Jobs at Amazon in United States, Jersey City

Key job responsibilities
• Translate ambiguous problems into well defined mathematical problems• Prototype, test, and implement state-of-the-art algorithms for antenna pointing calibration, anomaly detection, predictive failure models, and ground terminal performance evaluation• Provide actionable recommendations for system design/definition by defining, running, and summarizing physically-accurate simulations of ground terminal functionality• Collaborate closely with engineers to deploy performant, scalable, and maintainable applications in the cloudExport Control Requirement:
A day in the life• Design, development, deployment, and support of a Tier-1 Monitoring and Remediation System (MARS) needed to maintain high availability of hundreds of ground terminals deployed around the world• Ground systems integration/test (I&T) automation• Ground terminal configuration, provisioning, and acceptance automation• Systems analysis• Algorithm development (pointing/tracking/calibration/monitoring)• Software interface definition for supplier-provided hardware and development of software test automation

- Master's degree or above in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field
- 4+ years of deep learning, computer vision, human robotic interaction, algorithms implementation experience
- Experience in statistics methodology, applications to business problems or big data
- Experience with statistical methods (e.g., A/B Testing, Regression)

- Experience in new hardware product development
- Knowledge of one or more ML Frameworks (e.g., PyTorch, TensorFlow) and ML methods including NLP models (BERT, GPT-2/3), computer vision-based models (object detection, image recognition), and text-based models (Seq2Seq, Topic modeling)
- Experience with cloud computing technologies
- Knowledge of data structures, algorithm design, statistics, and system design
- Experience in calibration and anomaly detection
- Expert science/data science development experience in Python

Key job responsibilities

- 3+ years of non-internship professional software development experience
- 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- Experience programming with at least one software programming language

- 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Bachelor's degree in computer science or equivalent

Possessing a deep understanding of AWS products and services, as a Delivery Consultant you will be proficient in architecting complex, scalable, and secure solutions tailored to meet the specific needs of each customer. You’ll work closely with stakeholders to gather requirements, assess current infrastructure, and propose effective migration strategies to AWS. As trusted advisors to our customers, providing guidance on industry trends, emerging technologies, and innovative solutions, you will be responsible for leading the implementation process, ensuring adherence to best practices, optimizing performance, and managing risks throughout the project.
Key job responsibilities
As an experienced technology professional, you will be responsible for:- Providing technical guidance and implementation support throughout project delivery, with a focus on using AWS AI/ML services
- Collaborating with customer stakeholders to gather requirements and propose effective model training, building, and deployment strategies- Sharing knowledge within the organization through mentoring, training, and creating reusable artifacts
About the team
About AWS:
Diverse Experiences: AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job below, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.Mentorship & Career Growth - We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

- 8+ years of cloud based solution (AWS or equivalent), system, network and operating system experience
- 5+ years of experience hosting and deploying GenAI/ML solutions (e.g., for data pre-processing, training, deep learning, fine tuning, and inferences) or/and Data Science Experience
- 8+ years of coding, data querying languages (e.g. SQL), scripting languages (e.g. Python)

Possessing a deep understanding of AWS products and services, as a Delivery Consultant you will be proficient in architecting complex, scalable, and secure solutions tailored to meet the specific needs of each customer. You’ll work closely with stakeholders to gather requirements, assess current infrastructure, and propose effective migration strategies to AWS. As trusted advisors to our customers, providing guidance on industry trends, emerging technologies, and innovative solutions, you will be responsible for leading the implementation process, ensuring adherence to best practices, optimizing performance, and managing risks throughout the project.
Key job responsibilities
As an experienced technology professional, you will be responsible for:- Providing technical guidance and implementation support throughout project delivery, with a focus on using AWS AI/ML services
- Collaborating with customer stakeholders to gather requirements and propose effective model training, building, and deployment strategies- Sharing knowledge within the organization through mentoring, training, and creating reusable artifacts
About the team
About AWS:
Diverse Experiences: AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job below, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.Mentorship & Career Growth - We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

- 8+ years of cloud based solution (AWS or equivalent), system, network and operating system experience
- 5+ years of experience hosting and deploying GenAI/ML solutions (e.g., for data pre-processing, training, deep learning, fine tuning, and inferences) or/and Data Science Experience
- 8+ years of coding, data querying languages (e.g. SQL), scripting languages (e.g. Python)

