/ML Engineers We are looking for a goal oriented and driven AI/ML Engineers with relevant experiences. Key Responsibilities: NeuralNetwork Training : Develop and train advanced neuralnetwork models to meet specific functional requirements. Deployment and Integration : Efficiently deploy these neural … trends. Skills and Qualifications: Minimum 4 years of experience in building AI/ML software. Strong expertise in machine learning and neuralnetwork algorithms. Proficient in programming languages like Python, and libraries such as TensorFlow, PyTorch, NumPy and LangChain Experience with server deployment, cloud computing environments, and More ❯
/ML Engineers We are looking for a goal oriented and driven AI/ML Engineers with relevant experiences. Key Responsibilities: NeuralNetwork Training: Develop and train advanced neuralnetwork models to meet specific functional requirements. Deployment and Integration: Efficiently deploy these neural … trends. Skills and Qualifications: Minimum 4 years of experience in building AI/ML software. Strong expertise in machine learning and neuralnetwork algorithms. Proficient in programming languages like Python, and libraries such as TensorFlow, PyTorch, NumPy and LangChain Experience with server deployment, cloud computing environments, and More ❯
ML tasks. Build and optimize tools for scalable probabilistic inference under memory, latency, and compute constraints. Apply and innovate on methods like Bayesian neuralnetworks , variational autoencoders , diffusion models , and Gaussian processes for modern AI use cases. Collaborate closely with product, engineering, and business teams to build end More ❯
Theory Strong knowledge of Python & SQL Experience training & fine-tuning Transformers or Large Language Models (Huggingface Transformers, OpenAI, Llama 2, Langchain) Experience serving NeuralNetworks in production (PyTorch, ONNX, TorchServe, Triton) Experience developing & maintaining production ML services Experience with ad-hoc analytics, data visualisation, and BI tools (Superset More ❯
Theory Strong knowledge of Python & SQL Experience training & fine-tuning Transformers or Large Language Models (Huggingface Transformers, OpenAI, Llama 2, Langchain) Experience serving NeuralNetworks in production (PyTorch, ONNX, TorchServe, Triton) Experience developing & maintaining production ML services Experience with ad-hoc analytics, data visualisation, and BI tools (Superset More ❯
Manchester, Lancashire, United Kingdom Hybrid / WFH Options
NLP PEOPLE
strong knowledge of ML algorithms, ranging from classical techniques to deep learning methods. Proven experience in training, fine-tuning, and deploying neuralnetwork models using frameworks like PyTorch, with a focus on optimizing performance and scalability for real-world applications. Demonstrated ability to mentor and lead technical More ❯
complex subjects to non-technical stakeholders You are familiar with Terraform , Python , Pandas , and NumPy It is great if you have: Experience with NeuralNetworks/Deep Learning. Experience with information extraction, parsing, and segmentation. Experience with machine learning frameworks ( sklearn ) and ML workflow. Experience with NLP libraries More ❯
Computer Science, Artificial Intelligence, Mathematics, Statistics or related fields. Expert in Python, R, SQL and a range of ML techniques (e.g., random forests, neural nets, reinforcement learning) Track record of delivering high-impact AI projects from concept to production Strong communication skills – able to translate complex insights into More ❯
like Tableau, Spotfire, Power BI etc. Expertise in predictive modelling, including both parametric (e.g. logit/probit) and non-parametric (e.g. random forest, neural net) techniques as well as wider ML techniques like clustering/random forest (desirable). Tech Stack: SQL, Python, R, Tableau, AWS Athena + More ❯
like Tableau, Spotfire, Power BI etc. Expertise in predictive modelling, including both parametric (e.g. logit/probit) and non-parametric (e.g. random forest, neural net) techniques as well as wider ML techniques like clustering/random forest (desirable). Tech Stack: SQL, Python, R, Tableau, AWS Athena + More ❯
numerous and complex variables - Essential Experience in applying machine learning solutions for genomics investigations - Essential Requirement: Experience using machine learning applications (e.g. convolutional neuralnetworks, recurrent neuralnetworks) - Essential Experience of working on externally funded projects - Essential Experience with next generation sequencing (RNA-Seq, DNA-Seq … based on integration of multi-omic data (genome, transcriptome, epigenome) and integrate this novel information in the development of tissue/condition specific regulatory network, with the aim of prioritising variants occurring within those regions based on their predicted impact. They will also lead on the analysis, preparation, and … submission of the associated manuscripts. The successful candidate will develop computational pipelines centered on machine learning applications such as convolutional neuralnetwork to reproducibly handle multi-omic data (genome, transcriptome . click apply for full job details More ❯
