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Black Box Optimization Jobs (NOW HIRING)

AI Strategist, SEO & GEO

New York, NY · On-site

$125K - $165K/yr

Our platform turns black-box AI behavior into actionable insights, so marketing teams can make ... Now, we're pioneering a new category at the intersection of AI, SEO, and brand strategy. We raised ...

Architect scalable grey-box, white-box, and black-box test frameworks that become organizational ... Design and deploy AI/ML solutions for test optimization, intelligent failure triage, predictive ...

Comfort reasoning about and implementing custom optimization logic (e.g., gradient-based methods, constraint handling), not just applying black-box tooling. Preferred Qualifications * Experience with ...

Apply white-box, grey-box, and black-box testing methodologies to validate firmware functionality ... and validation workflow optimization. Required Qualifications * Bachelor's degree with ...

Comfort reasoning about and implementing custom optimization logic (e.g., gradient-based methods, constraint handling), not just applying black-box tooling. Preferred Qualifications * Experience with ...

This role performs both black-box and white-box testing to validate functionality, reliability, and ... optimization techniques, and modern automation frameworks * Adapt testing approaches as ...

Control Systems Engineer

Chillicothe, IL · On-site

$100K - $120K/yr

... of optimizing engine performance and emissions. As an individual contributor within the Large ... Strong background in modeling dynamic systems through physics‑based white box models, black box ...

Senior ML Engineer

$180K - $200K/yr

Work across a broad modeling landscape including RL, graph neural networks, black-box/classical optimization, and generative modeling * Formulate objectives, model constraints, and debug numerical ...

... optimization frameworks that balance objectives like margin, conversion, and risk • Apply ... pure black-box prediction is not enough • Design experiments and measurement approaches to ...

Research Engineer

San Francisco, CA · On-site

$175K - $275K/yr

This is not a black-box applied role: your work will be published, your infrastructure will be ... Strong fundamentals in machine learning, optimization, and large-scale data processing

Showing results 21-40

Black Box Optimization information

See salary details

$16K

$55.8K

$102K

How much do black box optimization jobs pay per year?

As of Sep 13, 2026, the average yearly pay for black box optimization in the United States is $55,794.00, according to ZipRecruiter salary data. Most workers in this role earn between $36,000.00 and $72,500.00 per year, depending on experience, location, and employer.

What are some common challenges faced by professionals working in black box optimization and how can they be addressed?

Professionals in Black Box Optimization often encounter challenges such as limited information about the system being optimized, noisy data, and computationally expensive evaluations. To manage these, practitioners typically use surrogate models, parallel computing, and adaptive sampling to efficiently explore the solution space. Collaboration with domain experts is also vital to interpret results and refine optimization strategies, ensuring robust and meaningful outcomes. Staying updated on the latest optimization algorithms and software tools can further enhance performance and problem-solving capabilities.

What are the key skills and qualifications needed to thrive as a black box optimization specialist, and why are they important?

To thrive as a Black Box Optimization Specialist, you typically need a strong background in mathematics, statistics, and computer science, often supported by a relevant degree. Familiarity with optimization software (such as MATLAB or Python libraries like SciPy), machine learning frameworks, and sometimes domain-specific tools is essential. Strong analytical thinking, problem-solving abilities, and collaborative communication skills help you stand out in this role. These skills enable effective analysis and optimization of complex systems where internal mechanisms are unknown, leading to impactful solutions in fields like engineering, finance, and AI.

What is the difference between Black Box Optimization vs Data Scientist?

AspectBlack Box OptimizationData Scientist
Required CredentialsTypically a degree in mathematics, computer science, or engineering; certifications in optimization or data analysisDegree in statistics, computer science, or related fields; certifications in data analysis or machine learning
Work EnvironmentResearch labs, R&D departments, tech companies focusing on algorithm developmentBusiness environments, tech firms, consulting, analyzing data to inform decisions
Industry UsageUsed in engineering, AI, machine learning, and operations researchApplied across finance, healthcare, marketing, and technology sectors

Black Box Optimization and Data Scientists often share skills in programming and analytical thinking. While Black Box Optimization focuses on developing algorithms to optimize complex systems without explicit models, Data Scientists analyze and interpret data to generate insights. Both roles are vital in data-driven industries but serve different purposes within the analytics ecosystem.

What other helpful pages are available for Black Box Optimization?

Other pages related to Black Box Optimization:

Infographic showing various Black Box Optimization job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 89% Full Time, 8% Part Time, and 2% Contract. Highlights an 77% Physical, 5% Hybrid, and 18% Remote job distribution, with an average salary of $55,794 per year, or $26.8 per hour.

