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). Experience building and maintaining ML pipelines and data pipelines. Proficiency in model deployment techniques (e.g., serving models … for ML, reproducibility. Experience with Docker and container orchestration (e.g., Kubernetes). Preferred Skills: Experience with feature stores (e.g., Feast, Tecton). Knowledge of distributed training (e.g., Horovod, distributed PyTorch). Familiarity with big data tools (e.g., Spark, Hadoop, Beam). Understanding of NLP, computer vision, or time series analysis techniques. Knowledge of experiment tracking tools (e.g., MLflow, Weights & Biases More ❯
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). Experience building and maintaining ML pipelines and data pipelines. Proficiency in model deployment techniques (e.g., serving models … for ML, reproducibility. Experience with Docker and container orchestration (e.g., Kubernetes). Preferred Skills: Experience with feature stores (e.g., Feast, Tecton). Knowledge of distributed training (e.g., Horovod, distributed PyTorch). Familiarity with big data tools (e.g., Spark, Hadoop, Beam). Understanding of NLP, computer vision, or time series analysis techniques. Knowledge of experiment tracking tools (e.g., MLflow, Weights & Biases More ❯
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). Experience building and maintaining ML pipelines and data pipelines. Proficiency in model deployment techniques (e.g., serving models … for ML, reproducibility. Experience with Docker and container orchestration (e.g., Kubernetes). Preferred Skills: Experience with feature stores (e.g., Feast, Tecton). Knowledge of distributed training (e.g., Horovod, distributed PyTorch). Familiarity with big data tools (e.g., Spark, Hadoop, Beam). Understanding of NLP, computer vision, or time series analysis techniques. Knowledge of experiment tracking tools (e.g., MLflow, Weights & Biases More ❯
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). Experience building and maintaining ML pipelines and data pipelines. Proficiency in model deployment techniques (e.g., serving models … for ML, reproducibility. Experience with Docker and container orchestration (e.g., Kubernetes). Preferred Skills: Experience with feature stores (e.g., Feast, Tecton). Knowledge of distributed training (e.g., Horovod, distributed PyTorch). Familiarity with big data tools (e.g., Spark, Hadoop, Beam). Understanding of NLP, computer vision, or time series analysis techniques. Knowledge of experiment tracking tools (e.g., MLflow, Weights & Biases More ❯
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). Experience building and maintaining ML pipelines and data pipelines. Proficiency in model deployment techniques (e.g., serving models … for ML, reproducibility. Experience with Docker and container orchestration (e.g., Kubernetes). Preferred Skills: Experience with feature stores (e.g., Feast, Tecton). Knowledge of distributed training (e.g., Horovod, distributed PyTorch). Familiarity with big data tools (e.g., Spark, Hadoop, Beam). Understanding of NLP, computer vision, or time series analysis techniques. Knowledge of experiment tracking tools (e.g., MLflow, Weights & Biases More ❯
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). Experience building and maintaining ML pipelines and data pipelines. Proficiency in model deployment techniques (e.g., serving models … for ML, reproducibility. Experience with Docker and container orchestration (e.g., Kubernetes). Preferred Skills: Experience with feature stores (e.g., Feast, Tecton). Knowledge of distributed training (e.g., Horovod, distributed PyTorch). Familiarity with big data tools (e.g., Spark, Hadoop, Beam). Understanding of NLP, computer vision, or time series analysis techniques. Knowledge of experiment tracking tools (e.g., MLflow, Weights & Biases More ❯
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). Experience building and maintaining ML pipelines and data pipelines. Proficiency in model deployment techniques (e.g., serving models … for ML, reproducibility. Experience with Docker and container orchestration (e.g., Kubernetes). Preferred Skills: Experience with feature stores (e.g., Feast, Tecton). Knowledge of distributed training (e.g., Horovod, distributed PyTorch). Familiarity with big data tools (e.g., Spark, Hadoop, Beam). Understanding of NLP, computer vision, or time series analysis techniques. Knowledge of experiment tracking tools (e.g., MLflow, Weights & Biases More ❯
