26 to 50 of 312 TensorFlow Jobs

with model deployment and monitoring tools, version control, and orchestration frameworks (e.g., Docker, Kubernetes, MLflow, CI/CD pipelines). Experience with Python and common ML libraries (scikit-learn, TensorFlow, PyTorch, XGBoost) and data-processing tools (SQL, Spark). Typical Education & Experience Experienced (Level 3) Education/experience typically acquired through advanced education (e.g. Associate) and typically 3 or More ❯

with a strong portfolio of high-impact projects in production Expert-level programming skills in Python and SQL, and fluency with leading ML/AI frameworks (e.g., scikit-learn, TensorFlow, PyTorch) Direct experience with GenAI/LLM technologies, including tools like Hugging Face, LangChain, OpenAI APIs, vector databases, and fine-tuning methods Deep knowledge of machine learning algorithms (supervised More ❯

Engineering, or a related technical field Strong proficiency in Python is a must 2 - 4 years of experience in machine learning or backend software development Experience using frameworks like TensorFlow, PyTorch, or Scikit-learn Solid understanding of ML workflows: data cleaning, model development, tuning, evaluation Familiar with model deployment, API development, or real-world ML integration Experience with tools More ❯

as a Data Scientist or in a similar role. Strong programming skills in Python, R, or SQL . Hands-on experience with machine learning libraries such as scikit-learn, TensorFlow, or PyTorch . Solid understanding of statistics, predictive modeling, and data mining techniques. Experience with data visualization tools such as Tableau, Power BI, or matplotlib/seaborn . Familiarity More ❯

of experience in AI engineering or a related role. Technical Skills: Proficiency in programming languages such as Python, R, or Java. Experience with AI frameworks and libraries such as TensorFlow, PyTorch, or scikit-learn. Machine Learning Knowledge: Strong understanding of machine learning algorithms, neural networks, and deep learning techniques. Analytical Skills: Excellent analytical and problem-solving skills, with the More ❯

a Data Scientist, ideally within customer analytics, marketing, or CRM environments. Strong coding skills in Python, with deep familiarity across ML and data libraries (pandas, numpy, scipy, scikit-learn, tensorflow, pytorch). A broad understanding of machine learning and statistical methods, including NLP, deep learning, Bayesian inference, time-series forecasting, and recommendation systems. Hands-on experience with cloud platforms More ❯

technical field (Statistics, Mathematics, Physics, Computer Science, Machine Learning) Strong programming skills in Python (production-level) and SQL; confident with modern ML/AI libraries such as scikit-learn, TensorFlow, or PyTorch Familiarity with MLOps frameworks, model deployment, and cloud-based platforms (Databricks, AWS, Azure) Strong experience with data visualisation tools and techniques; able to turn complex results into More ❯

consistent track record of shipping models to production and supporting them post-deployment. Strong Python programming skills, including object-oriented design and proficiency with key ML libraries (e.g., PyTorch, TensorFlow, Scikit-Learn). Solid understanding of probability and statistical modeling to support robust model development and interpretation. Experience with cloud platforms (especially Azure and/or AWS) and modern More ❯

to manage ambiguity. Data driven decision making. Experience with GenAI LLM models Experience with MLOps, building workflows for model retraining, monitoring and deploying Experience with ML frameworks such as TensorFlow, PyTorch Experience with cloud-based data platforms such as AWS or Azure Experience with data visualization tools such as Power BI Salary : $122,400.00 - $228,000.00 Pay Type: Salaried More ❯

and associated concepts, such as transformer architecture and retrieval augmented generation. Strong programming ability with demonstrated experience in Python and one or more associated machine learning frameworks, such as TensorFlow, PyTorch, or SKLearn. Knowledge of and experience working with open-source AI models. Demonstrated ability to perform the essential duties of the position with or without accommodation. Authorization to More ❯

and on-prem setup Requirements: 25 years experience in ML engineering/MLOps roles Strong proficiency in Python and experience with relevant ML libraries/frameworks (pandas, numpy, sklearn, TensorFlow, PyTorch) Strong understanding and experience in implementing end-to-end ML pipelines (data, training, validation, serving) Experience with ML workflow orchestration tools (e.g., Airflow, Prefect, Kubeflow) and ML feature More ❯

