Reliability Analytics Engineer, Amazon Robotics

Are you inspired by invention? Is problem solving through teamwork in your DNA? We apply advances in robotics and software to solve real-world problems that delight our customers' experiences in ways we can't even imagine yet. Amazon Robotics is at the epicenter of robotics innovation. Our diverse team of engineers come from all over the world to design, test and build our dynamic fleet of robots and mechatronic systems. We design the hardware, write the code, test, build and watch it all come to life. This allows us to innovate quickly and on limitless ideas. Current advancements are underway in self-governing movement and mobility, artificial intelligence and machine learning, manipulation, simulation, robotic management software, predictive analytics, and much more.

We are seeking a Reliability Engineer specializing in reliability data analytics to drive data-informed availability selections across Amazon Robotics product programs and deployed fleet. You will apply reliability engineering methods while owning the assessment tools, datasets, and reporting that the broader reliability engineering team depends on. You will define requirements for data pipelines and dashboards, use AI and automation to build them, and directly develop reliability-specific assessment tools. This role combines hands-on reliability engineering with a strong bias toward data systems, enabling the team to scale its evaluation capacity across multiple product programs simultaneously.

Key job responsibilities Define data requirements and specifications for reliability pipelines; partner with data engineering teams to build and validate ETL processes that ingest field failures, test data, and product telemetry from enterprise data lakes and EAM systems.

Perform data cleansing, validation, and preparation of reliability datasets (censored life data, field service records, accelerated test results) to ensure assessment correctness before use in making engineering choices.

Translate reliability engineering questions into data queries and assessment workflows structuring ambiguous problems into repeatable, scalable evaluation methods that other engineers can reuse.

Develop and maintain reliability-specific assessment tools and automation using Python, AI/ML, and statistical libraries (e.g., automated failure mode classification, survival assessment calculators, and fleet health monitoring scripts)

Design and specify dashboard requirements for reliability KPIs (availability, MTBF, MTTR, failure rate trends); build prototypes and operationalize production dashboards.

Identify gaps in available data, define collection requirements for new failure modes or test programs, and work with hardware test and field teams to close data gaps.

Establish data governance practices for reliability datasets (i.e. metadata standards, version control, traceability to source systems) so assessment findings are reproducible and auditable.

A day in the life You run Mean Cumulative Function (MCF) and Weibull examinations on robot fleets, ensuring suspensions are correct before publishing to the reliability team. You meet with data engineers to define telemetry pipeline requirements: necessary fields, censoring rules, and output schemas. You build Python tools that automate reliability growth tracking pulling from the data lake, applying models, and generating standard reports any engineer can run. You deliver failure rate data by subsystem for DFMEA exercises. You refine Machine Learning classifiers that auto-tag field failure tickets by mode, improving accuracy from sustaining team feedback. You're a reliability engineer who understands repairable systems, physics-of-failure, and life data. Your differentiator is scaling expertise through data tools, automation, and AI-building systems the entire team can run.

BS degree in mechanical engineering or equivalent

• 3+ years of working in mechanical engineering or equivalent experience
• Experience with data analysis tools such as Advanced Excel, SQL, Tableau, Python
• Experience applying basic statistical methods (e.g. regression) to difficult business problems, Knowledge of data engineering pipelines, cloud solutions, ETL management, databases, visualizations and analytical platforms
• Experience with AWS services including S3, Redshift, EMR and RDS
• Experience managing and deploying ML products
• Experience with reliability tools (Reliasoft, Minitab, JMP, or equivalent)

The benefits that generally apply to regular, full-time employees include:

1. Medical, Dental, and Vision Coverage
2. Maternity and Parental Leave Options
3. Paid Time Off (PTO)
4. 401(k) Plan, The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

USA, MA, North Reading - 117,300.00 - 160,000.00 USD annually USA, MA, Westboro - 117,300.00 - 160,000.00 USD annually USA, WA, Seattle - 117,300.00 - 160,000.00 USD annually

Amazon Robotics Reliability Engineering is a team of experts in diverse engineering disciplines joined by a passion to astonish customers through solving complex optimization problems. We succeed by embracing ambiguity, moving at a fast pace, and supporting each other's growth.