5 Amazon Sagemaker Jobs

Principle Developer - ML/Prompt Engineer Technologies: Amazon Bedrock, RAG Models, Java, Python, C or C++, AWS Lambda, Responsibilities: Responsible for developing, deploying, and maintaining a Retrieval Augmented Generation (RAG) model in Amazon Bedrock, our cloud-based platform for building and scaling generative AI applications. Design and implement a RAG model that can generate natural language responses, commands, and actions based on user queries and context, using the Anthropic Claude model as the backbone. Integrate the RAG model with Amazon Bedrock, our platform that offers a choice of high-performing foundation models from leading AI companies and Amazon via a single API, along with a broad set of capabilities to build generative AI applications with security, privacy, and responsible AI. Optimize the RAG model for performance, scalability, and reliability, using best practices and robust engineering methodologies. Design, test, and optimize prompts to improve performance, accuracy, and alignment of large language models across diverse use cases. Develop and maintain reusable prompt templates, chains, and libraries to support scalable and consistent GenAI applications. Skills/Qualifications: Experience in programming with at least one software language, such as Java, Python, or C/C++. Experience in working with generative AI tools, models, and frameworks, such as Anthropic, OpenAI, Hugging Face, TensorFlow, PyTorch, or Jupyter. Experience in working with RAG models or similar architectures, such as RAG, Ragna, or Pinecone. Experience in working with Amazon Bedrock or similar platforms, such as AWS Lambda, Amazon SageMaker, or Amazon Comprehend. Ability to design, iterate, and optimize prompts for various LLM use cases (e.g., summarization, classification, translation, Q&A, and agent workflows). Deep understanding of prompt engineering techniques (zero-shot, few-shot, chain-of-thought, etc.) and their effect on model behavior. Familiarity with prompt evaluation strategies, including manual review, automatic metrics, and A/B testing frameworks. Experience building prompt libraries, reusable templates, and structured prompt workflows for scalable GenAI applications. Ability to debug and refine prompts to improve accuracy, safety, and alignment with business objectives. Awareness of prompt injection risks and experience implementing mitigation strategies. Familiarity with prompt tuning, parameter-efficient fine-tuning (PEFT), and prompt chaining methods. Familiarity with continuous deployment and DevOps tools preferred. Experience with Git preferred Experience working in agile/scrum environments Successful track record interfacing and communicating effectively across cross-functional teams. Good communication, analytical and presentation skills, problem-solving skills and learning attitude Mandatory Key Skills Amazon Bedrock,RAG Models,Java,Python,C++,AWS Lambda,RAG model,Anthropic, OpenAI,Hugging Face,TensorFlow,PyTorch,Jupyter,Amazon SageMaker, DevOps tools, Prompt Engineering*

Role Responsibilities: Build and deploy ML models using Amazon SageMaker Integrate AI/ML solutions with cloud/on-prem pipelines Apply GenAI techniques like neural networks and image processing Ensure production-grade quality in AI solutions Job Requirements: Proven expertise in Amazon SageMaker and ML frameworks Strong programming skills in Python (Java/C++ a plus) Experience with GenAI tools and AI cloud services Understanding of model lifecycle, from training to deployment

