201 to 225 of 403 PyTorch Jobs

Reliable LLM/RAG/Agentic systems Bonus Points: Experience with fine-tuning embedding models Published papers in NLP, representation learning, or related fields Familiarity with modern ML frameworks (PyTorch, TensorFlow, Hugging Face) Experience with vector databases and similarity search systems What You’ll Work On: Design and implement advanced semantic caching systems Develop and optimize embedding-based retrieval mechanisms More ❯

Experience JavaScript/TypeScript, with experience in MERN Stack (MongoDB, Express.js, React.js, Node.js or similar..) Strong proficiency in Python, particularly for AI and ML applications. Hands-on experience with PyTorch, GenAI, and reasoning models. Experience implementing RAG architectures in production environments. Solid understanding of both SQL and NoSQL databases Experience building and consuming APIs; familiarity with CI/CD practices. More ❯

Experience JavaScript/TypeScript, with experience in MERN Stack (MongoDB, Express.js, React.js, Node.js or similar..) Strong proficiency in Python, particularly for AI and ML applications. Hands-on experience with PyTorch, GenAI, and reasoning models. Experience implementing RAG architectures in production environments. Solid understanding of both SQL and NoSQL databases Experience building and consuming APIs; familiarity with CI/CD practices. More ❯

in Mathematics, Computer Science, Artificial Intelligence, _ ideally a Masters Strong mathematical foundation, especially in algebra, number theory, and statistics. Proficiency in Python and familiarity with machine learning frameworks (e.g., PyTorch, TensorFlow). Understanding of NLP, computer vision, and retrieval methods. Ability to turn theory into practical, deployable systems. Desirable Experience with Microsoft Azure or other cloud platforms. Knowledge of vector More ❯

a proven commercial experience delivering AI/ML projects end-to-end in production environments Strong Python skills with hands-on use of ML libraries like Scikit-learn, TensorFlow, PyTorch, or Hugging Face Solid understanding of machine learning fundamentals and performance evaluation techniques Experience working in cloud platforms (AWS, GCP, or Azure) with MLOps tools (e.g. MLflow, SageMaker, Vertex AI More ❯

cross-functional teams to turn real-world problems into working software. 🛠️ What You Bring: Fluency in Python and strong grasp of ML/DL concepts. Experience with frameworks like PyTorch, TensorFlow, Scikit-learn, and HuggingFace Transformers. Comfort designing production-ready AI systems—optimising for speed, cost, and value. Passion for leveraging AI assistants and agentic tools to maximise impact. Bonus More ❯

cross-functional teams to turn real-world problems into working software. 🛠️ What You Bring: Fluency in Python and strong grasp of ML/DL concepts. Experience with frameworks like PyTorch, TensorFlow, Scikit-learn, and HuggingFace Transformers. Comfort designing production-ready AI systems—optimising for speed, cost, and value. Passion for leveraging AI assistants and agentic tools to maximise impact. Bonus More ❯

you'll bring: Experience in Data Science, or a related field Solid skills in Python and SQL for data manipulation and modelling Familiarity with ML libraries like Scikit-learn, PyTorch or TensorFlow Awareness of cloud platforms (Azure, AWS, or GCP) and data governance practices A strong analytical mindset, team spirit, and eagerness to learn from senior peers To speak in More ❯

team. Development of VBA/Python tools to expediate the change management review process. Skills Knowledge and Experience Technical Skills: Proficiency in Python, including ML libraries such as TensorFlow, PyTorch, Scikit-learn, Keras, etc. Expert Level in programming such as VBA, Python, JAVA and other coding tools. Familiarity with data processing, feature engineering, and model evaluation techniques. Soft Skills: Strong More ❯

statistical analysis and proven experience applying a range of machine learning techniques to solve business problems (e.g., regression, classification, clustering, time-series forecasting). Practical experience with Keras or PyTorch is required. Full-Stack Deployment: Demonstrable experience taking models to production, including building and deploying APIs with FastAPI and using Vertex AI for ML workflows. Visualization & Communication: Ability to create More ❯

with a strong interest and practical experience in applied AI or machine learning. Strong programming skills in Python (or similar languages) with familiarity in AI/ML libraries (TensorFlow, PyTorch, etc.). Experience working with large-scale models (LLM/VLM) and deploying AI-driven solutions into production. Solid understanding of cloud technologies, containerization, and building scalable AI applications. Ability More ❯

NLP, Information Retrieval, or Conversational AI Experience with large language models and retrieval-augmented generation Research background in conversational systems or dialogue management Experience with modern deep learning frameworks (PyTorch, TensorFlow) Excellent written and verbal communication skills PREFERRED QUALIFICATIONS Knowledge of multi-agent systems and tool-use frameworks Experience with e-commerce or shopping domain applications Publications at top venues More ❯

