc. Solid experience with ML frameworks such as Pytorch and Huggingface The ability to work in a team, collaborate with others to solve interesting problems that directly affect our customers Demonstrated critical thinking and problem-solving More ❯
ideas and concepts effectively. Ability to work independently and collaboratively. Preferred Skills: Experience building scalable applications with LLMs, using frameworks such as LangChain, LlamaIndex, HuggingFace, etc. Depth of knowledge with RAG implementation and improvements. More ❯
pipelines, containerisation using Docker, and API development. Familiarity with MLOps and LLMOps practices, along with applied experience using Large Language Models (e.g., OpenAI, Anthropic, HuggingFace) to enhance business solutions. Practical knowledge of interfacing tools such as Streamlit for building interactive data applications and dashboards. Solid experience with More ❯
Strong knowledge of Mathematical Statistics, Algorithms & Data Structures, ML Theory Strong knowledge of Python & SQL Experience training & fine-tuning Transformers or Large Language Models (Huggingface Transformers, OpenAI, Llama 2, Langchain) Experience serving Neural Networks in production (PyTorch, ONNX, TorchServe, Triton) Experience developing & maintaining production ML services Experience with ad-hoc More ❯
VectorDBs. Expert programming skills in languages such as Python, Java, or C++, and working knowledge of deep learning frameworks such as TensorFlow, PyTorch, or Hugging Face. Understanding of generative models, such as Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and Transformer models (e.g., GPT, BERT for text). Experience More ❯
intelligence and machine learning and extensive practical experience with it. Expert knowledge and experience with relevant programming languages (incl. Python), frameworks (incl. Pycharm, OpenAI, HuggingFace, Spark, Azure, AWS). Extensive experience with cloud environments (AWS, Azure, GCP). Ability to write highly performant code working with big data. Bachelor’s More ❯
model applications. Proficiency in Python and SQL, with strong skills in data manipulation and analysis. Expertise in AI frameworks such as TensorFlow, PyTorch, and HuggingFace Transformers. Ability to effectively communicate complex AI concepts, especially to non-technical stakeholders. Preferred Qualifications Experience with graph databases and knowledge graphs. More ❯
capabilities (e.g., large language models advanced NLP toolkits) into our integration stack. You will stay current with AI/ML trends (e.g., transformer architectures, HuggingFace, Vertex AI on GCP, Azure Cognitive Services, AWS Sagemaker) and identify opportunities to incorporate new technology for improved efficiency and innovation. You More ❯
and deploying LLM-based solutions in an enterprise setting as a senior/staff scientist. Proficiency in Python and libraries such as TensorFlow, PyTorch, HuggingFace Transformers, and spaCy. Strong understanding of LLM architectures (e.g., GPT, BERT, T5) and experience fine-tuning them for specific tasks. Demonstrable experience More ❯
and deploying LLM-based solutions in an enterprise setting as a senior/staff scientist. Proficiency in Python and libraries such as TensorFlow, PyTorch, HuggingFace Transformers, and spaCy. Strong understanding of LLM architectures (e.g., GPT, BERT, T5) and experience fine-tuning them for specific tasks. Demonstrable experience More ❯
Academic background with a university degree in Computer Science, software engineering, Machine Learning, or a related field. Strong programming skills in Python (PyTorch, TensorFlow, HuggingFace, LangChain, FastAPI, Flask). Good understanding of ML model architecture and LLMs , including how they are trained, fine-tuned, and deployed on More ❯
participate in the upside of an ultra-growth venture. Have fun. Apply if: You have experience with our stack: Python, LlamaIndex/LangChain, PyTorch, HuggingFace, FastAPI, Postgres, SQLAlchemy, Alembic, OpenAI, Docker, Azure, Typescript, React. You have hands-on experience working with LLMs, RAG architectures, NLP, or applying Machine Learning to More ❯
data science with a strong focus on practical AI applications. Deep understanding of generative AI, LLMs, NLP, and machine learning frameworks (e.g., TensorFlow, PyTorch, HuggingFace). Experience with cloud AI services (AWS, Azure, GCP) and AI model deployment. Proficiency in Python, APIs, and AI-driven automation tools. More ❯
models using Amazon SageMaker, with experience managing SageMaker pipelines. Strong understanding of deep learning and machine learning frameworks such as TensorFlow, PyTorch, transformers, NLTK, HuggingFace, or spaCy. Proven experience building end-to-end ML pipelines, including data annotation, data preprocessing, feature engineering, model training, and deployment. Ability More ❯
business workflows. Required Qualifications & Skills Strong experience in AI, NLP, and machine learning algorithms. Proficiency in Python and frameworks such as TensorFlow, PyTorch, or Hugging Face. Hands-on experience with generative AI and LLM fine-tuning . Experience deploying AI applications on Azure (e.g., Azure ML, Azure Functions, Azure More ❯