Responsibilities : 1. Strategic Leadership : a. Define and drive the overall ML Ops strategy and roadmap for the organization, aligning it with business objectives and technical capabilities. b. Oversee the design, development, and implementation of ML Ops platforms, frameworks, and processes. c. Foster a culture of innovation and continuous improvement within the ML Ops team. 2. Technical Architecture : a. Design and implement scalable, reliable, and efficient ML Ops architectures. b. Select and integrate appropriate tools, technologies, and frameworks to support the ML lifecycle. c. Ensure compliance with industry best practices and standards for ML Ops. 3. Team Management : a. Lead and mentor a team of ML Ops engineers and architects. b. Foster collaboration and knowledge sharing among team members. c. Provide technical guidance and support to data scientists and engineers. 4. Innovation and Research : a. Stay up-to-date with emerging ML Ops trends and technologies. b. Research and evaluate new tools and techniques to enhance ML Ops capabilities. c. Contribute to the development of innovative ML Ops solutions. Minimum Required Skills : - 11+ years of experience preferred. - Proven track record of designing and implementing large-scale ML pipelines and infrastructure. - Experience with distributed computing frameworks (Spark, Hadoop) - Knowledge of graph databases and auto ML libraries - Bachelor's / Master's degree in computer science, analytics, mathematics, statistics - Strong experience in Python, SQL. - Solid understanding and knowledge of containerization technologies (Docker, Kubernetes). - Proficient in Experience in CI/CD pipelines, model monitoring, and MLOps platforms (Kubeflow, MLFlow) - Proficiency in cloud platforms, containerization, and ML frameworks (TensorFlow, PyTorch). - Certifications in cloud platforms or ML technologies can be a plus. - Extensive experience with cloud platforms (AWS, GCP, Azure) and containerization technologies (Docker, Kubernetes). - Strong problem-solving and analytical skills. - Ability to plan, execute and take ownership of task. Keywords : - ML Ops / MLOps Architect - Azure DevOps - Docker - Kubernetes - TensorFlow - MLFlow - Pipeline - Machine Learning Platform Engineer - Data Science Platform Engineer - DevOps Engineer (with ML focus) - AI Engineer - Data Engineer - Cloud Engineer (with ML focus) - Software Engineer (with ML focus) - Model Deployment Specialist - MLOps Architect - CI/CD - PyTorch - Scikit-learn - Cloud Computing - Big Data - Azure - Azure Machine Learning - GCP - Vertex AI - AWS - Amazon SageMaker

Overview of the Role: We have an outstanding opportunity for an expert AI and Data Cloud Solutions Engineer to work with our trailblazing customers in crafting ground-breaking customer engagement roadmaps demonstrating the Salesforce applications, platform across the machine learning and LLM/GPT domains in India! The successful applicant will have a track record in driving business outcomes through technology solutions, with experience in engaging at the C-level with Business and Technology groups.' Responsibilities: Primary pre-sales technical authority for all aspects of AI usage within the Salesforce product portfolio - existing Einstein ML based capabilities and new (2023) generative AI Majority of time (60%+) will be customer/external facing Evangelisation of Salesforce AI capabilities Assessing customer requirements and use cases and aligning to these capabilities Solution proposals, working with Architects and wider Solution Engineer (SE) teams Building reference models/ideas/approaches for inclusion of GPT based products within wider Salesforce solution architectures, especially involving Data Cloud Alignment with customer security and privacy teams on trust capabilities and values of our solution(s) Presenting at multiple customer events from single account sessions through to major strategic events (World Tour, Dreamforce) Representing Salesforce at other events (subject to PM approval) Sales and SE organisation education and enablement e.g. roadmap - all roles across all product areas Bridge/primary contact point to product management Provide thought leadership in how large enterprise organisation can drive customer success through digital transformation. Ability to uncover the challenges and issues a business is facing by running successful and targeted discovery sessions and workshops. Be an innovator who can build new solutions using out-of-the-box thinking. Demonstrate business value of our AI solutions to business using solution presentations, demonstrations and prototypes. Build roadmaps that clearly articulate how partners can implement and accept solutions to move from current to future state. Deliver functional and technical responses to RFPs/RFIs. Work as an excellent teammate by chipping in, learning and sharing new knowledge. Demonstrate a conceptual knowledge of how to integrate cloud applications to existing business applications and technology. Lead multiple customer engagements concurrently. Be self-motivated, flexible, and take initiative.| Required Qualifications: Experience will be evaluated based on the core proficiencies of the role. 4+ years working directly in the commercial technology space with AI products and solutions. Data knowledge - Data science, Data lakes and warehouses, ETL, ELT, data quality AI knowledge - application of algorithms and models to solve business problems (ML, LLMs, GPT) 10+ years working in a sales, pre-sales, consulting or related function in a commercial software company Strong focus and experience in pre-sales or implementation is required. Experience in demonstrating Customer engagement solution, understand and drive use cases, customer journeys, ability to draw Day in life of across different LOBs. Business Analysis/ Business case/return on investment construction. Demonstrable experience in presenting and communicating complex concepts to large audiences A broad understanding of and ability to articulate the benefits of CRM, Sales, Service and Marketing cloud offerings Strong verbal and written communications skills with a focus on needs analysis, positioning, business justification, and closing techniques. Continuous learning demeanor with a demonstrated history of self enablement and advancement in both technology and behavioural areas. Preferred Qualifications: expertise in an AI related subject (ML, deep learning, NLP etc.) Familiar with technologies such as OpenAI, Google Vertex, Amazon Sagemaker, Snowflake, Databricks etc

