1 to 25 of 241 Remote Permanent TensorFlow Jobs

or Machine Learning Professional Certification. Familiarity with traditional machine learning tools such as Python, SKLearn, XGBoost, SparkML, etc. Experience with deep learning frameworks like TensorFlow or PyTorch. Knowledge of ML model deployment options (e.g., Azure Functions, FastAPI, Kubernetes) for real-time and batch processing. Experience with CI/CD More ❯

applications. Required Skills & Qualifications Technical Expertise: Minimum of 8 years of work experience with hast 4 years in Python; familiarity with frameworks like PyTorch, TensorFlow, and libraries like Hugging Face Transformers. Hands-on experience with LLMs (e.g., OpenAI GPT models, Anthropic Claude) and fine-tuning techniques. Strong understanding of More ❯

of a wide range of ML algorithms. Understanding of MLOps practices for managing and monitoring models in production. Experience with deep learning frameworks (e.g., TensorFlow, PyTorch). Proficiency in programming languages such as Python, SQL, and R. Knowledge of SQL and NoSQL databases for data storage and retrieval. Experience More ❯

Learning & Model Development Experience developing and fine-tuning machine learning models, including supervised and unsupervised learning. Applied knowledge of deep learning frameworks such as TensorFlow or PyTorch. Familiarity with transformer-based architectures (e.g., BERT, GPT) and usage of Hugging Face Transformers. Ability to design and implement basic model training More ❯

applications, particularly in fraud prevention and user personalization. Experience designing, developing, and implementing advanced machine learning models. Familiarity with machine learning frameworks such as TensorFlow, PyTorch, and scikit-learn. Data Engineering Skills: Proficiency in developing and maintaining real-time data pipelines for processing large-scale data. Experience with ETL More ❯

AI ethics standards What You Bring 3+ years of experience in MLOps, DevOps, or AI model deployment Strong skills in Python and frameworks like TensorFlow, PyTorch, ONNX Proficiency with Docker, Kubernetes, and serverless architectures Hands-on experience with ML tools (ArgoWorkflow, Kubeflow, MLflow, Airflow) Experience deploying and optimizing GPU More ❯

algorithms and NLP techniques, with hands-on experience in either academia or industry. Proficiency in Python and experience with ML/NLP libraries like TensorFlow, PyTorch, scikit-learn, or Hugging Face. Experience working with cloud platforms such as AWS, GCP, or Azure. Familiarity with advanced NLP methods, including Prompt More ❯

and multi-agent systems (MAS). Advanced Python programming skills, with a strong emphasis on writing efficient, scalable, and maintainable code. Proven experience with TensorFlow/PyTorch/Jax, Scikit-learn, and MLOps workflows for training, deployment, and monitoring of ML models. Experience working with Polars and/or More ❯

deep learning, and LLM-based applications (e.g., GPT, BERT, LangChain). Programming: Proficiency in Python and experience with AI/ML frameworks (e.g., PyTorch, TensorFlow, Hugging Face ). Data Engineering & SQL: Ability to write efficient SQL queries to blend and structure data from multiple sources for modeling and analysis. More ❯

Requirements: 3+ years of experience in AI/ML engineering, data science or related fields Strong knowledge of machine learning algorithms, deep learning frameworks (TensorFlow, PyTorch), and statistical modeling Proficiency in Python, R, or Julia for AI/ML development Experience with cloud platforms such as AWS, Azure, or More ❯

and developing custom solutions using large language models (LLMs) for business use cases. Proficient in Python-based AI/ML development using frameworks like TensorFlow, PyTorch, and Scikit-learn. LLM Orchestration and Development Expertise in building LLM-powered applications using frameworks such as LangChain and LangGraph, including prompt engineering More ❯

related field (or equivalent experience). Preferred Qualifications: Advanced degree (Master's or Ph.D.) in a relevant field. Experience with machine learning frameworks (e.g., TensorFlow, PyTorch). Knowledge of data visualization tools (e.g., Tableau, Power BI). Familiarity with version control systems (e.g., Git). More ❯

and developing custom solutions using large language models (LLMs) for business use cases. Proficient in Python-based AI/ML development using frameworks like TensorFlow, PyTorch, and Scikit-learn. LLM Orchestration and Development Expertise in building LLM-powered applications using frameworks such as LangChain and LangGraph, including prompt engineering More ❯

