Amazon

Sr. Machine Learning Engineer (Sr. SDE), OTS DataTech

Austin, TX Nashville, TN
USD 151k - 261k
AWS Docker Kubernetes PyTorch TensorFlow Hadoop Spark Machine Learning
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Description
- 5+ years of non-internship professional software development experience
- 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- 5+ years of programming with at least one software programming language experience
- Experience as a mentor, tech lead or leading an engineering team
- 5+ years of professional software development experience with CI/CD experience
- Bachelors or MS degree in computer science or engineering field (CE, EE, ML preferred)
- Strong communication skills, both written and verbal.
- 5+ years of experience in full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations
- Experience developing, building and implementing complex software systems and machine learning systems that have been successfully delivered to customers.
- Experience developing, building, and implementing data engineering pipelines and infrastructure.
- Experience with AWS technologies.
- 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).
- Background in AI/ML, including GenAI, supervised and unsupervised learning, and optimization algorithms.
- Experience with ML frameworks (e.g., PyTorch, TensorFlow) and application development frameworks (e.g., LangChain).
- Experience with big data technologies (e.g., Hadoop, Spark).
- Experience as a mentor, tech lead, or leading an engineering team.

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $151,300/year in our lowest geographic market up to $261,500/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 Amazon’s 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 Sr. Machine Learning Engineer with a background in building cutting-edge infrastructure components and platforms that are highly scalable, extensible, and robust to enable exponential growth and adoption of AI/ML within OTS. In this role, you will play a pivotal role in shaping the vision, roadmap, and execution of science and engineering based solutions from beginning to end.

You will be responsible to build and maintain an MLOps Platform that will support end-to-end scientific operations for a wide range of AI/ML use cases within the realms of GenAI, supervised and unsupervised learning, optimization, and more. The MLOps Platform will streamline and standardize the entire Machine Learning Development Lifecycle including data processing, model training, deployment, and monitoring. You will evangelize the adoption of our solutions across the organization to help OTS builder teams quickly develop and deploy reliable AI/ML solutions in scale.

By leveraging your deep technical expertise in machine learning and software engineering, you will help the DataTech team adopt engineering best practices and uplift our Operational Excellence standards.

You will be closely partnering with a cross-functional team of stakeholders including with Applied Scientists, Data Scientists, Data Engineers, Product Managers, and Technical Program Managers.

As part of other initiatives, you will also contribute to building a data infrastructure that supports our DataMesh framework, enabling engineering and BI self-service architecture for DaaP, 3P software integrations, and more.

Come join OTS DataTech as we continue to innovate and pioneer the AI/ML space within OTS!


Key job responsibilities
* Build and maintain an MLOps Platform that supports end-to-end AI/ML operations.
* Shape the vision and roadmap for AI/ML across the organization, leading their development from concept to deployment from an engineering perspective.
* Guide teams to adopt software engineering best practices that uplift our Operational Excellence standards.
* Promote and facilitate the adoption of AI/ML solutions across the organization.
* Build and maintain data infrastructure that supports the DataMesh framework and enables self-service architecture.

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. If you’re passionate about this role and want to make an impact on a global scale, please apply!
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