26 to 50 of 203 Permanent TensorFlow Jobs

core data science libraries: Pandas, NumPy, and SciPy . Machine Learning: Deep, practical experience with popular ML frameworks and libraries: scikit-learn, TensorFlow, or PyTorch . Statistics & Math: Strong foundation in statistical modeling , probability, hypothesis testing, regression analysis, and multivariate calculus/linear algebra for understanding model mechanics. Databases ...

workloads Knowledge of MLOps practices and ML pipelines Experience with data platforms such as Snowflake, Databricks, or Spark Familiarity with AI frameworks like TensorFlow or PyTorch Cloud certifications such as AWS Certified Solutions Architect or Azure AI Engineer Qualified candidates should APPLY NOW for immediate consideration! Please hit APPLY ...

selecting appropriate modeling approaches for each. Strong proficiency in Python and SQL, with hands‐on experience using major ML libraries/frameworks (e.g., PyTorch, TensorFlow, scikit‐learn) for model development and evaluation. Deep understanding of machine learning algorithms, model evaluation techniques (e.g., AUC, lift, calibration, stability), and data pipeline ...

working as a data scientist (or similar role). Expert proficiency of Python and experience using SQL, alongside using common ML/AI packages (TensorFlow, PyTorch, XGBoost, etc.). Familiarity with statistical (e.g. GLM, GAMs) and deep learning techniques (e.g. neural networks, transformers, diffusion models, etc.). Comfortable designing ...

related field Strong expertise in Large Language Models and advanced fine-tuning techniques Hands-on experience with ML frameworks such as PyTorch, TensorFlow, or scikit-learn Experience with Generative AI tools like LangChain, Weaviate, LangGraph, or LlamaIndex Advanced programming skills in Python Competitive programming or data science background (e.g. ...

SparkSQL in data or ML-focused roles. Strong understanding of machine learning concepts and experience using common ML libraries such as scikit‐learn, TensorFlow or PyTorch, alongside packages such as NumPy and Pandas. Knowledge of natural language processing techniques and API integration patterns for ML services. Experience delivering projects ...

deep learning, geavanceerde data-analysetechnieken en beheersing van programmeertalen (Python, R, SQL). Ervaring met cloudplatforms (AWS, Azure, GCP) en tools/frameworks zoals TensorFlow, PyTorch, MLflow, Dataiku of Databricks (MLOps/LLM-kennis is een pré). Goede business skills: in staat om data-oplossingen te ontwikkelen ...

distributed environment. LLMs: Understanding of LLM architectures, pre and/or post-training, evaluations and inference. Programming languages: Proficiency in Python using PyTorch/TensorFlow/JAX framework. Cloud-native technologies: Experience in developing and deploying in cloud platforms (e.g., AWS, GCP or Azure), an understanding of containerisation (e.g. ...

LLMs: Deep understanding of LLM architectures, pre and/or post-training, evaluations and inference. Programming languages: Excellent proficiency in Python using PyTorch/TensorFlow/JAX framework. Customer facing: Experience working directly with customers to solve applied problems, including product integration. Cloud-native technologies: Experience in developing ...

/ML engineering or architecture roles Proven experience in the healthcare or life sciences domain Strong knowledge of machine learning frameworks (e.g., TensorFlow, PyTorch) Experience with healthcare data standards (e.g., HL7, FHIR) Familiarity with cloud platforms (AWS, Azure, or GCP) Understanding of data privacy, security, and regulatory requirements ...

teams to deliver features Skills & Experience: Strong Python and SQL skills Familiarity with Azure or AWS Some exposure to ML frameworks (e.g. scikit-learn, TensorFlow, or PyTorch) Background in data engineering, analytics engineering, or similar Desirables: ETL/ELT pipeline experience Microsoft Fabric/Data Lake knowledge BI tools ...

Skills for the Generative AI Engineer: Hands-on experience with Generative AI and LLMs Strong programming skills in Python Experience with frameworks such as TensorFlow, PyTorch, LangChain or similar Experience with prompt engineering and LLM integration Exposure to cloud platforms (AWS, Azure or GCP) Experience integrating APIs and microservices ...

tower neural networks, embedding techniques, and ranking models. Proficiency in Python with familiarity to ML libraries e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) Familiarity with cloud platforms (GCP, AWS, Azure) and tools like Dataiku. Experience with ML Ops, including model deployment, monitoring, and retraining pipelines. Ability to work ...

