176 to 200 of 441 PyTorch Jobs

software engineering and machine learning. Proven track record of deploying ML systems in production. A strong understanding of Machine Learning fundamentals. Strong experience with deep learning frameworks such as PyTorch or TensorFlow. Experience with training diffusion, transformer, or generative video models. Proficiency in Python. Experience building and maintaining scalable infrastructure (AWS, GCP, or custom solutions). Familiarity with CI/ More ❯

skills, with the ability to quickly become fluent in Python. Deep knowledge of core data science libraries (NumPy, Pandas, Scikit-Learn) and at least one deep learning framework (TensorFlow, PyTorch, or similar). High mathematical and statistical competence, with the ability to design new algorithms when needed. Experience leading teams to deliver innovative technical work on time, including project planning More ❯

the ability to write production-grade code Proficiency in core data science libraries (e.g. NumPy, Pandas, Scikit-learn) and familiarity with at least one deep learning framework (e.g. TensorFlow, PyTorch) A solid understanding of the full range of data science techniques, including supervised and unsupervised learning, Bayesian methods, NLP, time-series analysis, and SQL querying Ability to scope, design, and More ❯

the ability to write production-grade code Proficiency in core data science libraries (e.g. NumPy, Pandas, Scikit-learn) and familiarity with at least one deep learning framework (e.g. TensorFlow, PyTorch) A solid understanding of the full range of data science techniques, including supervised and unsupervised learning, Bayesian methods, NLP, time-series analysis, and SQL querying Ability to scope, design, and More ❯

the ability to write production-grade code Proficiency in core data science libraries (e.g. NumPy, Pandas, Scikit-learn) and familiarity with at least one deep learning framework (e.g. TensorFlow, PyTorch) A solid understanding of the full range of data science techniques, including supervised and unsupervised learning, Bayesian methods, NLP, time-series analysis, and SQL querying Ability to scope, design, and More ❯

the ability to write production-grade code Proficiency in core data science libraries (e.g. NumPy, Pandas, Scikit-learn) and familiarity with at least one deep learning framework (e.g. TensorFlow, PyTorch) A solid understanding of the full range of data science techniques, including supervised and unsupervised learning, Bayesian methods, NLP, time-series analysis, and SQL querying Ability to scope, design, and More ❯

engineering teams Deep experience deploying ML models into production environments Proficiency in designing scalable data pipelines and real-time inference systems Understanding of modern ML tooling and frameworks (e.g., PyTorch, TensorFlow, MLflow, AWS SageMaker) Strong cross-functional collaboration skills, particularly with data science and product teams Clear communication and an ability to prioritize for both experimentation and reliability Bonus Familiarity More ❯

innovating for continual improvement Provide primary operational support and engineering for multiple large-scale distributed software applications ️ Is this you? You have professional experience with: Model training Huggingface Transformers Pytorch vLLM TensorRT Infrastructure as code tools like Terraform Scripting languages such as Python or Bash Cloud platforms such as Google Cloud, AWS or Azure Git and GitHub workflows Tracing and More ❯

especially in customer-facing roles. Ability to work independently in a fast-paced, collaborative environment. Strong organization, planning and time management skills to achieve results Experience with Python, TensorFlow, PyTorch, or OpenCV. Preferred Exposure to embedded systems or real-time video processing. Understanding of fleet safety, telematics, or automotive camera systems. We offer a competitive salary and benefits package. Xirgo More ❯

Machine Learning engines (AWS, Azure, Google, etc.) Experiencewith large scale data processing tools (Spark, Hadoop, etc.) Abilityto query and program databases (SQL, No SQL) Experiencewith distributed ML frameworks (TensorFlow, PyTorch, etc.) Familiaritywith collaborative software tools (Git, Jira, etc.) Experiencewith user interface libraries/applications (Shiny, Django, etc.) Experiencein developing ML or statistical models in the field of pricing (e.g. priceelasticity More ❯

designing applications powered by Large Language Models and leading their implementation. Experience working with recommendation engines, data pipelines, or distributed machine learning. Experience with deep learning frameworks (e.g., TensorFlow, PyTorch, XGBoost). Knowledge of data warehousing concepts, including data warehouse technical architectures, infrastructure components, ETL/ELT and reporting/analytic tools and environments (e.g., Apache Beam, Hadoop, Spark, Pig More ❯

Bioinformatics, Computer Science, or a related technical field (MSc with significant experience also considered). Extensive experience in designing, training, debugging, and evaluating machine learning models using frameworks like PyTorch, TensorFlow, or JAX. Strong foundation in mathematics and statistics, including linear algebra, probability, and optimization. Excellent scientific writing and communication skills. Preferred Qualifications Experience in computational biology, genomics, or drug More ❯

