Amazon
Applied Scientist
At OpsTech Solutions (OTS), we are a technology centric services organization that designs, builds, and sustains the invisible, high-quality network, compute infrastructure and device scaffolding that empowers and protects Amazons global Operations. The OTS DataTech team drives enterprise data strategy and support across OTS. Our charter encompasses OTS-wide efforts, including Data as a Product (DaaP), enterprise data infrastructure, AI/ML capability, and supporting specific business-critical programs, fueling innovation and automation for OTS. We are looking for a passionate, talented, and innovative Applied Scientist with a background in developing and implementing state-of-the-art machine learning solutions within the realms of supervised and unsupervised learning, Generative AI (GenAI), and optimization. In this role, you will play a pivotal role in shaping the vision, roadmap, design, development, and implementation of science based solutions from beginning to end. Key responsibilities include: Building and maintaining an MLOps Platform that will support end-to-end scientific operations for a wide range of AI/ML use cases. Leveraging our foundational GenAI platform to help OTS customers build GenAI applications for their use cases. Partnering with a cross-functional team of stakeholders including Applied Scientists, Data Scientists, Machine Learning Engineers, Data Engineers, Product Managers, and Technical Program Managers. A day in the life Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: Medical, Dental, and Vision Coverage Maternity and Parental Leave Options Paid Time Off (PTO) 401(k) Plan If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. Basic Qualifications MS or PhD in quantitative field (CS, CE, ML preferred) or equivalent relevant work Strong background in machine learning, including supervised and unsupervised learning algorithms. Experience developing, building and implementing complex software systems, especially involving ML, that have been successfully delivered to customers. Knowledge of Generative AI and its applications. Proficiency in programming languages such as Python, Java, or C++. Strong communication skills, both written and verbal. Preferred Qualifications Experience with fine-tuning and deploying Large Language Models (LLMs) for customer facing GenAI applications. Experience with Infrastructure as Code (IaC) and AWS Cloud Development Kit (CDK). Experience with containerization and orchestration technologies (e.g., Docker, Kubernetes, Airflow) Experience with MLOps tools and frameworks (e.g., SageMaker, MLflow). Experience with ML frameworks (e.g., PyTorch, TensorFlow) and application development frameworks (e.g., LangChain). Experience with big data technologies (e.g., Hadoop, Spark). Knowledge of RAG and its applications. Experience with AWS technologies. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit
https://amazon.jobs/content/en/how-we-hire/accommodations
for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner. Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $136,000/year in our lowest geographic market up to $223,400/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit
https://www.aboutamazon.com/workplace/employee-benefits . This position will remain posted until filled. Applicants should apply via our internal or external career site.
At OpsTech Solutions (OTS), we are a technology centric services organization that designs, builds, and sustains the invisible, high-quality network, compute infrastructure and device scaffolding that empowers and protects Amazons global Operations. The OTS DataTech team drives enterprise data strategy and support across OTS. Our charter encompasses OTS-wide efforts, including Data as a Product (DaaP), enterprise data infrastructure, AI/ML capability, and supporting specific business-critical programs, fueling innovation and automation for OTS. We are looking for a passionate, talented, and innovative Applied Scientist with a background in developing and implementing state-of-the-art machine learning solutions within the realms of supervised and unsupervised learning, Generative AI (GenAI), and optimization. In this role, you will play a pivotal role in shaping the vision, roadmap, design, development, and implementation of science based solutions from beginning to end. Key responsibilities include: Building and maintaining an MLOps Platform that will support end-to-end scientific operations for a wide range of AI/ML use cases. Leveraging our foundational GenAI platform to help OTS customers build GenAI applications for their use cases. Partnering with a cross-functional team of stakeholders including Applied Scientists, Data Scientists, Machine Learning Engineers, Data Engineers, Product Managers, and Technical Program Managers. A day in the life Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: Medical, Dental, and Vision Coverage Maternity and Parental Leave Options Paid Time Off (PTO) 401(k) Plan If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. Basic Qualifications MS or PhD in quantitative field (CS, CE, ML preferred) or equivalent relevant work Strong background in machine learning, including supervised and unsupervised learning algorithms. Experience developing, building and implementing complex software systems, especially involving ML, that have been successfully delivered to customers. Knowledge of Generative AI and its applications. Proficiency in programming languages such as Python, Java, or C++. Strong communication skills, both written and verbal. Preferred Qualifications Experience with fine-tuning and deploying Large Language Models (LLMs) for customer facing GenAI applications. Experience with Infrastructure as Code (IaC) and AWS Cloud Development Kit (CDK). Experience with containerization and orchestration technologies (e.g., Docker, Kubernetes, Airflow) Experience with MLOps tools and frameworks (e.g., SageMaker, MLflow). Experience with ML frameworks (e.g., PyTorch, TensorFlow) and application development frameworks (e.g., LangChain). Experience with big data technologies (e.g., Hadoop, Spark). Knowledge of RAG and its applications. Experience with AWS technologies. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit
https://amazon.jobs/content/en/how-we-hire/accommodations
for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner. Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $136,000/year in our lowest geographic market up to $223,400/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit
https://www.aboutamazon.com/workplace/employee-benefits . This position will remain posted until filled. Applicants should apply via our internal or external career site.