101 to 125 of 1,245 Remote TensorFlow Jobs

Data Scientist with proven experience leading AI projects and mentoring junior team members. You should have strong expertise in Python, including libraries such as TensorFlow, PyTorch, and Hugging Face Transformers, with a solid understanding of LLM architectures. You should be well-versed in various machine learning techniques, including supervised More ❯

Docker, Kubernetes), and big data processing frameworks (e.g. Spark, BigQuery). • Expertise in Python and SQL, with working knowledge of ML frameworks such as TensorFlow, PyTorch, or Scikit-learn. • Demonstrated ability to lead through ambiguity and complexity, making pragmatic and scalable technical decisions. • Excellent communication and stakeholder engagement skills More ❯

lead technical direction across projects or domains Expertise in model validation, explainability, governance and ethical AI principles Advanced proficiency in Python (e.g. Scikit-learn, TensorFlow/PyTorch) and SQL, plus familiarity with ML engineering and MLOps practices Nice to have: Experience in setting or influencing data science strategy in More ❯

Demonstrated experience working closely with business stakeholders in R&D, translating complex scientific challenges into AI solutions. Proficiency in Python and ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn, Hugging Face). Experience building and deploying models in cloud environments (e.g. Azure, GCP). Solid understanding of statistics, optimization, and 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 ❯

make you stand out: • Experience working in an analytics role in the gambling industry. • Experience with CRM data analysis and customer segmentation. • Knowledge of tensorflow/pytorch. • Expertise in using data visualization tools such as Google Looker and working with Google's BigQuery. • Experience in design and evaluation of More ❯

make you stand out: • Experience working in an analytics role in the gambling industry. • Experience with CRM data analysis and customer segmentation. • Knowledge of tensorflow/pytorch. • Expertise in using data visualization tools such as Google Looker and working with Google's BigQuery. • Experience in design and evaluation of More ❯

make you stand out: Experience working in an analytics role in the gambling industry. Experience with CRM data analysis and customer segmentation. Knowledge of tensorflow/pytorch. Expertise in using data visualization tools such as Google Looker and working with Google's BigQuery. Experience in design and evaluation of More ❯

make you stand out: • Experience working in an analytics role in the gambling industry. • Experience with CRM data analysis and customer segmentation. • Knowledge of tensorflow/pytorch. • Expertise in using data visualization tools such as Google Looker and working with Google's BigQuery. • Experience in design and evaluation of More ❯

make you stand out: • Experience working in an analytics role in the gambling industry. • Experience with CRM data analysis and customer segmentation. • Knowledge of tensorflow/pytorch. • Expertise in using data visualization tools such as Google Looker and working with Google's BigQuery. • Experience in design and evaluation of More ❯

make you stand out: • Experience working in an analytics role in the gambling industry. • Experience with CRM data analysis and customer segmentation. • Knowledge of tensorflow/pytorch. • Expertise in using data visualization tools such as Google Looker and working with Google's BigQuery. • Experience in design and evaluation of 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 ❯

Vertex AI preferred) Conducted high level research, such as a M.Phil or PhD or relevant industry experience Knowledge of deep learning frameworks such as Tensorflow or Torch What's in it for you By joining Ocado Retail you'll have the chance to experience life at the world's More ❯

experience in machine learning, data science, or applied AI roles . Proficiency with Python, SQL , and common machine learning frameworks (e.g., scikit-learn, PyTorch, TensorFlow). Hands-on experience with cloud platforms , particularly Azure , AWS, or GCP — including ML and data tooling. Knowledge of generative AI frameworks , LLMs, vector More ❯

like AWS, Azure, or Google Cloud. Strong understanding of database technologies, SQL, and NoSQL databases. Experience working with AI frameworks and libraries such as TensorFlow, PyTorch, or Scikit-learn. Familiarity with building and deploying machine learning models in production environments. Excellent problem-solving skills and ability to troubleshoot complex More ❯

with the analysis or application of data in finance, economics, or related fields is a plus. • Experience with machine learning libraries such as PyTorch, TensorFlow, JAX is a plus. • Experience applying generative AI solutions (via open source tools or through Azure, Amazon Bedrock, Nvidia etc.) is a plus. • Experience More ❯

senior role. Proven experience in a startup or fast-paced environment. Strong proficiency in Python, SQL, and data science libraries (e.g., scikit-learn, pandas, TensorFlow/PyTorch). Experience working with financial data, risk modelling, or algorithmic trading is a plus. Familiarity with cloud platforms (AWS, GCP, or Azure More ❯

senior role. Proven experience in a startup or fast-paced environment. Strong proficiency in Python, SQL, and data science libraries (e.g., scikit-learn, pandas, TensorFlow/PyTorch). Experience working with financial data, risk modelling, or algorithmic trading is a plus. Familiarity with cloud platforms (AWS, GCP, or Azure More ❯

senior role. Proven experience in a startup or fast-paced environment. Strong proficiency in Python, SQL, and data science libraries (e.g., scikit-learn, pandas, TensorFlow/PyTorch). Experience working with financial data, risk modelling, or algorithmic trading is a plus. Familiarity with cloud platforms (AWS, GCP, or Azure More ❯

data. Requirements 2+ years of experience in Machine Learning, NLP, or AI development . Essential experience working with LLMs . Strong proficiency in Python, TensorFlow, PyTorch, Hugging Face transformers . Experience in data engineering, model training, and MLOps workflows . Background in lead generation, sales automation, or finance-related More ❯

years of experience in data science, machine learning, or a related role Proficiency in programming languages such as Python or R, and libraries like TensorFlow, PyTorch, Scikit-learn, or Pandas Strong understanding of statistical modeling, probability, and optimization techniques Ability to work with messy, real-world datasets and perform More ❯

Knowledge of optimization techniques for reducing LLM latency and computational costs Software Engineering & Architecture Strong Python development skills (pandas, numpy, scikit-learn, PyTorch/TensorFlow) Experience with web frameworks (Streamlit, FastAPI, or Flask) and frontend technologies Database design and optimization (PostgreSQL preferred) for large protein datasets API development and More ❯

solving skills is considered as a plus. Technical Skills: Strong programming skills in Python and SQL . Expertise in machine learning frameworks (e.g., PyTorch, TensorFlow, Scikit-learn). Hands-on experience with big data technologies and cloud platforms (AWS preferred; Azure is a plus). Experience deploying ML models 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 ❯

timeframe An excellent command of the basic libraries for data science (e.g. NumPy, Pandas, Scikit-Learn) and familiarity with a deep-learning framework (e.g. TensorFlow, PyTorch, Caffe) A high level of mathematical competence and proficiency in statistics A solid grasp of essentially all of the standard data science techniques More ❯