Working with Data Scientists to deploy trained machine learning models into production environments Working with a range of models developed using common frameworks such as Scikit-learn, TensorFlow, or PyTorch Experience with software engineering best practices and developing applications in Python. Technical experience of cloud architecture, security, deployment, and open-source tools ideally with one of the 3 major cloud More ❯
production-grade code and a good understanding of data engineering & MLOps Solid understanding of machine learning concepts, familiarity working with common frameworks such as sci-kit-learn, TensorFlow, or PyTorch Collaborative and humble team player with an ability to work with cross-functional teams, including technical and non-technical stakeholders Passion for learning new skills and staying up-to-date More ❯
how of designing 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 More ❯
Engineering, 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, Hugging Face) 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 Understanding More ❯
Scientific publications in top-tier AI and neuroscience conferences (NeurIPS, ICLR, ICML, AAAI, CVPR, Cosyne, SFN, CNN ecc) or peer reviewed journals Familiarity with deep learning libraries such as Pytorch, Huggingface, Transformers, Accelerator and Diffuser. Hands-on experience in training and fine-tuning generative models like diffusion models or large language models such as GPTs and LLAMAs. Experience with data More ❯
high-throughput data pipelines and APIs using Go, Python, or similar. Hands-on NLP experience with both pre-built services (e.g., AWS Comprehend) and custom transformer models (Hugging Face, PyTorch, TensorFlow) with a strong grounding in evaluating NLP models using classification and ranking metrics, and experience running A/B or offline benchmarks. Proficient with MLOps and training infrastructure (MLflow More ❯
generative 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, Hugging Face) 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 successful … experience in machine learning and/or data science roles Solid understanding of MLOps and production deployment practices Experience with Python and core ML libraries (e.g., Scikit-learn, Pandas, PyTorch, TensorFlow) Familiarity with cloud platforms and data infrastructure (e.g., AWS/GCP/Azure, SQL, ELT tools) Understanding of ethical frameworks, explainability, and governance in AI Engaging & Adaptable Communication: Ability More ❯
innovative improvements. Qualifications: Proven experience as an MLOps engineer or similar role with a focus on 3D applications Strong programming skills in Python, and familiarity with ML frameworks (TensorFlow, PyTorch, etc.) Expertise in 3D reconstruction and rendering Experience with cloud platforms (AWS, GCP, Azure) and container orchestration (Kubernetes, Docker) Excellent problem-solving skills and ability to work cross-functionally in More ❯
reinforcement learning and imitation learning Contribute to creating multi-robot systems and cross-embodiment learning techniques Drive innovation by publishing research and attending top conferences Engineer Background: Expertise in PyTorch or TensorFlow, distributed computing, and multi-GPU training Robotics experience, particularly in reinforcement/imitation learning Experience in cloud infrastructure (AWS, GCP, or Azure) and containerization Ability to translate research More ❯
reinforcement learning and imitation learning Contribute to creating multi-robot systems and cross-embodiment learning techniques Drive innovation by publishing research and attending top conferences Engineer Background: Expertise in PyTorch or TensorFlow, distributed computing, and multi-GPU training Robotics experience, particularly in reinforcement/imitation learning Experience in cloud infrastructure (AWS, GCP, or Azure) and containerization Ability to translate research More ❯
London, South East, England, United Kingdom Hybrid / WFH Options
Opus Recruitment Solutions Ltd
DeepCell Integrating 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, Hugging Face 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 ❯
City of London, London, United Kingdom Hybrid / WFH Options
Robert Half
GCP/AWS/Azure, MySQL, Firestore, Docker/Kubernetes, CI/CD, IaC • Champion security best practices in a regulated space • Explore AI & machine learning (LLMs, LangChain, TensorFlow, PyTorch) What you’ll bring: • Strong React & Python (FastAPI/Django/Flask) experience • Solid API design & database skills • Start-up or scale-up mindset, adaptable and hands-on • Passion for More ❯
GCP/AWS/Azure, MySQL, Firestore, Docker/Kubernetes, CI/CD, IaC • Champion security best practices in a regulated space • Explore AI & machine learning (LLMs, LangChain, TensorFlow, PyTorch) What you’ll bring: • Strong React & Python (FastAPI/Django/Flask) experience • Solid API design & database skills • Start-up or scale-up mindset, adaptable and hands-on • Passion for More ❯
software engineering and machine learning. Proven track record of deploying ML systems in production. A strong understanding of Machine Learning fundamentals. Strong experience with deep learning frameworks such as PyTorch or TensorFlow. Experience with training diffusion, transformer, or generative video models. Proficiency in Python. Experience building and maintaining scalable infrastructure (AWS, GCP, or custom solutions). Familiarity with CI/ More ❯
