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Black Box Optimization Jobs (NOW HIRING)

JPMorgan Chase & Co.

Site Reliability Engineer II

Chicago, IL · On-site

$58.75 - $78/hr

... optimal transparency and analysis * Applies enterprise-authorized AI capabilities within the work ... Familiar with observability such as white and black box monitoring, service level objective ...

De Circle

Interval - Solidity Engineer

New York, NY · On-site +1

... to a black box. We bring compute to your data with a private data lakehouse, verifiable audit ... Proven understanding of EVM architecture, smart contract security, and gas optimization.

Steely

Reverse Engineer

Reston, VA · On-site

$140K - $200K/yr

Conduct research working with white-box and black-box methodologies to analyze embedded systems ... Support software engineering development to translate algorithm prototypes into optimized ...

Steely

Reverse Engineer

Reston, VA

$140K - $200K/yr

Conduct research working with white-box and black-box methodologies to analyze embedded systems ... Support software engineering development to translate algorithm prototypes into optimized ...

Steely

Reverse Engineer

Reston, VA · On-site

$140K - $200K/yr

Conduct research working with white-box and black-box methodologies to analyze embedded systems ... Support software engineering development to translate algorithm prototypes into optimized ...

Thecsp

Process Technician

Carey, OH

The primary responsibilities will be to improve productivity through optimization of scrap and ... Process monitoring checks (i.e., flash thickness, black box) Long lead process improvements and ...

Opendoor

Applied Scientist- Pricing

Miami, FL · On-site

$156K - $335K/yr

This role will focus primarily on structural modeling, econometrics, optimization, and decision ... black-box prediction is not enough * Design experiments and measurement approaches to quantify ...

Opendoor

Applied Scientist- Pricing

Seattle, WA · On-site

$156K - $335K/yr

This role will focus primarily on structural modeling, econometrics, optimization, and decision ... black-box prediction is not enough * Design experiments and measurement approaches to quantify ...

EBizCharge

QA Engineer I

Irvine, CA · On-site

Help establish best practices for optimizing quality control and take the initiative to identify ... Proficiency in conducting black box and white box testing. * Proficiency in performing regression ...

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Black Box Optimization information

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$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 78% Physical, 4% Hybrid, and 18% Remote job distribution, with an average salary of $55,794 per year, or $26.8 per hour.

Site Reliability Engineer II

Chicago, IL • On-site

JPMorgan Chase & Co.
Finance and Insurance • 10K+ employees
Learn more about JPMorgan Chase & Co.external

$58.75 - $78/hr

Other

Re-posted 16 days ago

JPMorgan Chase & Co. rating

7.9

Company rating: 7.9 out of 10

Based on 500 frontline employees who took The Breakroom Quiz

Job description

Play a key role in ensuring system reliability at one of the world’s most iconic and largest financial institutions.

As a Site Reliability Engineer II at JPMorgan Chase within the Commercial and Investment Banking and Payment Technology Team, you will use technology to solve business problems and leverage software engineering best practices as we strive towards excellence. This role often works independently to execute small to medium projects, but you’ll also have the opportunity to collaborate with cross functional teams to continually improve your level of knowledge about JPMorgan Chase’s business and relevant technologies.

Job Responsibilities
  • Executes small to medium projects independently with initial direction and graduates to designing and delivering projects independently
  • Leverages technology to solve business problems by writing high quality, maintainable, and robust code following best practices in software engineering
  • Uses enterprise-authorized AI capabilities within the work environment to speed up incident triage, troubleshooting, and post-incident analysis, validating outputs and handling operational data according to sensitivity and security requirements.
  • Participates in triaging, examining, diagnosing, and resolving incidents and works with others to solve problems at their root
  • Recognizes toil within the role and proactively works towards eliminating it through systems engineering or updating application code
  • Understands observability patterns and strives to implement and improve service level indicators, objectives monitoring, and alerting solutions for optimal transparency and analysis
  • Applies enterprise-authorized AI capabilities within the work environment to identify recurring toil and reliability risks from operational signals, prioritizing reuse-first improvements and measurable SLO outcomes.
Required qualifications, capabilities, and skills
  • Formal training or certification on software engineering concepts and 2+ years applied experience
  • Ability to code in at least one programming language
  • Working knowledge of using enterprise-authorized AI capabilities within the work environment to support SRE workflows (e.g., troubleshooting support and runbook drafting) with strong validation habits and awareness of data sensitivity.
  • Ability to assess AI-assisted operational recommendations for correctness and risk, and apply appropriate controls to maintain resiliency, security, and auditability.
  • Experience maintaining a cloud-based infrastructure
  • Familiar with site reliability concepts, principles, and practices
  • Familiar with observability such as white and black box monitoring, service level objective alerting, and telemetry collection
  • Familiarity with containers or a common server OS such as Linux and Windows
  • Emerging knowledge of continuous integration and continuous delivery practices and related tooling
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