251 to 275 of 426 Permanent TensorFlow Jobs

and implementing AI solutions in complex enterprise environments Experience in all architecture domains:- application, data, cloud ( AWS) and technology with expertise with AI, Gen Ai and ML frameworks (e.g., TensorFlow, PyTorch, AWS Sagemaker, AWS Bedrock, OpenAI). Strong experience of AI services and AI lifecycle and model training Proficiency in backend and frontend technologies such as .NET Core, Node.js More ❯

evidenced by publications and preprints. Strong breadth and expertise in Statistical analysis, machine learning, data visualization, programming (Python, R, etc.), data cleaning and data manipulation. Tools: Python, R, SQL, TensorFlow, Scikit-learn, Tableau, Power BI. Ability to generate high quality ideas and be self-driven to explore. Strong experience in programming and comfortable modifying existing code-base. Experience with More ❯

or related fields Relevant experience in delivery of AI design, build, deployment or management Proficiency or certification in Microsoft Office tools, as well as relevant technologies such as Python, TensorFlow, Jupiter Notebook, Spark, Azure Cloud, Git, Docker and/or any other relevant technologies Strong analytical and problem-solving skills, with the ability to work on complex projects and More ❯

learning models, including Gradient Boosting Machines (GBMs), Neural Networks and Large language models (LLMs). Hands-on experience with popular machine learning libraries such as Scikit-learn, XGBoost, LightGBM, TensorFlow, or PyTorch. Knowledge of AWS products and services including Sagemaker. Deep knowledge of Microsoft Excel in a commercial setting. You enjoy being Agile - you should be happy working with More ❯

from pipelining to model deployment. Experience with some of the following tools and technologies (or an eagerness to learn): Python and its data science ecosystem (e.g., pandas, scikit-learn, TensorFlow/PyTorch). Statistical methods and machine learning (e.g., A/B testing, model validation). Data pipelining tools like SQL, dbt, BigQuery, or Spark. A strong communicator with More ❯

practises across multiple teams. Demonstrable experience designing and building AI-based solutions and/or AI platforms at scale. Familiarity with AI/ML tools, frameworks, and platforms (e.g., TensorFlow, PyTorch, ML Flow, Data Bricks Azure/AWS/GCP AI services). Track record of delivering production-grade AI applications or integrating AI capabilities into existing platforms. Demonstrable More ❯

AI research and development, with a proven track record in leading complex projects. Experience with data enrichment and building knowledge bases to support AI systems. Advanced proficiency in PyTorch, TensorFlow, or Jax, and programming languages (e.g., Python, R, Java). Plus: publications in leading peer-reviewed journals and conferences. Plus: prior experience in the energy sector. Kraken is a More ❯

coupling, secure computing, monitoring and operational data analytics, mathematical optimisation, containers, compilers, or application optimisation. You should have: A good working knowledge of AI/ML frameworks, at least TensorFlow and PyTorch, as well as the data preparation, handling, and lineage control, as well as model deployment, in particular in a distributed environment. At least a B.Sc. equivalent in More ❯

in a relevant discipline Strong background in AI/ML and/or statistical signal processing applied to time-series or sequential data Proficiency in Python with experience using TensorFlow, PyTorch, scikit-learn, or similar ML frameworks Experience leading R&D projects and mentoring early-career researchers Ability to work independently or within collaborative team Reference: AMC/DRI More ❯

and translate business needs into technical solutions. Requirements At least 3 years of experience in applied machine learning and deploying production models. Proficiency in Python, SQL, and frameworks like TensorFlow, PyTorch, or scikit-learn. Experience with AWS services and Databricks; understanding of ML Ops is highly beneficial. Ability to adapt quickly to new tools and deliver scalable solutions independently. More ❯

Publish research and engage with academic partners What You'll Bring: PhD or equivalent experience in AI/ML or signal processing Proficiency in Python and ML frameworks (PyTorch, TensorFlow, scikit-learn) Strong experience with time-series data, decision-making models, or sensor fusion A track record of innovation and delivering complex R&D Preferred Expertise: RF comms, radar More ❯

to deliver value. Write high-quality Python code following best practices. Continuously research and apply new tools, techniques, and technologies. Experience with: Cloud deployment,Neural networks and libraries like TensorFlow, XGBoost, CatBoost, SKlearn, API development, SQL,CI/CD, DevOps, or MLOps pipelines Experience with: Strong hands-on experience or genuine interest in data science and analytics. Proficiency in More ❯

processing actions, performing analysis, and assessing model performance. • Demonstrated professional or academic experience using Python or R. • Demonstrated professional or academic experience with deep learning frameworks such as PyTorch, Tensorflow, or Keras. (KEY EXPERIENCE FOR CUSTOMER) • Demonstrated professional or academic experience and proficiency with SQL to include using common table expressions, set operations, aggregated functions and nested subqueries. • Demonstrated More ❯

with 4+ years post-PhD experience in AI/ML research. Proven success leading R&D teams and securing funding. Strong Python programming skills and experience with ML frameworks (TensorFlow, PyTorch). Expertise in NLP, knowledge graphs, and/or graph machine learning. Desirable: experience with tools like PyTorch-Geometric, Neo4j, SQL/Cypher, or semantic reasoning. Role: AI More ❯

