51 to 75 of 114 Remote TensorFlow Jobs

learning lifecycle 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 More ❯

learning lifecycle 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 More ❯

commerce - this is essential as you'll be the domain expert from day one. Excellent Python programming skills and strong familiarity with ML libraries such as scikit-learn, XGBoost, TensorFlow, PyTorch, Keras etc. Proven track record deploying ML models to production (API, batch, or streaming contexts) Solid understanding of the modern software engineering, infrastructure and data technologies Experience working More ❯

shares knowledge, and promotes best practices. Excellent communicator, able to work cross-functionally and tailor messages to different audiences. Hands-on expertise in Python, SQL, ML frameworks (e.g. XGBoost, TensorFlow, PyTorch), and cloud tools (GCP, BigQuery, Vertex AI). Familiar with generative AI tools and frameworks (e.g. OpenAI, HuggingFace, LangChain). Deeply curious, commercially minded, and impact-driven with More ❯

and scaling models that solve complex, real-world problems Deep understanding of machine learning concepts and experience applying them in production settings, using frameworks such as Transformers, PyTorch, or TensorFlow Strong Python skills, with the ability to write clean, modular, production-grade code, and a solid understanding of data engineering and MLOps principles Ability to lead end-to-end More ❯

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 ❯

Looking For: 0–2 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 ❯

Looking For: 0–2 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 ❯

programming skills, with the ability to quickly become fluent in Python. Deep knowledge of core data science libraries (NumPy, Pandas, Scikit-Learn) and at least one deep learning framework (TensorFlow, PyTorch, or similar). High mathematical and statistical competence, with the ability to design new algorithms when needed. Experience leading teams to deliver innovative technical work on time, including More ❯

with the ability to write production-grade code Proficiency in core data science libraries (e.g. NumPy, Pandas, Scikit-learn) and familiarity with at least one deep learning framework (e.g. TensorFlow, PyTorch) A solid understanding of the full range of data science techniques, including supervised and unsupervised learning, Bayesian methods, NLP, time-series analysis, and SQL querying Ability to scope More ❯

Prior experience in anomaly detection applied to areas such as QA, gameplay analysis, computer vision or video stream analysis. Proven experience with machine learning frameworks such as Python, NumPy, TensorFlow, or PyTorch. Strong understanding of data analysis, signal processing, and statistical modeling. Experience with video processing and understanding of game streaming technologies is a plus. Problem-Solving Skills: Excellent More ❯

designing, developing & deploying scalable backend systems. Familiarity with CICD, containerisation, deployment technologies & cloud platforms (Jenkins, Kubernetes, Docker, AWS) or Familiarity with Big Data and Machine Learning technologies (NumPy, PyTorch, TensorFlow, Spark). Excellent communication, collaboration & problem solving skills, ideally with some experience in agile ways of working. Security clearance: You must be able to gain and maintain the highest More ❯

or Neocloud space. Practical knowledge of AI/ML technologies and their applications, including understanding language models (LLMs), and experience with training and fine-tuning LLMs using frameworks like TensorFlow, PyTorch, or Hugging Face Transformers. Good understanding of programming/scripting: (e.g., Python, Go) for customizing solutions, creating scripts, or automating tasks. Experience with AI relevant infrastructure, including Networking More ❯

develop, evolve, and maintain cloud-centric platform(s) including IoT, Customer Solution Delivery, Data Science Environments and Software Delivery, as well as satellite tools and environments (file storage, databases, tensorflow, data streaming, eventing, machine learning and big data frameworks, notebook technologies, and container orchestration tooling). Major/Key Accountabilities Design, develop, release and operate bespoke software tools, DSLs More ❯

have a proven commercial experience delivering AI/ML projects end-to-end in production environments Strong Python skills with hands-on use of ML libraries like Scikit-learn, TensorFlow, PyTorch, or Hugging Face Solid understanding of machine learning fundamentals and performance evaluation techniques Experience working in cloud platforms (AWS, GCP, or Azure) with MLOps tools (e.g. MLflow, SageMaker More ❯

have a proven commercial experience delivering AI/ML projects end-to-end in production environments Strong Python skills with hands-on use of ML libraries like Scikit-learn, TensorFlow, PyTorch, or Hugging Face Solid understanding of machine learning fundamentals and performance evaluation techniques Experience working in cloud platforms (AWS, GCP, or Azure) with MLOps tools (e.g. MLflow, SageMaker More ❯

functional teams to turn real-world problems into working software. 🛠️ What You Bring: Fluency in Python and strong grasp of ML/DL concepts. Experience with frameworks like PyTorch, TensorFlow, Scikit-learn, and HuggingFace Transformers. Comfort designing production-ready AI systems—optimising for speed, cost, and value. Passion for leveraging AI assistants and agentic tools to maximise impact. Bonus More ❯

functional teams to turn real-world problems into working software. 🛠️ What You Bring: Fluency in Python and strong grasp of ML/DL concepts. Experience with frameworks like PyTorch, TensorFlow, Scikit-learn, and HuggingFace Transformers. Comfort designing production-ready AI systems—optimising for speed, cost, and value. Passion for leveraging AI assistants and agentic tools to maximise impact. Bonus More ❯

or related field 3+ years' experience in applied R&D or research consultancy (public sector/defence background advantageous) Strong Python skills and experience with ML frameworks (e.g. PyTorch, TensorFlow, scikit-learn) Expertise in one or more of the following areas: Multi-modal data fusion or time series analysis Uncertainty quantification or probabilistic modelling Active learning, explainable AI, or More ❯

or related field 3+ years' experience in applied R&D or research consultancy (public sector/defence background advantageous) Strong Python skills and experience with ML frameworks (e.g. PyTorch, TensorFlow, scikit-learn) Expertise in one or more of the following areas: Multi-modal data fusion or time series analysis Uncertainty quantification or probabilistic modelling Active learning, explainable AI, or More ❯

teams (ideally 5+ people) Demonstrated success in writing and winning technical research proposals (especially within Defence or public sector R&D environments) Advanced skills in Python and ML frameworks (TensorFlow, PyTorch) Deep experience in one or more of the following: Knowledge graphs & graph ML (e.g. PyTorch-Geometric, Neo4j) NLP and information extraction (transformer-based models desirable) Semantic reasoning, ontology More ❯

in python, with a focus on machine learning, deep learning, natural language processing, generative AI, image processing and OCR all additional positives. Experience with some of the following frameworks - TensorFlow, Pytorch, Hugging face, Spacy, OpenCV, Regex or equivalents. Experience delivering safe code to production, focusing on cybersecurity and resilience of the application and APIs. Preferred Experience: Experience using PostgreSQL More ❯

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 ❯

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 ❯

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 ❯