Master's, PhD or equivalent experience in a technical field (e.g., Maths, Statistics, Computer Science, Physics, Chemistry, Biomedical Engineering). Python programming in a modern deep learning framework, e.g. PyTorch or JAX. Familiar with deep learning fundamentals: models, optimisation, evaluation and scaling. Capable of designing, executing and reporting from ML experiments. Mathematics skills to support the above: calculus, probability theory More ❯

field. Strong familiarity with Linux and the open-source ecosystem. Proficient experience working with machine learning and large datasets. In-depth understanding of open source machine learning frameworks (e.g., PyTorch, ggml, llama.cpp, vllm). Experience building complex systems on the cloud. Experience building and optimizing distributed systems and large-data applications, including those using tensor accelerators or GPUs. Strong analytical More ❯

from exploratory data analysis and model prototyping to production deployment, integration, and ongoing monitoring. You are proficient in Python and its data/ML ecosystem (e.g. pandas, scikit-learn, PyTorch, TensorFlow), and you can apply statistical and machine learning techniques confidently in real-world settings. You have deployed models into live systems and understand how to make ML operational - whether More ❯

Experience designing systems in modern cloud environments (e.g. AWS, GCP) Technologies and Tools Python ML and MLOps tooling (e.g. SageMaker, Databricks, TFServing, MLflow) Common ML libraries (e.g. scikit-learn, PyTorch, TensorFlow) Spark and Databricks AWS services (e.g. IAM, S3, Redis, ECS) Shell scripting and related developer tooling CI/CD tools and best practices Streaming and batch data systems (e.g. More ❯

across multiple teams. Demonstrable experience designing and building AI-based solutions and/or AI platforms at scale. Familiarity with AI/ML tools, frameworks, and platforms (e.g., TensorFlow, PyTorch, ML Flow, Data Bricks Azure/AWS/GCP AI services). Track record of delivering production-grade AI applications or integrating AI capabilities into existing platforms. Demonstrable understanding of More ❯

Kernel, AI Foundry, or similar. Experience with tools for automated testing and evaluation of AI outputs is a plus. Experience in Python and AI frameworks/tools such as PyTorch and TensorFlow. Core Skills and Qualifications: 6+ years of experience in software engineering, with at least 2 years focused on building or integrating AI/ML solutions. Hands-on experience More ❯

and/or Semantic Kernel. Experience with tools for automated testing and evaluation of AI outputs is a plus. Experience in Python and AI frameworks/tools such as PyTorch and TensorFlow. Core Skills and Qualifications: 8+ years of professional software engineering experience, including 3+ years working directly on AI/ML systems or platforms. Hands-on experience with Microsoft More ❯

environments. Proficient in machine learning techniques (supervised, unsupervised, reinforcement learning) and deep learning architectures (CNNs, RNNs, Transformers). Strong in Python (required); experience with ML libraries such as TensorFlow, PyTorch, Scikit-learn, and Keras. Working knowledge of cloud-native AI/ML services on AWS, Azure, or Google Cloud (e.g., SageMaker, Azure ML, Vertex AI). Understanding of AI red More ❯

a Machine Learning Engineer or Data Scientist, with a focus on building and deploying machine learning models. Strong proficiency in Databricks ML and other relevant tools such as TensorFlow, PyTorch, or scikit-learn. Solid understanding of machine learning algorithms, statistical modeling, and data preprocessing techniques. Experience working with big data technologies such as Apache Spark is a plus. Excellent communication More ❯

translate business needs into technical solutions. Requirements At least 3 years of experience in applied machine learning and deploying production models. Proficiency in Python, SQL, and frameworks like TensorFlow, PyTorch, or scikit-learn. Experience with AWS services and Databricks; understanding of ML Ops is highly beneficial. Ability to adapt quickly to new tools and deliver scalable solutions independently. Familiarity with More ❯

field and 2 years of experience. Full term of experience must include: Amazon Web Services tools such as SageMaker, Glue, Lambda or other similar platforms; Snowflake, R, PySpark, Spark, PyTorch, TensorFlow, Docker, Jenkins; Object-oriented programming with Python; Version control systems such as Git; and Data visualization tools and packages (Tableau or similar). The position is eligible for the More ❯

on experience in both machine learning engineering (training ML models), and who have full-stack SWE experience - both backend and frontend engineering. Ideal candidates should have experience with Python, Pytorch, JS and React and similar frameworks. Responsibilities: Carry out software development and research for designing automated LLM agents for coding, ML engineering and research tasks, including building agent analysis tools More ❯

research focus (PhD or MSc with equivalent industry experience) Experience working with LLMs, speech technologies (ASR, TTS), or multimodal systems Strong programming skills in Python, with experience in using PyTorch Hands-on experience with training and fine-tuning ML models, including setting up experiments and evaluating results Ability to read, interpret, and implement techniques from recent academic papers into practical More ❯