computational linguistics are highly desirable, either from a research academic or commercial perspective. Proficiency in Python and ML libraries such as Hugging Face, PyTorch, TensorFlow, and Scikit-learn. Experience deploying AI solutions into production environments using AWS/GCP/Azure. Hands-on with MLOps, CI/CD for More ❯
computational linguistics are highly desirable, either from a research academic or commercial perspective. Proficiency in Python and ML libraries such as Hugging Face, PyTorch, TensorFlow, and Scikit-learn. Experience deploying AI solutions into production environments using AWS/GCP/Azure. Hands-on with MLOps, CI/CD for More ❯
related field. Proficiency in programming languages such as Python, R, or Java. Strong understanding of mathematics and statistics. Experience with machine learning frameworks like TensorFlow, Keras, or PyTorch. Knowledge of data analysis and visualization tools (e.g., Pandas, NumPy, Matplotlib). Familiarity with big data technologies (e.g., Hadoop, Spark). More ❯
performance. Requirements: Bachelor’s, Master’s, or PhD in Computer Science, Data Science, Bioinformatics, or related field. Proficiency in Python and ML frameworks (e.g., TensorFlow, PyTorch). Experience with bioinformatics tools (e.g., Biopython, RDKit). Strong knowledge of statistical models, deep learning, and data preprocessing. Familiarity with cloud platforms More ❯
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 More ❯
end software solutions. Expertise in at least one relevant programming language (e.g., Python, Java, or C++) Familiarity with at least one AI framework (e.g., TensorFlow, PyTorch, or Scikit-learn). Knowledge of AI algorithms, machine learning techniques, and data analytics methodologies, with an emphasis on engineering applications. Understanding of More ❯
Able to explain complex ideas simply, and work well in cross-functional teams Tech You’ll Work With ML & Data Science Python (primary language) TensorFlow, PyTorch, or Keras NumPy, pandas Data pipelines (Azure Data Factory, Airflow, etc.) Applied ML: NLP, CV, transformers, GANs, time series, etc. Engineering & Cloud Azure More ❯
popular augmentation techniques Able to apply machine learning to real-life problems Vision Transformers, DeepLabv3, SegFormer, etc.Python, Scikit-Learn, NumPy, Pandas and PyTorch/TensorFlow/Keras Thrive in a cross-functional working environment Possess a clear passion for data science beyond the day job Nice-to-haves: NLP More ❯
solutions Implement testing, monitoring, and performance optimisation of ML systems Contribute to architectural discussions and promote engineering best practices Technical Environment: Python, PyTorch or TensorFlow AWS (including SageMaker, S3, Lambda) or Azure ML Docker, Kubernetes, Airflow CI/CD tools (e.g. GitHub Actions, Jenkins) MLflow or similar frameworks Required More ❯
and deploying machine learning models and algorithms in real-world applications. - Strong proficiency in Python programming and popular machine learning libraries/frameworks (e.g., TensorFlow, PyTorch, scikit-learn). - Deep understanding of machine learning concepts and techniques, including supervised/unsupervised learning, deep learning, reinforcement learning, etc. - Strong communication More ❯
Looking For: 2+ years in AI/ML engineering or backend software roles with ML components. Proficiency in Python and frameworks like PyTorch/TensorFlow, Scikit-learn. Experience deploying models with Docker, Kubernetes, or serverless architectures. Solid grasp of MLOps workflows, versioning, and cloud automation. Strong foundations in algorithms More ❯
Computer Science or a related field. Proven experience designing or delivering large-scale pricing, AI or recommendation systems. Deep technical knowledge of ML frameworks (TensorFlow, PyTorch), cloud platforms (AWS, GCP, Azure), and big data tools (Spark, Hadoop). Demonstrated success in building business-critical, real-time algorithmic solutions. Strong More ❯
vision challenges Knowledgeable about key architectures like Vision Transformers, DeepLabv3, and SegFormer Proficient in Python and ML tools, including Scikit-Learn, NumPy, Pandas, PyTorch, TensorFlow, or Keras Capable of applying machine learning to solve real-world problems Please apply via the link for immediate consideration More ❯
Looking For Most importantly, you must hold an active UKIC DV Clearance Strong experience in MLOps or ML Engineering Familiarity with ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn ) Strong proficiency in Python for production systems Proficient in Python and modern DevOps/MLOps tools Experience with cloud platforms and More ❯
real-world AI applications. Required: 4+ years in AI/ML engineering with hands-on Databricks experience . Strong Python skills with experience in TensorFlow, PyTorch, or Scikit-learn. Cloud experience ( Azure preferred, or AWS/GCP). Certifications in Databricks or Azure (e.g., Databricks ML Professional). Why More ❯
to work with cross-functional teams. Ability to communicate effectively and explain technical/complex concepts to non-technical stakeholders Experienced in Python, SQL, Tensorflow and a cloud platform Our client is an exciting phase of their growth and as a Head of Data Science you will have the More ❯
development, with a strong portfolio of projects. Proficiency in programming languages such as Python, R, or Java. Experience with AI frameworks and libraries (e.g., TensorFlow, PyTorch). Strong problem-solving skills and the ability to work in a fast-paced environment. Excellent communication and teamwork abilities. What We Offer More ❯
projects Strong track record of delivering machine learning or AI projects end-to-end Hands-on skills in Python, with frameworks like Scikit-learn, TensorFlow, PyTorch, or PySpark Deep understanding of data science best practices, including MLOps Strong stakeholder communication skills—able to translate complex insights into business impact More ❯
projects Strong track record of delivering machine learning or AI projects end-to-end Hands-on skills in Python, with frameworks like Scikit-learn, TensorFlow, PyTorch, or PySpark Deep understanding of data science best practices, including MLOps Strong stakeholder communication skills—able to translate complex insights into business impact More ❯
Cambridge, Cambridgeshire, UK Hybrid / WFH Options
Seer
an experienced and talented Senior AI Scientist. Experience Required: Deep Learning experience, preferably with LLMs & NLP. Strong knowledge and experience with Python/Pytorch, Tensorflow and other data science libraries. Experienced with cloud platforms, e.g AWS or GCP is considered a plus. The role is hybrid in Cambridge, UK More ❯
engineers. About You Practical knowledge of multimodal AI - LLM and VLM Excellent knowledge of machine learning and relevant frameworks as PyTorch and/or Tensorflow A strong research focus with first author publications in reputable ML/AI conferences/journals PhD student or graduate in either computer science More ❯
FAISS, Weaviate, Pinecone, ChromaDB, OpenSearch Required skills & experience: 3–5+ years of experience in ML engineering and software development Deep Python proficiency, with PyTorch, TensorFlow or Hugging Face Proven experience with LLMs, RAG, and deploying cloud-native AI on AWS Strong full-stack skills (React, TypeScript, Node.js) and API More ❯
Abingdon on Thames, Oxfordshire, UK Hybrid / WFH Options
Reqiva
with robotics, embedded systems, or IoT or edge devices. Experience with software engineering for manufacturing on industrial control. Familiarity with machine learning libraries (e.g., TensorFlow, PyTorch). Background in AI algorithms and hardware-accelerated computing. This is an expanding company who will give you the opportunity to shape software More ❯
/Selenium) Familiarity with modern DevOps practices (CI/CD pipelines, Docker, etc) Nice to have but not essential: Exposure to ML frameworks like TensorFlow or PyTorch (not essential) Experience in e-commerce or retail tech environments This is a hybrid role 2 days a week in office, so More ❯
