26 to 50 of 114 Permanent Amazon SageMaker Jobs

Infra as Code: Terraform, CloudFormation Monitoring: Prometheus, Grafana, ELK Security & Compliance: Data protection and access control Nice-to-Haves AI/ML integration (PyTorch, HF etc.) MLOps (MLflow, Kubeflow, SageMaker) Vector search (Pinecone, pgvector, Weaviate, Qdrant etc.) Video ingestion pipelines & codecs 💡Don’t worry if you haven’t used these exact tools. If you’ve built and scaled similar More ❯

Infra as Code: Terraform, CloudFormation Monitoring: Prometheus, Grafana, ELK Security & Compliance: Data protection and access control Nice-to-Haves AI/ML integration (PyTorch, HF etc.) MLOps (MLflow, Kubeflow, SageMaker) Vector search (Pinecone, pgvector, Weaviate, Qdrant etc.) Video ingestion pipelines & codecs 💡Don’t worry if you haven’t used these exact tools. If you’ve built and scaled similar More ❯

Infra as Code: Terraform, CloudFormation Monitoring: Prometheus, Grafana, ELK Security & Compliance: Data protection and access control Nice-to-Haves AI/ML integration (PyTorch, HF etc.) MLOps (MLflow, Kubeflow, SageMaker) Vector search (Pinecone, pgvector, Weaviate, Qdrant etc.) Video ingestion pipelines & codecs 💡Don’t worry if you haven’t used these exact tools. If you’ve built and scaled similar More ❯

Delta Lake or Iceberg formats. Familiarity with semantic layer/ontology development for metadata-rich environments. Knowledge of AI/ML pipelines and integration with model-serving platforms (e.g., SageMaker, MLflow). Physical Requirements: Ability to sit for extended periods while working on a computer or during meetings. Must be able to travel occasionally to client sites or company More ❯

updates in development, integration and production environments. Set up, integrate, and maintain a scalable, stable set of CI/CD tools to support development, testing, and security scanning. Implement Amazon CloudWatch, Splunk and other third party monitoring solutions to provide continuous monitoring capabilities, track all aspects of the system, infrastructure, performance, application errors and roll up metrics. Analyze functional … with standard concepts, practices, and procedures such as NIST, FISMA, FedRamp and Common Criteria regulations and standards. Familiarity with the MLOps, machine learning lifecycle and product landscape, for example: Amazon SageMaker, Apache Airflow, Looker, Trifacta etc. You don't need to be an expert in all these. Working knowledge of Linux Professional Skills: Excellent communication and interpersonal skills More ❯

/Open Source) for cloud infrastructure automation. Proficiency with Databricks: clusters, jobs, notebooks, DBFS, and workspace management. Hands-on experience with MLOps tools (e.g., MLflow, TFX, Kubeflow, Airflow, or SageMaker Pipelines Experience deploying and scaling Large Language Models (LLMs) in production environments. Proficiency in CI/CD tooling (GitHub Actions, Azure DevOps, GitLab CI, etc. Scripting and automation using More ❯

higher certification. Willingness to do a programming challenge during the interview process. Experience with Jupyter Notebooks, Python Data Science Libraries. Experience with ML-OPS and related tools (e.g., MLFLOW, Sagemaker, Bedrock) and ability to build interactive, insightful dashboards for monitoring ML models. Place of Performance: Hybrid work in San Antonio, TX. Desired Skills (Optional) Experience with NOSQL databases such More ❯

in building robust, scalable solutions for operational deployment. Hands-on experience with machine learning frameworks (TensorFlow, PyTorch, scikit-learn) and tools for model development and operationalization (Jupyter, MLflow, AWS SageMaker) in production environments. Experienced working in Linux-based and hybrid cloud/on-prem infrastructures, deploying and maintaining AI/ML solutions in secure, production-grade environments; strong collaboration More ❯

updates in development, integration and production environments. Set up, integrate, and maintain a scalable, stable set of CI/CD tools to support development, testing, and security scanning. Implement Amazon CloudWatch, Splunk and other third party monitoring solutions to provide continuous monitoring capabilities, track all aspects of the system, infrastructure, performance, application errors and roll up metrics. Analyze functional … with standard concepts, practices, and procedures such as NIST, FISMA, FedRamp and Common Criteria regulations and standards. Familiarity with the MLOps, machine learning lifecycle and product landscape, for example: Amazon SageMaker, Apache Airflow, Looker, Trifacta etc. You don't need to be an expert in all these. Working knowledge of Linux Professional Skills: Excellent communication and interpersonal skills More ❯

and managing AI solutions in production environments. Proficiency in AI/ML frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn). Experience with cloud-based AI platforms (e.g., AWS SageMaker, Google Cloud AI Platform, Azure Machine Learning). Experience with data management and processing tools (e.g., Hadoop, Spark, SQL). Proficiency in programming languages such as Python and Java. More ❯

SQL and No SQL DB Building and maintaining CI/CD pipeline in Jenkins, Azure DevOps or GitHub actions and ML Ops pipeline in Azure ML, Azure AI Foundry, SageMaker or Vertex AI. IaC - Bicep, ARM, Terraform Have a good understanding of different machine learning techniques and ability to explain the methods in detail (regression, clustering, decision trees, reinforcement More ❯

Python Experience with machine learning, familiar with Huggingface, Pytorch, and similar ML tools and packages Familiarity with deploying and scaling ML models in the cloud, particularly with AWS and SageMaker Understanding of DevOps processes and tools: CI/CD, Docker, Terraform, and monitoring/observability Bonus: experience with vector databases, semantic search, or event-driven systems like Kafka Additional More ❯

scripting Experience with CI/CD tools and practices, including GitHub Actions or GitLab CI Experience with AWS services and Cloud-native architecture patterns, including ECS, Lambda, SQS, SNS, SageMaker, RDS, DynamoDB, IAM policies, security groups, or network security Experience with Infrastructure as Code, including AWS CDK, Terraform, or CloudFormation Experience with security scanning tools Active TS/SCI More ❯