Claude, Gemini, or Perplexity. Strong understanding of generative AI principles, prompt chaining, context window management, and token efficiency. Proficiency in Python and experience with AI/ML frameworks like TensorFlow, PyTorch, or Hugging Face. Experience integrating AI into enterprise platforms such as DealCloud, Salesforce, or similar CRMs. Understanding of workflow automation tools (e.g., Zapier, n8n, Make) and dashboarding platforms More ❯

a Data Scientist, ideally within customer analytics, marketing, or CRM environments. Strong coding skills in Python, with deep familiarity across ML and data libraries (pandas, numpy, scipy, scikit-learn, tensorflow, pytorch). A broad understanding of machine learning and statistical methods, including NLP, deep learning, Bayesian inference, time-series forecasting, and recommendation systems. Hands-on experience with cloud platforms More ❯

and versioning Exposure to tools like KServe, Ray Serve, Triton, or vLLM a big plus Bonus Points: Experience with observability frameworks like Prometheus or OpenTelemetry Knowledge of ML libraries: TensorFlow, PyTorch, HuggingFace Exposure to Azure or GCP Passion for financial services Requirements: Degree in Computer Science, Engineering, Data Science or similar What We Offer A collaborative and innovative work More ❯

learning, with at least 2 years supporting federal or defense programs. * Must possess proficiency with *Maven, Vantage, TDP and Advana.* * Proficiency in Python and ML libraries (e.g., scikit-learn, TensorFlow, PyTorch) Experience with data wrangling, feature engineering, and model evaluation in secure or air-gapped environments. * Familiarity with DoD data systems, cybersecurity protocols, and cloud platforms (e.g., AWS GovCloud More ❯

software engineering concepts and best practices (e.g., versioning, testing, CI/CD, API design, MLOps) Building machine learning models and pipelines in Python, using common libraries and frameworks (e.g., TensorFlow, MLFlow) Distributed computing frameworks (e.g., Spark, Dask) Cloud platforms (e.g., AWS, Azure, GCP) and HP computing Containerization and orchestration (Docker, Kubernetes) Ability to scope and effectively deliver projects What More ❯

and technical audiences. Experience working with real world data sets and building scalable models from big data. Experience with modeling tools such as R, scikit learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc. Experience with large scale distributed systems such as Hadoop, Spark etc. Amazon is an equal opportunity employer and does not discriminate on the basis of protected More ❯

concept , model monitoring , and adoption of emerging AI tech. What We're Looking For 5+ years in data engineering, with team or project leadership experience. Advanced Python (Pandas, PyTorch, TensorFlow, Scikit-learn). Strong AWS/GCP , MySQL , and CI/CD experience; Docker/Kubernetes a plus. Excellent communication, organisation, and problem-solving skills. Passion for innovation and More ❯

concept , model monitoring , and adoption of emerging AI tech. What We’re Looking For 5+ years in data engineering, with team or project leadership experience. Advanced Python (Pandas, PyTorch, TensorFlow, Scikit-learn). Strong AWS/GCP , MySQL , and CI/CD experience; Docker/Kubernetes a plus. Excellent communication, organisation, and problem-solving skills. Passion for innovation and More ❯

in production. What We’re Looking For 3+ years of experience in Data Science. Strong proficiency in Python and experience with ML libraries/frameworks (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch). Hands-on experience implementing end-to-end ML pipelines (data ingestion, training, validation, serving). Familiarity with ML workflow orchestration tools (Airflow, Prefect, Kubeflow) and feature/ More ❯

in production. What We’re Looking For 3+ years of experience in Data Science. Strong proficiency in Python and experience with ML libraries/frameworks (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch). Hands-on experience implementing end-to-end ML pipelines (data ingestion, training, validation, serving). Familiarity with ML workflow orchestration tools (Airflow, Prefect, Kubeflow) and feature/ More ❯

supervised and unsupervised learning, NLP, neural networks, Bayesian statistics, time-series forecasting, collaborative filtering, and deep learning Proficiency in Python and ML libraries (e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) Experience with cloud platforms (GCP, AWS, Azure) and tools like Dataiku and Databricks Experience with ML Ops, including deployment, monitoring, and retraining pipelines Ability to work cross-functionally More ❯

Stay current with advancements in AI, ML, and Gen AI technologies, and evaluate their applicability to ongoing initiatives. Ideal Candidate Strong experience in AI/ML development using Python, TensorFlow, PyTorch, or similar frameworks. Solid understanding of data science principles, including statistical modelling, feature engineering, and algorithm selection. Experience with cloud platforms (e.g., Azure, AWS, GCP) and scalable data More ❯

of experience in software engineering, machine learning, data science, or artificial intelligence. • Strong proficiency in Python. • Experience using common NLP and/or ML Python frameworks, such as PyTorch,TensorFlow, Transformers/Hugging Face, and NumPy. • LLM skills including fine-tuning, LLMOps, function-calling, and retrieval augmented generation (RAG). • Experience following software best practices in team settings, including More ❯

excellent understanding of key concepts in computer science (e.g. databases, software engineering practices, cloud computing - especially AWS) and data science (e.g. machine learning process) Excellent knowledge of Python includingPytorch, Tensorflow andSKLearn as well as initial knowledge of LangChain andRAGAS. Familiarity with CI/CD workflows is required and experience with containerisation and deployment using Docker/Kubernetes will be More ❯