Staff SSD Firmware Test Engineer

Longmont, CO • On-site

Other

Medical, Dental, Vision, PTO

Posted 25 days ago


Job description

Our vision is to transform how the world uses information to enrich life for all. Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Micron's Firmware & Product Test (FPT) team is hiring a Staff Engineer to lead validation strategy for enterprise SSD firmware. In this role, you'll architect next-generation test frameworks, drive AI/ML-powered validation methodologies, and own end-to-end verification of complex NVMe front-end features across multiple product lines. You'll serve as a technical authority at the intersection of firmware validation and applied machine learning - shaping the strategic direction of our test infrastructure, mentoring engineers, and influencing firmware architecture decisions through deep validation insights. The FPT team builds verification plans in Python, enforces NVMe and security protocol compliance, and executes white-box, grey-box, and black-box testing across simulation, FPGA, and prototype hardware environments.

Responsibilities
  • Lead the design and execution of firmware verification strategies for customer specifications and NVMe protocols, owning validation of complex front-end features (SMART, Trim, Get Log Page, OCP) across multiple product lines.
  • Architect scalable grey-box, white-box, and black-box test frameworks that become organizational standards for firmware quality.
  • Drive root-cause analysis for critical field and regression failures; establish systematic debug methodologies and knowledge-sharing practices across the team.
  • Own the test infrastructure roadmap - including automation frameworks, CI/CD integration, and reporting dashboards - and influence tooling decisions at the department level.
  • Design and deploy AI/ML solutions for test optimization, intelligent failure triage, predictive analytics, anomaly detection, and test prioritization.
  • Lead code reviews, define test coverage standards, and drive continuous improvement in code quality and test effectiveness.
  • Present technical findings, risk assessments, and strategic recommendations to senior leadership and cross-functional stakeholders.
  • Mentor junior and mid-level engineers, providing technical guidance and fostering a culture of engineering excellence.
  • Collaborate with firmware architects, product managers, and customers to define testability requirements and influence firmware architecture decisions.
Basic Qualifications
  • Bachelor's degree with ~8+ years of relevant experience
  • Master's with ~6+ years
  • PhD with ~4+ years in Computer Science, Data Science, Electrical/Computer Engineering, or a related field
  • Expert-level Python proficiency, including strong command of NumPy, pandas, and scikit-learn, with a track record of building production-quality automation frameworks
  • Deep expertise in test architecture, automation strategy, and validation methodologies, with proven success designing scalable test solutions
  • Demonstrated experience applying ML models to real-world problems - designing, training, and deploying models for test optimization or failure analysis
  • Proven ability to lead technical initiatives, influence without authority, and drive alignment across teams
  • Excellent communication skills, with the ability to convey complex technical concepts to diverse audiences including senior leadership
Preferred Qualifications
  • Proficiency with ML frameworks such as TensorFlow or PyTorch, plus experience with MLOps practices
  • Track record of implementing AI/ML solutions in production testing or validation environments
  • Experience leveraging AI/Generative AI tools to improve engineering productivity, test automation, data analysis, and problem solving
  • Familiarity with Python-based AI/ML frameworks and responsible use of AI technologies is highly desirable
  • Deep understanding of embedded systems, firmware architecture, and hardware-software interfaces
  • Working knowledge of storage industry standards (NVMe, PCIe, OCP) at the specification level
  • Familiarity with NAND flash memory architecture and SSD firmware validation methodologies
  • Proficiency with Rust or C for firmware code comprehension, plus Linux/Windows system administration and Git/CI/CD pipelines
  • Contributions to open-source projects, patents, or published technical work
  • Experience leading cross-functional initiatives or small teams
Benefits

Micron benefits are designed to help you stay well, provide peace of mind and help you prepare for the future. We offer a choice of medical, dental and vision plans in all locations enabling team members to select the plans that best meet their family healthcare needs and budget. Micron also provides benefit programs that help protect your income if you are unable to work due to illness or injury, and paid family leave. Additionally, Micron benefits include a robust paid time-off program and paid holidays. For additional information regarding the Benefit programs available, please see the Benefits Guide posted on micron.com/careers/benefits.

Equal Opportunity Employment

Micron is proud to be an equal opportunity workplace and is an affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, age, national origin, citizenship status, disability, protected veteran status, gender identity or any other factor protected by applicable federal, state, or local laws.

Micron Prohibits the use of child labor and complies with all applicable laws, rules, regulations, and other international and industry labor standards.

Micron does not charge candidates any recruitment fees or unlawfully collect any other payment from candidates as consideration for their employment with Micron.

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