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). Experience building and maintaining ML pipelines and data pipelines. Proficiency in model deployment techniques (e.g., serving models … for ML, reproducibility. Experience with Docker and container orchestration (e.g., Kubernetes). Preferred Skills: Experience with feature stores (e.g., Feast, Tecton). Knowledge of distributed training (e.g., Horovod, distributed PyTorch). Familiarity with big data tools (e.g., Spark, Hadoop, Beam). Understanding of NLP, computer vision, or time series analysis techniques. Knowledge of experiment tracking tools (e.g., MLflow, Weights & Biases More ❯
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). Experience building and maintaining ML pipelines and data pipelines. Proficiency in model deployment techniques (e.g., serving models … for ML, reproducibility. Experience with Docker and container orchestration (e.g., Kubernetes). Preferred Skills: Experience with feature stores (e.g., Feast, Tecton). Knowledge of distributed training (e.g., Horovod, distributed PyTorch). Familiarity with big data tools (e.g., Spark, Hadoop, Beam). Understanding of NLP, computer vision, or time series analysis techniques. Knowledge of experiment tracking tools (e.g., MLflow, Weights & Biases More ❯
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). Experience building and maintaining ML pipelines and data pipelines. Proficiency in model deployment techniques (e.g., serving models … for ML, reproducibility. Experience with Docker and container orchestration (e.g., Kubernetes). Preferred Skills: Experience with feature stores (e.g., Feast, Tecton). Knowledge of distributed training (e.g., Horovod, distributed PyTorch). Familiarity with big data tools (e.g., Spark, Hadoop, Beam). Understanding of NLP, computer vision, or time series analysis techniques. Knowledge of experiment tracking tools (e.g., MLflow, Weights & Biases More ❯
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). Experience building and maintaining ML pipelines and data pipelines. Proficiency in model deployment techniques (e.g., serving models … for ML, reproducibility. Experience with Docker and container orchestration (e.g., Kubernetes). Preferred Skills: Experience with feature stores (e.g., Feast, Tecton). Knowledge of distributed training (e.g., Horovod, distributed PyTorch). Familiarity with big data tools (e.g., Spark, Hadoop, Beam). Understanding of NLP, computer vision, or time series analysis techniques. Knowledge of experiment tracking tools (e.g., MLflow, Weights & Biases More ❯
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). Experience building and maintaining ML pipelines and data pipelines. Proficiency in model deployment techniques (e.g., serving models … for ML, reproducibility. Experience with Docker and container orchestration (e.g., Kubernetes). Preferred Skills: Experience with feature stores (e.g., Feast, Tecton). Knowledge of distributed training (e.g., Horovod, distributed PyTorch). Familiarity with big data tools (e.g., Spark, Hadoop, Beam). Understanding of NLP, computer vision, or time series analysis techniques. Knowledge of experiment tracking tools (e.g., MLflow, Weights & Biases More ❯
data handling, model training, and evaluation. Solid understanding of software engineering practices, particularly in the context of ML development. Hands-on experience with Python and ML libraries such as PyTorch, TensorFlow, and Scikit-learn. Familiarity with tools like Git, Docker, and cloud platforms (e.g., AWS, GCP, Azure). Qualifications (Preferred for Senior Roles) Expertise in advanced ML areas such as … Agency and is an equal opportunities employer. We are on the client's supplier list for this role. Keywords AI Research, Machine Learning Engineer, NLP, Computer Vision, Deep Learning, PyTorch, TensorFlow, LLMs, Transformers, GANs, Reinforcement Learning, Data Science, Python, Cambridge AI Jobs, Applied AI, Research Scientist, Artificial Intelligence, ML Research, AI Innovation More ❯
years of experience in AI/ML development Strong understanding of AI/ML algorithms and techniques, including LLMs, GenAI, and automated AI systems. Machine learning frameworks (e.g., TensorFlow, PyTorch) Proficiency in Python, R, or other relevant programming languages. Experience with data analysis and visualization tools (e.g., Matplotlib, Seaborn, Tableau). Ability to work independently and lead projects from inception More ❯
years of experience in AI/ML development Strong understanding of AI/ML algorithms and techniques, including LLMs, GenAI, and automated AI systems. Machine learning frameworks (e.g., TensorFlow, PyTorch) Proficiency in Python, R, or other relevant programming languages. Experience with data analysis and visualization tools (e.g., Matplotlib, Seaborn, Tableau). Ability to work independently and lead projects from inception More ❯