Central London, London, United Kingdom Hybrid / WFH Options
Singular Recruitment
statistical analysis and proven experience applying a range of machine learning techniques to solve business problems (e.g., regression, classification, clustering, time-series forecasting). Practical experience with Keras or PyTorch is required. Full-Stack Deployment: Demonstrable experience taking models to production, including building and deploying APIs with FastAPI and using Vertex AI for ML workflows. Visualization & Communication: Ability to create More ❯
engineering teams Deep experience deploying ML models into production environments Proficiency in designing scalable data pipelines and real-time inference systems Understanding of modern ML tooling and frameworks (e.g., PyTorch, TensorFlow, MLflow, AWS SageMaker) Strong cross-functional collaboration skills, particularly with data science and product teams Clear communication and an ability to prioritize for both experimentation and reliability Bonus Familiarity More ❯
engineering teams Deep experience deploying ML models into production environments Proficiency in designing scalable data pipelines and real-time inference systems Understanding of modern ML tooling and frameworks (e.g., PyTorch, TensorFlow, MLflow, AWS SageMaker) Strong cross-functional collaboration skills, particularly with data science and product teams Clear communication and an ability to prioritize for both experimentation and reliability Bonus Familiarity More ❯
innovating for continual improvement Provide primary operational support and engineering for multiple large-scale distributed software applications ️ Is this you? You have professional experience with: Model training Huggingface Transformers Pytorch vLLM TensorRT Infrastructure as code tools like Terraform Scripting languages such as Python or Bash Cloud platforms such as Google Cloud, AWS or Azure Git and GitHub workflows Tracing and More ❯
What Were Looking For: 02 years of experience in machine learning, applied AI, or data science (personal projects and internships count!) Solid Python skills and familiarity with libraries like PyTorch, TensorFlow, or Hugging Face Transformers Understanding of basic ML concepts and data preprocessing techniques Interest in NLP, unstructured data, and information extraction Eagerness to learn, take feedback, and contribute to More ❯
time-series or physiological data Strong foundation in signal processing and time-series modeling (e.g., deep learning, classical ML, anomaly detection) Proficient in Python and ML frameworks such as PyTorch or TensorFlow Familiarity with FDA regulatory pathways for medical software (e.g., 510(k), De Novo), and standards like IEC 62304 or ISO 13485 Experience with MLOps practices and model versioning More ❯
designing applications powered by Large Language Models and leading their implementation. Experience working with recommendation engines, data pipelines, or distributed machine learning. Experience with deep learning frameworks (e.g., TensorFlow, PyTorch, XGBoost). Knowledge of data warehousing concepts, including data warehouse technical architectures, infrastructure components, ETL/ELT and reporting/analytic tools and environments (e.g., Apache Beam, Hadoop, Spark, Pig More ❯
Hands-on experience with MLOps and AIOps infrastructure and tooling. Proficient in problem-solving and analytical reasoning. Exceptional communication and collaboration skills. Experience with ML frameworks such as TensorFlow, PyTorch, TensorRT, or ONNX. Experience with Large Language Models, including RAG and fine-tuning techniques. Familiarity with compute infrastructure necessary to support operating AI and ML technology. For more information about More ❯
Profile Essential skills: Bachelor/Master's/PhD or equivalent experience in Machine Learning, Computer Science, Maths, Data Science, or related field. Proficiency in deep learning frameworks like PyTorch/JAX. Strong Python software development skills (nice to have C other languages). Familiar with deep learning fundamentals: models, optimisation, evaluation and scaling. Capable of designing, executing and reporting More ❯
current with emerging techniques. You are experienced in multivariate testing, mentoring junior scientists, and leading technical decisions. You are proficient in Python, Java, Scala, and ML frameworks (e.g., TensorFlow, PyTorch ), with experience in cloud platforms (AWS), big data (Spark), and deployment tools (Kubernetes, Airflow, Docker). Accommodation requests If you need assistance with any part of the application or recruiting More ❯
Profile Essential Skills Bachelor/Master's/PhD or equivalent experience in Machine Learning, Computer Science, Maths, Data Science, or related field. Proficiency in deep learning frameworks like PyTorch/JAX. Strong Python software development skills (nice to have C other languages). Familiar with deep learning fundamentals: models, optimisation, evaluation and scaling. Capable of designing, executing and reporting More ❯