51 to 75 of 103 Remote TensorFlow Jobs

Data Science, Computer Science, Biostatistics, or related field ✔️ 7–10 years’ experience, with 3+ years applying AI/ML to healthcare or clinical research data ✔️ Expertise in Python, R, TensorFlow, PyTorch, and modern ML frameworks ✔️ Hands-on experience with LLMs, generative AI, and natural language processing for medical text ✔️ Familiarity with AWS, MLOps, and cloud-based platforms ✔️ Proven ability More ❯

or statistical signal processing to sequential 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. Domains of Particular Interest RF communications and CEMA Electronic or Electromagnetic Warfare (EW) Tracking and sensor data fusion Radar signal processing Acoustic data processing (including More ❯

regard to you…it would be great if you bring strong Python skills, experience with Azure ML, Docker, Git, and a passion for machine learning tools like scikit-learn, TensorFlow or PyTorch. Bonus points if you're curious about GenAI and know your way around SQL. If you're ready to build things that actually get used, apply now More ❯

In regard to you...it would be great if you bring strong Python skills, experience with Azure ML, Docker, Git, and a passion for machine learning tools like scikit-learn, TensorFlow or PyTorch. Bonus points if you're curious about GenAI and know your way around SQL. If you're ready to build things that actually get used, apply now More ❯

advances in temporal modeling and deep learning. Document methods and support reproducibility, validation, and publication where appropriate. Essential Requirements Strong programming and modeling skills in Python (NumPy, PyTorch or TensorFlow, SciPy, pandas). In-depth knowledge of machine learning for time-series, including RNNs, LSTMs, GRUs, transformers, attention mechanisms. Solid understanding of probabilistic models (HMMs, Bayesian inference, graphical models 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 ❯

building data pipelines to integrate and process diverse data sources. • Understanding of data modeling, data warehousing, and data governance principles • Machine Learning Infrastructure: Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch) and experience in designing and implementing machine learning infrastructure. Understanding model serving, monitoring, and deployment strategies is beneficial Compensation: • $140,000 - $280,000 (Based on years of relevant More ❯

of AI technologies, algorithms, and frameworks . Proficiency in programming languages (Python, R, C/C++, Java) and secure coding practices. Hands-on experience with ML/LLM frameworks (TensorFlow, PyTorch, scikit-learn, etc.). Expertise in DevOps/CI/CD security and cloud-native architectures (containers, Kubernetes, Git). Strong knowledge of AI/ML-specific security More ❯

Approaches: Machine learning, optimisation, stochastic and agent-based models About You Experience in the energy sector - markets, trading, forecasting, etc. Strong Python skills with machine learning frameworks (scikit-learn, TensorFlow, PyTorch). Knowledge of GitHub/Azure DevOps and SQL advantageous. Excellent communicator, able to explain technical concepts to non-technical audiences. Degree (or equivalent experience) in a numerical More ❯

building data pipelines to integrate and process diverse data sources. • Understanding of data modeling, data warehousing, and data governance principles • Machine Learning Infrastructure: Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch) and experience in designing and implementing machine learning infrastructure. Understanding model serving, monitoring, and deployment strategies is beneficial Compensation: • $190,000 - $290,000 (Based on years of relevant More ❯

working with large databases and data warehouses. You'll be proficient in Python, R, or other relevant programming languages and have Experience with machine learning libraries and frameworks (e.g., TensorFlow, Scikit-learn, PyTorch). With a background in data mining and pattern recognition you'll be an expert in statistical modelling, predictive analytics and regression techniques. An industry certification More ❯

data science position to help us identify, diagnose, and cure production inefficiencies using data. Specific responsibilities include: Model Development : Design and develop deep learning models using frameworks such as TensorFlow, PyTorch, and Keras for specific applications in the manufacturing domain. Training and Evaluation : Train models on large datasets, evaluate their performance, and fine-tune hyperparameters to optimize results. Deployment More ❯