Overview of the Role: We have an outstanding opportunity for an expert AI and Data Cloud Solutions Engineer to work with our trailblazing customers in crafting ground-breaking customer engagement roadmaps demonstrating the Salesforce applications, platform across the machine learning and LLM/GPT domains in India! The successful applicant will have a track record in driving business outcomes through technology solutions, with experience in engaging at the C-level with Business and Technology groups. Responsibilities: Primary pre-sales technical authority for all aspects of AI usage within the Salesforce product portfolio - existing Einstein ML based capabilities and new (2023) generative AI Majority of time (60%+) will be customer/external facing Evangelisation of Salesforce AI capabilities Assessing customer requirements and use cases and aligning to these capabilities Solution proposals, working with Architects and wider Solution Engineer (SE) teams Building reference models/ideas/approaches for inclusion of GPT based products within wider Salesforce solution architectures, especially involving Data Cloud Alignment with customer security and privacy teams on trust capabilities and values of our solution(s) Presenting at multiple customer events from single account sessions through to major strategic events (World Tour, Dreamforce) Representing Salesforce at other events (subject to PM approval) Sales and SE organisation education and enablement e.g. roadmap - all roles across all product areas Bridge/primary contact point to product management Provide thought leadership in how large enterprise organisation can drive customer success through digital transformation. Ability to uncover the challenges and issues a business is facing by running successful and targeted discovery sessions and workshops. Be an innovator who can build new solutions using out-of-the-box thinking. Demonstrate business value of our AI solutions to business using solution presentations, demonstrations and prototypes. Build roadmaps that clearly articulate how partners can implement and accept solutions to move from current to future state. Deliver functional and technical responses to RFPs/RFIs. Work as an excellent teammate by chipping in, learning and sharing new knowledge. Demonstrate a conceptual knowledge of how to integrate cloud applications to existing business applications and technology. Lead multiple customer engagements concurrently. Be self-motivated, flexible, and take initiative.| Required Qualifications: Experience will be evaluated based on the core proficiencies of the role. 4+ years working directly in the commercial technology space with AI products and solutions. Data knowledge - Data science, Data lakes and warehouses, ETL, ELT, data quality AI knowledge - application of algorithms and models to solve business problems (ML, LLMs, GPT) 10+ years working in a sales, pre-sales, consulting or related function in a commercial software company Strong focus and experience in pre-sales or implementation is required. Experience in demonstrating Customer engagement solution, understand and drive use cases, customer journeys, ability to draw Day in life of across different LOBs. Business Analysis/ Business case/return on investment construction. Demonstrable experience in presenting and communicating complex concepts to large audiences A broad understanding of and ability to articulate the benefits of CRM, Sales, Service and Marketing cloud offerings Strong verbal and written communications skills with a focus on needs analysis, positioning, business justification, and closing techniques. Continuous learning demeanor with a demonstrated history of self enablement and advancement in both technology and behavioural areas. Preferred Qualifications: expertise in an AI related subject (ML, deep learning, NLP etc.) Familiar with technologies such as OpenAI, Google Vertex, Amazon Sagemaker, Snowflake, Databricks etc