architect high-quality software solutions. Develop IT solutions using Python and related libraries for AI applications. Build scalable data pipelines utilizing technologies like Pandas, NumPy, or Spark. Apply Agile and DevOps practices to deliver effective solutions. Understand and translate business requirements into technical specifications. Identify opportunities for enhancing DevOps processes More ❯
Woking, England, United Kingdom Hybrid / WFH Options
JR United Kingdom
AI/ML, with at least 1 year focused on Generative AI and NLP. Strong programming skills in Python; proficient in libraries such as NumPy, Pandas, scikit-learn, PyTorch, TensorFlow. Proven experience building and scaling GenAI applications in production. Expertise in LLM architectures (OpenAI, LLaMA, Mistral, etc.) and RAG implementation. More ❯
Guildford, England, United Kingdom Hybrid / WFH Options
JR United Kingdom
AI/ML, with at least 1 year focused on Generative AI and NLP. Strong programming skills in Python; proficient in libraries such as NumPy, Pandas, scikit-learn, PyTorch, TensorFlow. Proven experience building and scaling GenAI applications in production. Expertise in LLM architectures (OpenAI, LLaMA, Mistral, etc.) and RAG implementation. More ❯
Effective communication and teamwork with data scientists and developers are crucial. Proficiency in Python and SQL; experience with libraries such as SciKit Learn, Pandas, Numpy is highly desirable. Experience with deep learning frameworks like Pytorch or TensorFlow. Understanding of the full data science project lifecycle, from problem definition to data More ❯
years of professional experience in machine learning engineering. 2+ years of leadership or technical mentoring experience. Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning … . Familiarity with reinforcement learning or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯
