76 to 100 of 243 PyTorch Jobs

experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production ...

/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 in healthcare ...

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 (e.g. Power ...

model deployment pipelines (including edge inference) Improve CI/CD workflows for ML systems and automate infrastructure Key Requirements: Strong Python and experience with PyTorch-based training pipelines Experience with distributed training (DDP, FSDP, DeepSpeed) Solid cloud experience (GCP/AWS/Azure) Hands-on with Docker and infrastructure ...

Hands-on with; LLMs (OpenAI, Llama, Claude, Mistral), Vector DBs (Pinecone, Weaviate, FAISS), Frameworks (LangChain, LlamaIndex, AutoGen, CrewAI, LangGraph) Strong Python + ML frameworks (PyTorch/TensorFlow) Experience deploying on AWS, Azure, or GCP Experience leading or influencing technical teams Nice to have: Experience in consulting/client-facing roles ...

Azure, GCP) with Generative AI services Experience of managing teams of 15-20 people Ideally you will have strong technical understanding within Python, PyTorch, TensorFlow, and specialised Generative AI libraries SC Cleared is essential as a minimum Within this role, you will be responsible for: Determine where AI adds genuine ...

reviews, and testing strategies. Identify performance or reliability bottlenecks and propose improvements. Required Qualifications & Experience Strong experience with Python and Django. Familiarity with Torch (PyTorch) for analytical or ML workloads. Proficiency in SGLang or willingness to learn domain-specific languages. A keen sense of system design and desire to build ...

Backend: 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 ...

following technologies: Java, Python, Data engineering, Data and Database engineering, Agentic AI, Gen AI, Machine Leaning, Generative AI, Scripting, Spark, Hadoop, SQL, NoSQL, PyTorch and one of the cloud technologies like AWS, Azure or GCP. Should have worked in at least two or more industry domains. Should have a good ...

evaluation, data annotation and curation, training pipelines, performance optimisation, edge ML, MLOps, deployment and maintenance of ML solutions, Python development, Python-based ML frameworks, PyTorch, TensorFlow, sklearn, OpenCV, NumPy, feature development, code review, pytest, linting, bug fixing, relational databases, database design and maintenance, AWS/cloud infrastructure, CI/ ...

experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production ...

experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production ...

experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production ...

experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production ...

experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production ...

experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production ...

experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production ...

experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production ...

experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production ...

experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production ...

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 You must ...

Strong experience in Python and SQL, including libraries such as Pandas, NumPy and scikit-learn. Experience working with deep learning frameworks such as PyTorch or TensorFlow. A solid grounding in statistics and probability, with strong mathematical foundations (calculus and linear algebra highly advantageous). Experience working across the full data ...

tooling 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 ...

Lead Machine Learning Engineer (MLOps, KServe + building Kubernetes Clusters, PyTorch, TensorFlow on AWS) As a Capital One Machine Learning Engineer (MLE) , you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You'll participate in the detailed technical design, development … ready data pipelines that feed ML models 3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 2+ years of experience developing performant, resilient, and maintainable code 2+ years of experience with data gathering and preparation ...

Lead Machine Learning Engineer (MLOps, KServe + building Kubernetes Clusters, PyTorch, TensorFlow on AWS) As a Capital One Machine Learning Engineer (MLE) , you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You'll participate in the detailed technical design, development … ready data pipelines that feed ML models 3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 2+ years of experience developing performant, resilient, and maintainable code 2+ years of experience with data gathering and preparation ...