medical, aerospace, or automotive Experience of real-time operating systems and embedded development Experience working to an Agile lifecycle. Awareness of machine-learning frameworks such as Pytorch, Keras/Tensorflow, MATLAB Machine Learning toolbox Awareness of mathematical libraries used for signal processing, image processing and data processing Awareness of high-performance computing and the challenges of parallel processing This 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 ❯

team members, and collaborating closely with engineers, PMs and analysts to deliver measurable user and business impact. We work primarily in Python and SQL, with tools like Scikit-learn, Tensorflow, PyTorch and Pandas. Our ML stack runs on AWS and Sagemaker. We value clean, documented, well-tested and reviewed code-and have the tooling and culture to support this. More ❯

background in machine learning, especially in generative models (e.g. GANs, VAEs, diffusion models) applied to chemical or materials domains. Proficient in programming and data analysis using Python, PyTorch or TensorFlow, and common cheminformatics or molecular simulation software. Excellent analytical, problem-solving, and communication skills-able to share complex concepts with technical and non-technical audiences. Proactive approach to autonomous More ❯

scale – beyond PoC, into live environments. Ability to engage clients with clear communication and advisory skills. Emirati Arabic language skill s are ESSENTIAL for this role Preferred: Knowledge of TensorFlow, PyTorch, vector databases, retrieval-augmented generation (RAG) . Background in start-ups (T-shaped generalists) or consultancies (client-facing exposure). Experience in regulated industries or public sector projects. More ❯

by your tech lead and colleagues from the wider Data Science chapter at Lyst. We work mainly in Python using all the standard ML toolkits and frameworks (e.g. SKLearn, Tensorflow, Pytorch), and run our ML code in the AWS environment using Sagemaker where possible. We have a strong preference for clean, documented, well tested and reviewed code and have More ❯

s ability to surface high-value insights and opportunities for users. What We’re Looking For Proven experience delivering impactful AI/ML projects. Expertise in frameworks such as TensorFlow or PyTorch, and proficiency in Python. Familiarity with AI-first approaches and large language model integration. Some data engineering experience is a strong plus. Strong analytical and problem-solving More ❯

s ability to surface high-value insights and opportunities for users. What We’re Looking For Proven experience delivering impactful AI/ML projects. Expertise in frameworks such as TensorFlow or PyTorch, and proficiency in Python. Familiarity with AI-first approaches and large language model integration. Some data engineering experience is a strong plus. Strong analytical and problem-solving More ❯

Starter; willing to learn new technologies, ability to learn fast Desirable Attributes: Knowledge of Eclipse RCP and Eclipse OSGi Swing and SWT experience Understanding of Machine Learning technologies (Python, TensorFlow etc.) Experience in Geophysics and/or Geology domain especially Oil and Gas Undergraduate degree in Software Engineering, Computer Science or equivalent Agile Scrum certification Experienced in working with More ❯

a small team of software developers and quality assurance engineers Desirable Attributes: Knowledge of Eclipse RCP and Eclipse OSGi Swing and SWT experience Understanding of Machine Learning technologies (Python, TensorFlow etc.) Experience in Geophysics and/or Geology domain especially Oil and Gas Undergraduate degree in Software Engineering, Computer Science or equivalent Agile Scrum certification Experienced in working with More ❯

peers, and delivering high-impact work without direct management responsibilities. Proven experience mentoring and coaching colleagues. Strong Python skills and experience with ML frameworks such as PyTorch, HF Transformers, TensorFlow, or JAX. Track record of end-to-end applied research and deploying transformer models. Deep knowledge of machine learning fundamentals and cloud deployment. Excellent communication skills with the ability More ❯

and you're comfortable taking a feature from concept to deployment. Machine Learning Engineering & Research: A comprehensive background in machine learning, with deep experience in ML frameworks (e.g., PyTorch, TensorFlow, Hugging Face) and a strong grasp of the underlying theory behind the models and techniques you use. Bonus Points: Experience with modern LLM orchestration frameworks (e.g., LangChain, LlamaIndex, DSPy More ❯