51 to 75 of 161 Permanent TensorFlow Jobs

MLOps and AIOps infrastructure and tooling. Proficient in problem-solving and analytical reasoning. Exceptional communication and collaboration skills. Experience with ML frameworks such as TensorFlow, PyTorch, TensorRT, or ONNX. Experience with Large Language Models, including RAG and fine-tuning techniques. Familiarity with compute infrastructure necessary to support operating ...

numerical optimization with experience in programming languages such as Python (primary), Java and SQL Familiarity with deep learning tools and frameworks such as TensorFlow, Pytorch, Jax, Hugging libraries etc. Expert knowledge with traditional (tabular) ML modeling and methods. Proven proficiency in deep learning methodologies, fine tuning, and transformer architectures. ...

numerical optimization with experience in programming languages such as Python (primary), Java and SQL Familiarity with deep learning tools and frameworks such as TensorFlow, Pytorch, Jax, Hugging libraries etc. Expert knowledge with traditional (tabular) ML modeling and methods. Proven proficiency in deep learning methodologies, fine tuning, and transformer architectures. ...

trade‐offs in production systems. Solid grounding in ML/DL concepts, with hands‐on experience applying frameworks such as PyTorch and/or TensorFlow, including embeddings and model fine‐tuning where appropriate. Experience deploying and operating production Gen AI systems, leveraging Docker, cloud‐native architecture, production APIs ...

industry experience, or an MS with significant industry or research experience in the field Extensive experience with machine learning and deep learning toolkits (e.g.: TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas) Ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance ...

Representation Learning: Deep understanding of embedding generation, deep semantic retrieval, and multi-modal representation learning. Technical Stack: Mastery of Python and deep learning frameworks (TensorFlow, PyTorch) alongside hands-on experience with distributed computing (Spark, Ray) and cloud infrastructure (AWS/GCP). Graph Neural Networks (GNNs): Strong experience applying ...

models on Databricks. Familiarity with cloud‐based application development (AWS & Azure). Familiarity with one or more ML frameworks and technologies: scikit‐learn, xgboost, TensorFlow, PyTorch, Spark, SageMaker, Vertex AI, Kubeflow, Seldon, Triton. Strong communication skills, able to express ideas clearly and collaborate across teams. #J-18808-Ljbffr ...

Science or related technical field, or equivalent experience in software and site reliability engineering. Preferred experience with distributed ML frameworks such as Horovod or TensorFlow Distributed, familiarity with data engineering pipelines such as Apache Airflow or Spark, and knowledge of chaos engineering tools and compliance frameworks such as GDPR ...

Writing maintainable and reusable code Hands-on experience developing, tuning, and deploying machine learning models using frameworks and libraries such as: Scikit-learn XGBoost TensorFlow PyTorch Equivalent machine learning frameworks Strong analytical and problem-solving capabilities with a scientific and data-driven mindset. Ability to translate complex technical concepts ...

familiarity with good software engineering practices. Excellent written and verbal communication. Strong experience developing, testing machine learning solutions using frameworks such as TensorFlow, PyTorch or scikit‐learn. Solid intuitive grasp of fundamental concepts from probability, statistics, linear algebra and calculus. Collaborative, humble and enthusiastic attitude. Preferred Qualifications, Capabilities ...

familiarity with good software engineering practices Excellent written and verbal communication Strong experience developing, testing machine learning solutions using frameworks such as TensorFlow, PyTorch or scikit-learn Solid intuitive grasp of fundamental concepts from probability, statistics, linear algebra and calculus Collaborative, humble and enthusiastic attitude Preferred qualifications, capabilities ...

equivalent experience in Computer Science, Maths, Machine Learning, Data Science, or related field. Desirable: Exposure to machine learning frameworks such as PyTorch, JAX, Triton, TensorFlow Experience with distributed workload management systems such as Kubernetes, VLLM, Keras or MLOps pipelines Experience working with hardware simulators or emulators (e.g. QEMU). ...

programming skills in Python , Rust, or similar; and strong software engineering fundamentals building performant and reliable systems. Proficient in deep learning frameworks (Pytorch, JAX, TensorFlow). You can work on different layers of the stack from low-level training backends, data ingestion to ML/RL algorithmic design ...