Data Science, Computer Science, Mathematics, or a related field. Experience or coursework in machine learning, deep learning, or AI techniques (e.g., supervised learning, neuralnetworks, NLP). Proficiency in Python and libraries like Scikit-learn, TensorFlow, PyTorch, or Hugging Face Transformers. Familiarity with data preprocessing, model evaluation, and More ❯
Data Science, Computer Science, Mathematics, or a related field. Experience or coursework in machine learning, deep learning, or AI techniques (e.g., supervised learning, neuralnetworks, NLP). Proficiency in Python and libraries like Scikit-learn, TensorFlow, PyTorch, or Hugging Face Transformers. Familiarity with data preprocessing, model evaluation, and More ❯
Computer Science, Artificial Intelligence, Mathematics, Statistics or related fields. Expert in Python, R, SQL and a range of ML techniques (e.g., random forests, neural nets, reinforcement learning) A good understanding of the regulatory environment, especially responsible lending (creditworthiness/affordability) Experience in using the latest data science techniques More ❯
like Tableau, Spotfire, Power BI etc. Expertise in predictive modelling, including both parametric (e.g. logit/probit) and non-parametric (e.g. random forest, neural net) techniques as well as wider ML techniques like clustering/random forest (desirable). Tech Stack: SQL, Python, R, Tableau, AWS Athena + More ❯
R, SAS, Matlab, etc.) experience. 5+ years of data scientist experience. Experience with statistical models e.g. multinomial logistic regression. Experience developing neuralnetwork models. PREFERRED QUALIFICATIONS 2+ years of data visualization using AWS QuickSight, Tableau, R Shiny, etc. experience. Experience managing data pipelines. Experience as a leader More ❯
Science teams in an eCommerce or conversion rate optimisation-focused environment is a plus. Hands-on experience with Machine & Deep Learning, AI and NeuralNetworks tools including Python, Spark, Tensor Flow. Competencies across core programming languages including Python, Java, C/C++, R. Ability to work in a More ❯
Cambridge, Cambridgeshire, United Kingdom Hybrid / WFH Options
Adecco
Vision, Deep Learning, Machine Learning, AI, or NLP. * Strong mathematical and analytical skills, including knowledge of statistics and probability. * Experience with neuralnetwork architecture and deep learning techniques. * Proficiency in programming languages such as Python and Java. * Familiarity with big data and distributed computing. * Ability to explore More ❯
Stevenage, Hertfordshire, United Kingdom Hybrid / WFH Options
MBDA Miissle System
Machine Learning for regression and pattern recognition/discovery problems e.g. Gaussian processes, latent variable methods, support vector machines, probabilistic/statistical models, neuralnetworks, Bayesian inference, random-forests, novelty detection, clustering Deep Learning e.g. Deep reinforcement learning, Monte-Carlo tree search, deep regression/classification, deep embeddings More ❯
other container languages A passion for applying tech to solve healthcare challenges. Non-essential skills/nice to have: Experience or understanding of NeuralNetworks Experience with Biotechnology/Bioinformatics Familiarity with AWS, Kubernetes, or RESTful APIs. Exposure to regulated medical software environments. If you are interested, please More ❯
other container languages A passion for applying tech to solve healthcare challenges. Non-essential skills/nice to have: Experience or understanding of NeuralNetworks Experience with Biotechnology/Bioinformatics Familiarity with AWS, Kubernetes, or RESTful APIs. Exposure to regulated medical software environments. If you are interested, please More ❯
Services • Experience with Computer Vision: Kernel, Hardware Accelerator, TVM, or Code-gen • Experience with Deep Learning: C++ or Python, and AI, NeuralNetwork, Tensorflow, PyTorch, MxNET, Llvm, Compiler, CPU, CUDA, Nvidia, TensorRT, TPU, Cluster Management, High Performance Computing, or Optimization Amazon is an equal opportunities employer. We More ❯
a positive. An understanding of machine learning processes and their applications to investments. Ideally, they will be familiar with various algorithms (logistic regression, neuralnetworks) and an understanding of how to implement these in Python. A passion for bringing together investment ideas in an organized framework with the More ❯
analysts, fostering a culture of technical excellence and innovation. Key Skills & Experience Strong expertise in statistical modelling and machine learning techniques (GLMs, GBMs, neuralnetworks, etc.). Experience in pricing or market modelling, preferably in insurance. Proficiency in Python and SQL for data analysis and model development. Hands More ❯
general insurance pricing Experience with some of the following predictive modelling techniques; Logistic Regression, GBMs, Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Neural Nets and Clustering Experience in statistical and data science programming languages (e.g. R, Python, PySpark, SAS, SQL) A good quantitative degree (Mathematics, Statistics, Engineering More ❯