Why This Role* Deep technical expertise (still hands-on)
* Scalable mechanism design (programs, frameworks, enablement)
* Startup empathy (credible in front of developers and co-founders)
* AI/data native perspective (helping startups turn data into their moat)This role offers the chance to shape how AWS engages startups at scale — while working at the frontier of cloud + data + AI innovation.
Key job responsibilities
Technical Leadership & Mechanism Building
* Design and implement scalable programs, reusable assets, and automation tools that amplify the impact of the Startup SA org.
* Create reference architectures, IaC templates, and enablement content to accelerate solution delivery across startups.
* Develop systematic approaches to capture, codify, and share technical insights from the field back into the org.
* Mentor SAs and drive technical upskilling programs that elevate the entire team’s capabilities.Domain Expertise & Hands-on Impact
Principal SAs for Startups should have depth and expertise in one of the following technical domains, but the technical curiosity to become proficient in all:
* ML/AI Infrastructure:
* Architect training and inference systems at scale (distributed training, LoRA/QLoRA, quantization, GPU/TPU optimization).
* Design end-to-end ML pipelines and MLOps workflows (data prep, labeling, model registry, deployment).
* Build and optimize model serving architectures and inference systems for cost and latency.
* Cloud Native & Kubernetes:
* Lead design and ops excellence for Kubernetes/EKS, service mesh, microservices, and serverless-first architectures.
* Ensure security, compliance, and observability in containerized workloads.
* DevOps & Reliability:
* Drive GitOps-first workflows, CI/CD at scale, IaC (Terraform/CDK), and automated testing frameworks.
* Apply SRE best practices: monitoring, incident management, resilience, and scaling patterns.
* Data Strategy & Foundations:
* Advise startups on proprietary data strategy as a moat: collection, quality, labeling, governance.
* Architect data pipelines (ETL/ELT, streaming, orchestration) and integrate with modern analytics platforms (Snowflake, Redshift, BigQuery, Databricks).
* Guide adoption of feature stores, vector databases, and lakehouse patterns to enable ML/RAG use cases.
* Ensure compliance and governance across sensitive workloads (GDPR, HIPAA, SOC2).
* Maintain deep understanding of emerging technical trends in GenAI, cloud, and data ecosystems.
* Translate insights into actionable guidance for startups and scalable mechanisms for the org.
* Provide forward-looking perspectives on technology adoption, evolution, and competitive advantage.Scaling & Developer Enablement
* Build repeatable solutions and reference architectures addressing common startup pain points.
* Publish blogs, whitepapers, open-source repos, and technical presentations that extend reach beyond direct engagements.
* Act as a “co-founder whisperer” — translating complex technical trade-offs into pragmatic startup-stage guidance.About the team
Diverse Experiences
Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.
Why AWSWork/Life BalanceInclusive Team CultureMentorship and Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

- 12+ years of specific technology domain areas (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics) experience
- Deep technical expertise in multiple domains including ML/AI systems, cloud-native architectures (Kubernetes, microservices, serverless), DevOps/SRE practices, and data engineering/strategy, with advanced proficiency in languages like Python, Go, TypeScript, and Java.
- Demonstrated track record of scaling technical impact through building enablement programs, mentoring teams, and establishing best practices that transform individual expertise into organizational capabilities.
- Strong technical leadership credentials including creating technical content, contributing to open-source projects, delivering thought leadership, and effectively communicating with audiences from engineers to C-suite executives.
- Comprehensive understanding of modern AI/ML ecosystems (LangChain, Hugging Face, vLLM, Ray) combined with expertise in cloud-native security, compliance, and observability frameworks to build production-grade systems.

- Experience building, deploying, and operating systems and infra at hyperscale.
- A history of contributions to open-source or developer communities.
- A strong portfolio of technical publications, talks, or thought leadership.
- The credibility to pair-program with a founder one day, then brief a C-suite on trends the next.Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

On-site Manufacturing Engineers work closely with our CMs to scale up our production on NPIs and ensure that we can meet the production and quality targets. You will also work with ODMs, CMs, internal AWS hardware and software development teams, and with upstream component vendors to monitor and improve the incoming hardware quality of AWS products both proactively in the design phase as well as monitoring, reporting and investigating any early-life product failures. This role requires the engineer to be a technical contact and take on full ownership of the manufacturing launch and resolution of process issues. You will be the driver in getting production up and running, understanding root cause of hardware failures and resolving gaps in our suppliers manufacturing processes.You’ll join a diverse team of software, hardware, and network engineers, supply chain specialists, security experts, operations managers, and other vital roles. You’ll collaborate with people across AWS to help us deliver the highest standards for safety and security while providing seemingly infinite capacity at the lowest possible cost for our customers. And you’ll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion.Key job responsibilities
- Manage quality at the CM
- Provide On-Site support to new product launches as well as sustaining issues
- Design in quality and manufacturability on new designs of servers and racksAmazon Web Services (AWS) values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

- Bachelor's or Master’s degree in Industrial, Manufacturing Engineering or similar related field or equivalent experience
- 2+ years of Manufacturing Engineering work experience with server platforms or on high-tech hardware
- 5+ working with manufacturing suppliers to improve incoming quality of systems
- 5+ years Experience reducing cycle time and improving labor efficiency

Responsibilities:
Interact with business customers to understand and document their business processes and requirementsAble to code with any python or any such programming language to calculate and present data.Key job responsibilities
Deliver reliable, scalable, and efficient business solutions by supporting all phases of the software development life cycle (SDLC), including requirements gathering, modeling & design, development, testing, deployment, integration, and documentation.Provide support and improvement across series of internally development models, systems and tools.

- Bachelor's Degree in Information Systems, Computer Science, Engineering, Math, Finance/Accounting, or a related discipline
- 1+ year experience working in financial planning/budgeting, business analysis, or a related analytics field that includes financial modeling, problem solving, and gathering/translating business requirements
- 1+ year experience working with IBM Cognos TM1 (Planning Analytics) solutions or related Performance Management technologies (Hyperion, SAP, Anaplan or similar)

- Experience with dimension management software processes and MDM tools
- Experience with Python, particularly TM1Py.
- Project management & reporting experience, and familiarity with software development methodologies
- Familiarity with AWS solutions such as S3 and Redshift · Knowledge of SQL authoring, RDBMS database interaction, data warehousing concepts, or third-party ETL tools
- Successful experience working in a fast-paced, results-oriented environment