The Tech Stack AI/ML : Multi-agent frameworks, fine-tuning, reinforcement learning, advanced RAG Platform : AWS serverless, event-driven architecture, microservices Languages : Python, with modern ML libraries (PyTorch, TensorFlow) What They're Looking For 5+ years developing AI/ML systems beyond basic integration Deep understanding of agent architectures and distributed AI systems Computer science fundamentals - algorithms, system More ❯

Proven experience as a Data Scientist, ideally in a government, defence, or security environment. Strong programming skills in Python or R, including experience with libraries such as scikit-learn, TensorFlow, or PyTorch. Solid understanding of statistical modelling, machine learning, and data mining techniques. Experience with SQL and working with large-scale databases. Familiarity with data visualisation tools (e.g., Power More ❯

and ML techniques. Proven ability to extract insights from documents using tools like Apache Tika or PDFMiner. Proficiency in Python and/or R, with hands-on experience using TensorFlow, PyTorch, or similar frameworks. Ability to produce visualizations and qualitative analysis that clearly communicate technical insights. Comfort working with both structured and unstructured datasets in high-stakes environments. Bonus More ❯

AI-driven user personalization for visually impaired individuals Develop AI-powered accessibility solutions Ensure compliance with data privacy and ethical AI guidelines Essential: Machine learning & deep learning - Proficiency in TensorFlow (2.x), PyTorch, Scikit-Learn Strong skills in Python, experience with R or JavaScript is a plus Experience with Health data processing - HER, FHIR, Wearable sensor data Knowledge of transformer More ❯

post-PhD experience applying AI/ML and/or statistical signal processing to sequential or time-series data Strong Python development skills with experience in ML libraries (e.g., TensorFlow, PyTorch, scikit-learn) Ability to lead and deliver research programmes independently and in teams Desirable Experience (one or more of the following): RF communications or electronic warfare (EW) Radar More ❯

versioning in compliant environments. Preferred Qualifications: Experience building ML models with wearable data (e.g., continuous heart rate, motion, respiration). Exposure to embedded AI or edge model deployment (e.g., TensorFlow Lite, Core ML, ONNX). Knowledge of healthcare data privacy and security (e.g., HIPAA, GDPR). Familiarity with GMLP (Good Machine Learning Practice) and clinical evaluation frameworks. #J More ❯

4+ years of post-doctoral or industry experience. Proven experience leading R&D teams (5+ people) and securing funding. Strong Python development skills, with experience using ML frameworks like TensorFlow or PyTorch. Expertise in at least one of the following areas: Graph Machine Learning (predictive, causal, or neuro-symbolic) NLP (text mining, entity linking, information extraction) Applications of LLMs More ❯

to defence or government customers Deep understanding of knowledge graphs, text mining, NLP, and/or graph neural networks Strong Python development skills and proficiency with ML frameworks (PyTorch, TensorFlow) Proven experience applying ML to real-world problems and securing R&D funding (e.g. Dstl, EPSRC) Excellent communication skills with ability to engage technical and non-technical stakeholders Desirable More ❯

versioning in compliant environments. Preferred Qualifications: Experience building ML models with wearable data (e.g., continuous heart rate, motion, respiration). Exposure to embedded AI or edge model deployment (e.g., TensorFlow Lite, Core ML, ONNX). Knowledge of healthcare data privacy and security (e.g., HIPAA, GDPR). Familiarity with GMLP (Good Machine Learning Practice) and clinical evaluation frameworks. The successful More ❯

and applications. Develop and deploy AI solutions using Azure Machine Learning services. Have a knowledge of top ML libraries scalable across multiple CPU's and GPU's. Such as TensorFlow, PyTorch, Keras, OpenAI, XGBoost. And have used these in a commercial setting. Troubleshoot and resolve issues related to data processing and AI model performance. Collaborate with cross-functional teams More ❯

funded R&D projects. Proficient programming skills in Python, with extensive experience in ML development using libraries and toolkits. Familiarity with at least one major ML framework such as TensorFlow or PyTorch. Desirable Technical Expertise: Candidates should demonstrate expertise (through publications, industrial applications, or open-source contributions) in one or more of the following areas: Graph-based machine learning More ❯