Computer Science, Electrical Engineering, Control Systems, or a related field Experience across a spectrum of libraries, frameworks and services : such as ML libraries e.g. TensorFlow or PyTorch model servers such as AWS Bedrock MLOps such as ML Flow or Sagemaker agent/AI orchestration such as LangGraph ...

research environments. Strong understanding of Machine Learning techniques and architectures, including Generative AI, Transformers and neural networks. Python and common Data Science libraries. TensorFlow, PyTorch or similar machine learning frameworks. AWS, Azure or Google Cloud AI and Data Science services. Ability to work effectively with technical and non-technical ...

research environments. Strong understanding of Machine Learning techniques and architectures, including Generative AI, Transformers and neural networks. Python and common Data Science libraries. TensorFlow, PyTorch or similar machine learning frameworks. AWS, Azure or Google Cloud AI and Data Science services. Ability to work effectively with technical and non-technical ...

management Requirements Python AWS LangChain LangGraph Retrieval Augmented Generation (RAG) Vector databases MLOps Production Machine Learning platforms AI governance and engineering best practice PyTorch, TensorFlow or Scikit-learn Contract £750-900 per day (inclusive) Initial 6 months with long-term programme roadmap Inside IR35 London (3 days per week ...

again. Proven track record delivering impactful ML/AI solutions in production. Deep expertise in Python and modern AI/ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn, NumPy, Pandas). Hands-on experience with GenAI, agentic AI, and automated testing for AI systems. Curiosity and creativity to challenge assumptions ...

Computer Science or a closely related discipline Strong software development experience using Python Hands-on experience with Machine Learning frameworks such as PyTorch or TensorFlow Experience working with Large Language Models (LLMs), Knowledge Graphs, Graph Machine Learning or Natural Language Processing Experience developing AI prototypes, proof-of-concept solutions ...

/ML Engineers build, evaluate, and deploy machine‐learning systems at scale. The day‐to‐day work combines data preprocessing, model training (PyTorch, TensorFlow), evaluation against business or research metrics, and production deployment (FastAPI, Triton, Ray) with monitoring. The role increasingly overlaps with MLOps (model deployment, monitoring, retraining infrastructure ...

Computer Science (or equivalent proven track record). 4 + years working on large‐scale ML codebases. Hands‐on with PyTorch, JAX or TensorFlow; comfortable with distributed training (DeepSpeed/FSDP/SLURM/K8s). Experience in deep learning, NLP or LLMs; bonus for CUDA or data‐pipeline ...

WHAT YOU BRING Production‐Level AI Expertise: Proven success building, deploying, and maintaining complex AI/ML solutions, modern AI frameworks (such as Python, TensorFlow, PyTorch, or LangChain), and cloud‐native AI platforms (AWS, Azure, or GCP). Distributed Systems Mastery: Deep technical capability in structuring data platforms, data ...

WHAT YOU BRING Production‐Level AI Expertise: Proven success building, deploying, and maintaining complex AI/ML solutions, modern AI frameworks (such as Python, TensorFlow, PyTorch, or LangChain), and cloud‐native AI platforms (AWS, Azure, or GCP). Distributed Systems Mastery: Deep technical capability in structuring data platforms, data ...

Hands‐on LLM/ML systems experience: fine‐tuning models, building inference pipelines, optimisation for latency/cost, evaluation of model performance; comfortable with TensorFlow, PyTorch, Triton and productionising ML. Technical depth and breadth: T‐shaped expertise in at least one area (ML infrastructure, backend systems, performance optimisation) with ...

related technical field or bring equivalent experience in software and site reliability engineering. Preferred: Experience with distributed ML frameworks such as Horovod or TensorFlow Distributed. Familiarity with data engineering pipelines such as Apache Airflow or Apache Spark. Knowledge of chaos engineering tools and compliance frameworks such as GDPR ...