At least 10 years
This role is STARs-friendly: Skilled Through Alternative Routes.
35% STARs in role.
Job Title: Reliability Engineer
Job Description
The Reliability Engineer leads the reliability assessment, validation, and design guidance for core electrochemical components. This role owns the full reliability lifecycle from concept and design through development testing, manufacturing, and field operation. The engineer investigates failures using physics-of-failure methods and physical testing, predicts component and system robustness, and translates insights into design and architecture improvements that continuously enhance product reliability and inform system-level reliability estimates. Acting as a key reliability advisor, this person partners closely with system and hardware design teams to evaluate off-the-shelf components for a unique operating environment and long service-life requirements.
Responsibilities
- Own reliability engineering for prodcut and electrochemical rebalancing cells, ensuring robust performance over long service lifetimes.
- Identify and characterize dominant degradation and failure mechanisms, including electrochemical, chemical, mechanical, thermal, and environmental modes.
- Develop physics-of-failure models to guide accelerated life testing, define operating limits, and support design tradeoffs.
- Define clear reliability requirements and targets for core components based on field usage conditions, duty cycles, and cost models.
- Design and execute validation plans to determine expected operating lifetimes across different specification ranges.
- Lead teardown and failure analysis of lab-tested and field-returned components to determine root causes and recurrence risks.
- Partner with cross-functional engineering teams to translate failure analysis findings into design changes, updated requirements, and improved validation plans.
- Support system-level reliability analyses, including fault tree analysis, reliability block diagrams, and Design Failure Mode and Effects Analysis (DFMEA).
- Integrate component-level reliability data into system reliability models and predictions to support product and architecture decisions.
- Analyze field data from deployed systems to identify reliability trends, emerging risks, and opportunities for design and process improvements.
- Serve as a reliability advisor to design teams evaluating off-the-shelf components for long-duration, grid-scale energy storage applications.
- Review off-the-shelf component data sheets, qualification reports, and life-test data to evaluate assumptions, margins, and applicability to operating conditions.
- Translate specific duty cycles—including electrical, thermal, mechanical, environmental, and chemical exposure—into reliability risks, gaps, and recommended validation or derating strategies.
- Provide guidance on when additional testing, screening, or supplier engagement is required before deployment of new components.
- Define and communicate reliability requirements for critical suppliers supporting battery and electrochemical components.
- Review and challenge supplier life-test data, assumptions, and acceleration models to ensure they align with real-world operating conditions.
- Support supplier corrective actions related to reliability issues, ensuring effective resolution and long-term prevention.
- Maintain and expand internal reliability guidelines, best practices, and lessons learned to strengthen organizational knowledge and processes.
Essential Skills
- Bachelor’s degree in Materials, Mechanical, Electrical, Chemical Engineering, or a related field.
- 10+ years of experience in reliability engineering, component development, or failure analysis (flexible for exceptionally strong candidates).
- Strong understanding of accelerated testing methods, governing equations, and physics-of-failure across a range of failure mechanisms.
- Solid foundation in applied statistics and reliability statistics, including methods such as Weibull analysis, Maximum Likelihood Estimation, Bayesian methods, and Monte Carlo simulation.
- Hands-on experience with failure analysis techniques such as optical microscopy, scanning electron microscopy (SEM), C-SAM, X-ray inspection, cross-sectioning, and energy-dispersive X-ray spectroscopy (EDX).
- Proficiency with reliability engineering analysis tools and platforms used for reliability modeling, statistics, and test planning.
- Demonstrated ability to develop and execute validation plans and interpret test results to drive design and process improvements.
- Ability to communicate complex reliability findings clearly to cross-functional teams and influence design decisions.
Additional Skills & Qualifications
- Working knowledge of programming, preferably in Python, to support data analysis and modeling.
- Familiarity with corrosive environments, polymers, or battery materials and their impact on long-term reliability.
- Experience analyzing field reliability data to determine or predict failure causes and drive corrective actions.
- Comfort working across disciplines in a fast-moving hardware development environment with evolving requirements.
- Knowledge of reliability and warranty analysis methodologies, as well as reliability prediction techniques.
- Familiarity with design-for-reliability methods, including integrating ECAD, MCAD, and CAE data into 3D finite element models.
- Strong collaboration skills for working with design, test, manufacturing, and supplier teams on reliability topics.
Work Environment
This role is primarily onsite with potential for a hybrid schedule depending on business needs. The position is embedded in a hands-on hardware development environment, where you collaborate closely with multidisciplinary engineering teams. You can expect regular interaction with laboratory and test facilities for component and system validation, as well as engagement with suppliers and manufacturing partners. The work setting supports detailed experimental work, data analysis, and design collaboration in a professional, engineering-driven environment.
We will be prioritizing regional talent who can work onsite and start work within the next couple of weeks. We may consider non-local prospects if their resume shows full qualifications and the candidate can relocate themselves to the area within a couple of weeks.
#LI-MH3
Job Type & LocationThis is a Contract to Hire position based out of Tualatin, OR.
Pay and BenefitsThe pay range for this position is $135500.00 - $155500.00/hr.
Eligibility requirements apply to some benefits and may depend on your job
classification and length of employment. Benefits are subject to change and may be
subject to specific elections, plan, or program terms. If eligible, the benefits
available for this temporary role may include the following:
• Medical, dental & vision
• Critical Illness, Accident, and Hospital
• 401(k) Retirement Plan – Pre-tax and Roth post-tax contributions available
• Life Insurance (Voluntary Life & AD&D for the employee and dependents)
• Short and long-term disability
• Health Spending Account (HSA)
• Transportation benefits
• Employee Assistance Program
• Time Off/Leave (PTO, Vacation or Sick Leave)
This is a hybrid position in Tualatin,OR.
Application DeadlineThis position is anticipated to close on May 28, 2026.
About Actalent
Actalent is a global leader in engineering and sciences services and talent solutions. We help visionary companies advance their engineering and science initiatives through access to specialized experts who drive scale, innovation and speed to market. With a network of almost 30,000 consultants and more than 4,500 clients across the U.S., Canada, Asia and Europe, Actalent serves many of the Fortune 500.
The company is an equal opportunity employer and will consider all applications without regard to race, sex, age, color, religion, national origin, veteran status, disability, sexual orientation, gender identity, genetic information or any characteristic protected by law.
If you would like to request a reasonable accommodation, such as the modification or adjustment of the job application process or interviewing process due to a disability, please email actalentaccommodation@actalentservices.com for other accommodation options.
San Francisco Fair Chance Ordinance: Pursuant to the San Francisco Fair Chance Ordinance, for all positions located in the city and county of San Francisco, we will consider for employment qualified applicants with arrest and conviction records.
Massachusetts Lie Detector: It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.
Use of Artificial Intelligence (AI): We may use Artificial Intelligence (AI) to support parts of our hiring process, including sourcing, screening, and evaluating candidates. AI helps assess applications and qualifications, but final decisions are made by our hiring team. By applying, you acknowledge and agree that your application may be reviewed using AI tools.
Posting ID: JP-006026592