Bachelor's degree Nice If You Have: Experience deploying analytics workloads on a platform as a service ( PaaS ) and sof tware as a service ( SaaS ) , including AWS EMR, Redshift, SageMaker, Databricks, SQL Data Warehouse, or machine learning service Experience with distributed or parallel programming frameworks, including Apache Spark or NVIDIA CUDA Experience with infrastructure as code frameworks and services More ❯

training techniques including fine-tuning, RLHF, parameter-efficient methods (LoRA/QLoRA), or custom post-training workflows MLOps experience : Knowledge and familiarity with MLOps frameworks and tools such as Sagemaker, Kedro, MLflow or Weights and Biases Energy Domain Knowledge: Background in power systems, energy dispatch optimisation, grid modelling, or other energy sector applications where AI/ML drives operational … proficiency with hands-on experience in AI/ML frameworks including RAG, LangChain, TensorFlow, and PyTorch Practical experience with Generative AI and exposure to leading LLM platforms (Anthropic, Meta, Amazon , OpenAI) Proficiency with essential data science libraries including Pandas, NumPy, scikit-learn, Plotly/Matplotlib, and Jupyter Notebooks Knowledge of ML-adjacent technologies, including AWS SageMaker, Kedro and More ❯

/ML Skills: Deep knowledge of at least one leading cloud platform (AWS, Azure, or Google Cloud Platform). Experience with cloud-native AI/ML services (e.g., AWS SageMaker, Azure ML, Google AI Platform), enabling secure integration and operationalization of models. Infrastructure as Code (Terraform, CloudFormation, ARM) and AI-powered IaC generation tools. Cloud security (IAM, encryption, compliance More ❯

services. Hands on experience with DevOps and engineering tools (GitLab, GitHub, Azure DevOps, Docker, Kubernetes). Proficiency with AI/ML and MLOps platforms (Databricks, Google Cloud Vertex AI, SageMaker). Familiarity with generative AI technologies and frameworks (OpenAI, Google Gemini, Hugging Face Transformers). Demonstrated success in developing and executing product strategies. Ability to lead and inspire cross More ❯

experience 10+ years of related software engineering experience. REQUIRED QUALIFICATIONS Experience with the following languages: Python, NodeJS Hands on experience working with technologies such as Nifi, Tensorflow, PyTorch, and Sagemaker Familiar with audio processing technologies such as Librosa, PyAudio Analysis or Open Smile. Familiar with text processing technologies such as NGTK, Spacy, or Stanford Core NLP Experience with cloud More ❯

your fingertips. Join us. The world can't wait. You Have: 5+ years of experience with AWS services and cloud-native architecture patterns such as ECS, Lambda, SQS, SNS, SageMaker, RDS, DynamoDB, IAM policies , security groups, and network security 3+ years of experience with containerization such as Docker, Kubernetes, ECS, and container orchestration 3+ years of experience with Authority More ❯

laws, and emerging technology Experience collaborating with data scientists and other AI related stakeholders Desired Skills: Experience with Python, R, SQL, Jupyter, MLOps, AI/ML services (e.g., AWS SageMaker, Amazon Q, Azure ML Studio, CoPilot Studio, Google BigQuery, Oracle ML) leveraging cloud service provider(s) (e.g., AWS, Azure, Oracle, and Google) Experience with designing, developing, and implementing More ❯

Looking For Must Have Practical experience deploying ML models into production environments Strong Python development skills and understanding of ML model structures Familiarity with tools such as MLflow, Airflow, SageMaker, or Vertex AI Understanding of CI/CD concepts and basic infrastructure automation Ability to write well-tested, maintainable, and modular code Strong collaboration skills and a growth mindset More ❯

turn insights into product features Ensure compliance, scalability, and reliability of ML systems Skills Required Proven experience with ML in production environments Strong skills in Python, SQL, and AWS (SageMaker, Lambda, etc.) Familiarity with MLOps and real-time data applications A pragmatic mindset and strong problem-solving ability Background in adtech or fraud detection is a bonus Desired Skills More ❯

turn insights into product features Ensure compliance, scalability, and reliability of ML systems Skills Required Proven experience with ML in production environments Strong skills in Python, SQL, and AWS (SageMaker, Lambda, etc.) Familiarity with MLOps and real-time data applications A pragmatic mindset and strong problem-solving ability Background in adtech or fraud detection is a bonus Desired Skills More ❯

turn insights into product features Ensure compliance, scalability, and reliability of ML systems Skills Required Proven experience with ML in production environments Strong skills in Python, SQL, and AWS (SageMaker, Lambda, etc.) Familiarity with MLOps and real-time data applications A pragmatic mindset and strong problem-solving ability Background in adtech or fraud detection is a bonus Desired Skills More ❯

business teams, and technology partners, ensuring alignment throughout the project lifecycle. Key Technical Skills & Tools AI & LLM Frameworks: LangChain, OpenAI APIs, Anthropic, LlamaIndex, AutoGPT, CrewAI Cloud Platforms: AWS (Bedrock, Sagemaker), Azure AI, GCP Vertex AI Languages: Python (primary), JavaScript/TypeScript (optional) Orchestration/Workflow: LangGraph, Haystack, Hugging Face, RAG pipelines MLOps/Deployment: Docker, Kubernetes, CI/CD More ❯