watford, hertfordshire, east anglia, united kingdom
Cognitive Group | Part of the Focus Cloud Group
years of experience in AI/ML development Strong understanding of AI/ML algorithms and techniques, including LLMs, GenAI, and automated AI systems. Machine learning frameworks (e.g., TensorFlow, PyTorch) Proficiency in Python, R, or other relevant programming languages. Experience with data analysis and visualization tools (e.g., Matplotlib, Seaborn, Tableau). Ability to work independently and lead projects from inception More ❯
St Albans, England, United Kingdom Hybrid / WFH Options
Be Technology
systems meet key business objectives. Stay informed on advancements in AI and integrate the latest technologies into solutions. Key Skills & Experience: Strong programming skills in Python (experience with TensorFlow, PyTorch, or similar frameworks). Expertise in deploying models on cloud platforms (Azure) or containerised environments (Docker, Kubernetes). Proficiency in machine learning algorithms and advanced AI techniques, including transformer-based More ❯
Stevenage, England, United Kingdom Hybrid / WFH Options
Capgemini
/ML development and data science. • Strong understanding of AI/ML algorithms and techniques, including LLMs, GenAI, and automated AI systems. • Experience with machine learning frameworks (e.g., TensorFlow, PyTorch) and data science libraries (e.g., NumPy, pandas, scikit-learn). • Proficiency in Python, R, or other relevant programming languages. • Proficiency in working with large datasets, data wrangling, and data preprocessing. More ❯
/ML development and data science. Strong understanding of AI/ML algorithms and techniques, including LLMs, GenAI, and automated AI systems. Experience with machine learning frameworks (e.g., TensorFlow, PyTorch) and data science libraries (e.g., NumPy, pandas, scikit-learn). Proficiency in Python, R, or other relevant programming languages. Proficiency in working with large datasets, data wrangling, and data preprocessing. More ❯
Cambridge, England, United Kingdom Hybrid / WFH Options
ZipRecruiter
architect or technical lead with systems-level experience Proven track record of delivering AI solutions for complex scientific problems Experience with machine learning algorithms, deep learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn, spaCY), and data processing techniques. Demonstrated experience in developing and deploying machine learning models in production environments. Experience with AI Cloud Platforms (AWS SageMaker, Azure ML, or GCP More ❯
field. Strong programming skills with a solid understanding of algorithms and data structures. Proficiency in Python with hands-on experience using open-source ML frameworks such as scikit-learn, PyTorch, TensorFlow, or Keras. Extensive experience with Machine Learning and Deep Learning models (e.g., tree-based methods, CNNs, Transformers) and developing robust, production-ready ML systems. Strong communication skills, with the More ❯
experience in AI/ML development. Strong understanding of AI/ML algorithms and techniques, including LLMs, GenAI, and automated AI systems. Experience with machine learning frameworks (e.g., TensorFlow, PyTorch). Must Have: Proficiency in Python, R, or other relevant programming languages. Proficiency in working with large datasets, data wrangling, and data preprocessing. Ability to work independently and lead projects More ❯
sequential (e.g. sensor time-series) data and decision-making post PhD. Experience in software development for proof of concept in Python. Experience with machine and deep learning frameworks: TensorFlow, Pytorch, scikit-learn, etc. Of particular interest are candidates with experience in one or more of the following domains: RF communications and CEMA Electronic or Electromagnetic Warfare (EW) Tracking and sensor More ❯
Extensive prior experience exploring and testing large language model behaviour, prompting and building products with language models. Expert knowledge of Python and advanced ML/LLM frameworks (e.g., TensorFlow, PyTorch, LangChain, LlamaIndex, etc). Deep understanding of agentic AI concepts and frameworks (e.g., agentic design patterns, multi-agent systems, reinforcement learning) and their applications in healthcare. Previous experience of training More ❯
Saffron Walden, England, United Kingdom Hybrid / WFH Options
Wellcome Sanger Institute
Do you want to help us improve human health and understand life on Earth? Make your mark by shaping the future to enable or deliver life-changing science to solve some of humanity’s greatest challenges. We seek a Senior More ❯