principles, design patterns, and best practices. Great to have Skills Experience in working with AI Models (LLM, SLM) and Deep Learning tools such as Tensorflow etc NVIDIA GPU experience is a plus Experience with a modern JavaScript framework or library (e.g., React, Vue.js). Familiarity with RESTful API design More ❯

business problems. We prioritise clean, well-tested code with a culture of documentation and knowledge sharing. Our tech stack includes GCP, Python, GitHub, PyTorch, TensorFlow, Scikit-learn, and XGBoost. With mature infrastructure and dedicated teams for Data Engineering, Analytics, and Platform Engineering, our Data Scientists enjoy high autonomy. We More ❯

scikit-image. Strong knowledge of NLP methods and techniques, including text preprocessing, word embeddings, and language modeling. Proficiency in machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn. Strong programming skills in Python, with experience in data manipulation, analysis, and visualization using libraries like Pandas, NumPy, and Matplotlib. More ❯

science, AI, mathematics, statistics or equivalent. Hands-on experience with Azure Machine Learning, Azure AI Services, and Azure Databricks. Strong understanding of ML frameworks (TensorFlow, PyTorch, Scikit-learn, XGBoost, etc.). Experience deploying ML models using Azure ML Managed Endpoints, AKS, or Azure Functions. Familiarity with MLOps tools (Azure More ❯

in Machine Learning, Deep Learning, and NLP Experience with transformer models (BERT, GPT, LLaMA, etc.) Proficiency in SQL, Python and ML libraries such as TensorFlow, PyTorch, Hugging Face, and Scikit-Learn Expertise in personalisation techniques (recommendation systems, user segmentation, dynamic pricing) Experience working with sensitive and business critical data More ❯

as Python, R, and SQL, and data analysis libraries (e.g., Pandas, NumPy, SciPy, Tidyverse). Strong knowledge of machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn, NLTK). Experience with NLP techniques, such as named entity recognition (NER), topic modeling, semantic similarity, and knowledge graph construction. Demonstrated More ❯

field. 8+ years of experience in machine learning, with a focus on deep learning and generative AI. Strong proficiency in Python and ML frameworks (TensorFlow, PyTorch, JAX). Experience with LLMs and generative models. Expertise in data processing and optimization techniques. Familiarity with MLOps, containerization (Docker, Kubernetes), and cloud More ❯

data transfers. Sound understanding of utilizing data science methodologies and technologies to tackle business challenges. Familiarity with Machine Learning, Deep Learning frameworks (such as TensorFlow/PyTorch), Large Language Models (LLMs), and Natural Language Processing (NLP) libraries and models is highly desirable. Expertise in manipulating and curating large datasets. More ❯

ML workloads. Strong proficiency with Docker, Kubernetes, and infrastructure automation (Terraform, CloudFormation). Solid programming skills in Python and familiarity with ML frameworks like TensorFlow, PyTorch . Experience designing CI/CD pipelines for ML workflows and deployment automation. Exposure to LLM Ops , including managing fine-tuning and deployment More ❯

or a related field. Proficiency in programming languages like Python, R, or SQL for data manipulation. Experience building machine learning models using libraries like TensorFlow, PyTorch, or scikit-learn. Familiarity with cloud platforms like AWS, GCP, or Azure. Strong written and spoken English skills. Bonus Experience: Experience with big More ❯

in Bayesian inference and probabilistic modeling : PGMs, HMMs, GPs, MCMC, variational methods, EM algorithms, etc. Proficiency in Python (must) and familiarity with PyMC, NumPyro, TensorFlow Probability , or similar probabilistic programming tools. Hands-on experience with classical ML and modern techniques, including deep learning , transformers , diffusion models , and ensemble methods More ❯

background in prompt engineering and LLM optimization • Proven track record of implementing and scaling production AI systems • Expertise in Python and major ML frameworks (TensorFlow, PyTorch) • Experience with model evaluation, A/B testing, and establishing robust evaluation frameworks Software Engineering & Infrastructure: • Strong experience with Cloud platforms (AWS, GCP More ❯