1 to 25 of 161 Remote 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 ❯

Job Details Education: Bachelor's, Master's, or PhD in Computer Science, AI, Data Science, or a related field. Programming Skills: Proficiency in Python, TensorFlow, PyTorch, Scikit-learn, or similar frameworks. Machine Learning & AI Expertise: Strong knowledge of supervised, unsupervised, and reinforcement learning. Data Handling: Experience with big data 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 ❯

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 ❯

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 ❯

attention to detail, and a commitment to quality. Strong communication, leadership, and mentorship abilities. Preferred, but not required: Experience with machine learning frameworks (e.g., TensorFlow, PyTorch). Familiarity with containerization and orchestration technologies (Docker, Kubernetes). Knowledge of front-end technologies (HTML, CSS, JavaScript) is a plus. 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 ❯

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 ❯

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 ❯

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 ❯

least two different programming languages (e.g., Python, R, C/C++), including experience with reinforcement learning libraries in Python Experience using deep learning packages (TensorFlow, PyTorch, JAX) Experience cleaning data, prototyping, and fine-tuning state of the art deep learning models Experience with statistics, machine learning, and reinforcement learning More ❯

across the Civil Service. Key Skills and Experience • Strong programming skills in Python, R, or SQL. • Experience with machine learning frameworks (e.g., Scikit-learn, TensorFlow, PyTorch). • Proficiency in data manipulation and analysis (e.g., Pandas, NumPy, Spark). • Knowledge of data visualization tools (e.g., Power BI, Tableau, Matplotlib). More ❯

programming skills in Python or R, with proficiency in data manipulation libraries (e.g., Pandas, NumPy). Experience with machine learning frameworks (e.g., Scikit-Learn, TensorFlow) and data visualization tools (e.g., Tableau, Matplotlib). Solid understanding of statistics, probability, and data-driven decision-making. Experience working with databases (SQL) and More ❯

Science, Computer Science, Statistics, or related field 3+ years of experience in data science or machine learning role Proficiency in Python (pandas, scikit-learn, TensorFlow, etc.) and SQL Experience with cloud platforms (Azure preferred) and ML tools Strong understanding of machine learning concepts and model evaluation techniques Ability to More ❯

data science tools and languages such as Python, PostgreSQL/SQL, Spark, and Git Experience using ML and data science packages such as PyTorch, TensorFlow, or scikit-learn Experience leveraging open-source models and adapting them to generate custom solutions Able to work on-site in Chantilly, Va ACTIVE More ❯