Profile Essential skills: Bachelor/Master's/PhD or equivalent experience in Machine Learning, Computer Science, Maths, Data Science, or related field. Proficiency in deep learning frameworks like PyTorch/JAX. Strong Python software development skills (nice to have C other languages). Familiar with deep learning fundamentals: models, optimisation, evaluation and scaling. Capable of designing, executing and reporting More ❯

specialization in machine learning. • Experience with Python, and ideally also Scala or Java. • Experience in developing ML models for structured data. • Proficient with Machine learning frameworks such as Tensorflow, PyTorch, Spark MLlib. • Industry experience in designing and implementing large-scale machine learning-based recommender systems. • Industry experience in A/B testing, experimentation design and test analysis. • Strong coding, machine More ❯

inference, and time-series analysis An excellent proficiency of the basic libraries for data science (e.g. NumPy, Pandas, Scikit-Learn) and familiarity with a deep-learning framework (e.g. TensorFlow, PyTorch) Demonstrable experience enabling impactful change with AI within a financial services institution. Coupling that with prior experience in consulting would be a bonus. You possess proven experience leading data science More ❯

in designing, developing & deploying scalable backend systems. Familiarity with CICD, containerisation, deployment technologies & cloud platforms (Jenkins, Kubernetes, Docker, AWS) or Familiarity with Big Data and Machine Learning technologies (NumPy, PyTorch, TensorFlow, Spark). Excellent communication, collaboration & problem solving skills, ideally with some experience in agile ways of working. Security clearance: You must be able to gain and maintain the highest More ❯

developing and deploying perception algorithms (e.g., object detection, segmentation, tracking, SLAM, multi-sensor fusion) in real-world applications Proficiency in Python and C++ Experience with deep learning frameworks (e.g., PyTorch, TensorFlow) and MLOps tools/platforms Communication, interpersonal, and collaboration skills for working in a dynamic, cross-functional environment Company Statements Equal Opportunity Rivian is an equal opportunity employer and More ❯

Collaborate with data and software engineers to deliver integrated solutions. Degree in Computer Science, Engineering, or a related field. Hands-on experience with AI technologies and frameworks (e.g., TensorFlow, PyTorch). Proficiency in programming languages such as Python, Java, or C#. Experience with API design and management, as well as data integration techniques. Strong experience of setup of cloud services More ❯

implementing AI solutions in complex enterprise environments Experience in all architecture domains:- application, data, cloud ( AWS) and technology with expertise with AI, Gen Ai and ML frameworks (e.g., TensorFlow, PyTorch, AWS Sagemaker, AWS Bedrock, OpenAI). Strong experience of AI services and AI lifecycle and model training Proficiency in backend and frontend technologies such as .NET Core, Node.js, and React More ❯

high-throughput data pipelines and APIs using Go, Python, or similar. Hands-on NLP experience with both pre-built services (e.g., AWS Comprehend) and custom transformer models (Hugging Face, PyTorch, TensorFlow) with a strong grounding in evaluating NLP models using classification and ranking metrics, and experience running A/B or offline benchmarks. Proficient with MLOps and training infrastructure (MLflow More ❯

Deep expertise in at least two of the following: reinforcement learning, Bayesian optimisation, AI agents, LLMs, VLMs. Proficiency in Python and experience with at least one major ML framework (PyTorch, TensorFlow, or JAX). Ability to work in a fast-paced, research-oriented environment with ambiguous and evolving goals. Excellent problem-solving, collaboration, and communication skills. Ability to lead a More ❯

Bring: 10+ years of experience in AI/ML. B.S. in Physics, Engineering, or Computer Science (STEM). Advanced degree preferred. Experience: Expertise in machine learning frameworks such as PyTorch, TensorFlow, and JAX. Proficiency with reinforcement learning algorithms (PPO, SAC, DQN). Hands-on experience integrating AI with modeling and simulation tools (AFSIM, MDASim). Strong programming skills in Python More ❯

and use new tools and technologies. Nice to Haves: • Experience working with Kubernetes/OpenShift and containers. • Experience with AI and Machine Learning platforms, tools, and frameworks, such as PyTorch, LLaMA.cpp, vLLM, and Kubeflow. • Experience with writing and publication of research papers. • Understanding of DevOps methodology, Scrum, and/orJira. • Bachelor's degree or higher in Machine Learning (ML), Natural More ❯

Neocloud space. Practical knowledge of AI/ML technologies and their applications, including understanding language models (LLMs), and experience with training and fine-tuning LLMs using frameworks like TensorFlow, PyTorch, or Hugging Face Transformers. Good understanding of programming/scripting: (e.g., Python, Go) for customizing solutions, creating scripts, or automating tasks. Experience with AI relevant infrastructure, including Networking (InfiniBand and More ❯

Neocloud space. Practical knowledge of AI/ML technologies and their applications, including understanding language models (LLMs), and experience with training and fine-tuning LLMs using frameworks like TensorFlow, PyTorch, or Hugging Face Transformers. Good understanding of programming/scripting: (e.g., Python, Go) for customizing solutions, creating scripts, or automating tasks. Experience with AI relevant infrastructure, including Networking (InfiniBand and More ❯