Learning Engineer or equivalent role Hands-on experience developing and deploying ML models in Python using frameworks such as scikit-learn, XGBoost, PyTorch, or TensorFlow Strong experience with cloud-based ML deployment (e.g., AWS SageMaker, Lambda, S3) Knowledge of MLOps/LLMOps tooling (e.g., MLflow, Weights & Biases, Data Version ...

version control tools, preferably Git. Proficiency in Docker and container orchestration. Advanced proficiency in Python and familiarity with AI and machine learning libraries (e.g., TensorFlow, PyTorch, Scikit-learn). Strong understanding of algorithms, data structures, and software engineering principles. Experience in deploying AI models in a production environment. Proven ...

into production environments, ideally for operational, supply chain, or critical infrastructure use cases. · Programming: Expert-level Python programming (pandas, scikit-learn, statsmodels, PyTorch/TensorFlow). · Platform Expertise: Deep, hands-on experience with Databricks and the AWS cloud ecosystem. · Mathematical Foundation: Strong understanding of probability, time-series analysis ...

stack What They’re Looking For 4+ years experience in machine learning, data science, or AI engineering Strong Python skills (NumPy, Pandas, PyTorch/TensorFlow) Experience working with biological or biomedical data (industry or academia) Solid understanding of ML fundamentals (supervised/unsupervised learning, model evaluation, etc.) Familiarity with ...

commercial acumen with a history of influencing the commercial success of AI products and solutions. Desirable Experience with modern deep learning frameworks (e.g., PyTorch, TensorFlow), fine tuning or distillation of LLMs (e.g., GPT, Llama, Claude, Gemini), and advanced ML libraries (e.g., scikit-learn, XGBoost). Experience with data storage ...

Node.js, Python, REST & GraphQL APIs Cloud & Infra: AWS (ECS, S3, Lambda), Docker, Cloudformation, Pulumi, CI/CD with GitHub Actions ML/AI: PyTorch, TensorFlow, scikit‐learn, MLflow for experiment tracking, Zenml for ML pipelines Data: PostgreSQL, DynamoDB, data pipelines with Zenml (We’re open to evolving the stack ...

Statistics, Mathematics, or related quantitative fields preferred. Strong proficiency in Python (preferred) or Scala, including experience with ML libraries such as scikit‐learn, XGBoost, TensorFlow or PyTorch. Extensive experience with Spark or PySpark and distributed data systems (e.g., AWS EMR, Databricks) working on very large, messy datasets. Deep understanding ...

text, audio, image, or video data Familiarity with cloud platforms (AWS, Azure, GCP) Strong Python skills and experience with ML libraries and frameworks (e.g. TensorFlow, PyTorch) Knowledge of statistics and probability Experience with ML lifecycle tools (e.g. MLflow, Kubeflow, Argo) Understanding of Ethical and Responsible AI principles Security Requirements ...

Engineer or Data Scientist with production ML exposure Strong understanding of ML algorithms, model development, and deployment Experience with Python and ML frameworks (e.g. TensorFlow, PyTorch, scikit-learn) Familiarity with data pipelines and cloud or on-prem environments Understanding of MLOps principles Ability to work in secure or regulated ...

ICML, or ICLR. Hands-on experience applying deep learning models to complex, ideally temporal or financial, datasets. Expertise in Python and modern ML frameworks (TensorFlow, PyTorch, JAX, etc.). Prior experience in a commercial or industry setting post-PhD, ideally in a similarly data-driven domain. Why Apply Compensation ...

distributed computing tools such as Azure Synapse and Snowflake. Familiarity with data transformation tools (Databricks, Azure Data Factory) and ML platforms (Azure ML, TensorFlow). Experience with data visualisation tools such as Power BI. Strong commercial acumen with the ability to translate business problems into scalable analytical solutions. Excellent ...

system design: orchestration, memory, deployment, monitoring – Exposure to tools such as LangGraph, ReAct, CoT — or building similar systems from scratch – Familiar with PyTorch/TensorFlow, RAG architectures, vector databases, modern cloud infra – Experience in startup or consulting environments is a plus – Comfortable working autonomously in fast-moving, sometimes ambiguous ...