Interested in this Research Engineer role at PlayStation?
Apply Now →Skills & Technologies
About This Role
Position Type:
Location(s):
United States, Remote
Date Posted:
Job ID:
R\-124949
Why Sony Interactive Entertainment?
Sony Interactive Entertainment isn’t just the Best Place to Play — it’s also the Best Place to Work. Sony Interactive Entertainment (SIE) is the company behind the PlayStation brand. As a subsidiary of Sony Group Corporation, we’re part of a proud legacy of innovation and excellence. SIE is a dynamic technology company, delivering cutting\-edge hardware and network services to more than 100 million people and an entertainment leader, home to some of the most beloved and recognizable intellectual properties (IP) in the world. Our role at SIE is to create and nurture the experiences under the PlayStation brand, a name synonymous with entertainment excellence and creativity.
Reporting to the Director of Global Vulnerability Management, you will serve as a Senior Security Research Engineer and technical lead within SIE’s Global Vulnerability Management team. You will lead complex work that advances our Threat Exposure Management capability and supports our transition to a Continuous Threat Exposure Management operating model, while remaining directly engaged in vulnerability research, analysis, security validation, prioritization, and remediation support.
You will partner across Information Security, engineering, technology, and business teams to improve how SIE discovers, prioritizes, validates, and mobilizes action on security risks. You will translate annual TEM goals into defined workstreams, delivery plans, success measures, and repeatable operating practices that improve visibility, decision\-making, remediation outcomes, and program scale.
Responsibilities
- Lead complex Global Vulnerability Management workstreams that advance SIE’s Threat Exposure Management capability and transition toward a Continuous Threat Exposure Management operating model across discovery, prioritization, validation, and mobilization.
- Translate annual TEM goals into defined delivery plans, milestones, success measures, dependencies, and repeatable operating practices. Monitor progress, identify barriers, and adjust execution to improve outcomes.
- Lead hands\-on vulnerability research and technical analysis to confirm security conditions, eliminate false positives, characterize exploitability and business impact, and provide actionable remediation or mitigation guidance.
- Improve the discovery and assessment of vulnerabilities across SIE network, cloud, endpoint, application, container, and other technology environments.
- Develop risk\-based prioritization using vulnerability and threat intelligence, exploitation evidence, asset and business context, control effectiveness, and remediation considerations.
- Lead security validation activities and develop proofs of concept when appropriate to distinguish material risk, evaluate defensive controls, and support informed decisions.
- Partner with Information Security teams and technology owners to mobilize remediation, clarify ownership, establish effective handoffs, resolve barriers, and measure progress through remediation, mitigation, or accepted disposition.
- Evolve GVM platforms, integrations, data, analytics, automation, and AI\-enabled workflows to improve coverage, data quality, consistency, decision speed, and operational scale.
- Communicate vulnerability trends, material risks, remediation progress, and program outcomes to technical, operational, and leadership audiences through clear reports and recommendations.
- Mentor engineers and partner teams, contribute to technical standards and procedures, and improve the quality of vulnerability analysis, validation, documentation, and delivery.
- Maintain current knowledge of relevant vulnerabilities, exploitation techniques, threat activity, security technologies, and industry practices.
- Some travel may be required.
Qualifications
------------------
- 8\+ years of relevant experience in information security, information technology, systems engineering, or a related field, including substantial experience in vulnerability management, security research, or exposure management.
- Bachelor’s degree or equivalent in computer science, information security, or a related discipline.
- Experience leading complex technical workstreams across multiple teams, translating objectives into delivery plans, and achieving measurable outcomes without relying on direct reporting authority.
- Hands\-on experience with vulnerability research, technical analysis, security validation, risk\-based prioritization, and remediation or mitigation guidance.
- Experience assessing vulnerabilities across several technology domains, such as operating systems, networks, cloud services, applications, endpoints, containers, databases, or hybrid infrastructure.
- Experience with vulnerability discovery, assessment, validation, or exposure\-management platforms and their supporting integrations.
- Knowledge of adversarial tactics, exploitation techniques, threat intelligence, and attack frameworks such as MITRE ATT\&CK, with the ability to apply that information to vulnerability prioritization.
- Experience using scripting, programming, APIs, or automation to improve security analysis and operational workflows. Relevant technologies may include Python, SQL, Bash, PowerShell, JavaScript, or comparable languages.
- Experience analyzing and contextualizing security data to connect technical findings with asset, service, business, threat, control, and remediation information.
- Familiarity with software engineering practices such as version control, testing, code review, CI/CD, reusable components, and controlled production releases.
- Ability to communicate complex security conditions, priorities, tradeoffs, and recommendations clearly to technical, operational, and leadership audiences.
- Experience mentoring engineers or analysts and influencing technical practices across teams.
Desired qualifications
--------------------------
- Experience helping evolve a traditional vulnerability\-management function toward a TEM or CTEM operating model.
- Experience with continuous security validation, adversarial exposure validation, exploit research, or proof\-of\-concept development.
- Experience securing cloud, container, application, or build\-pipeline environments and integrating security capabilities into engineering workflows.
- Experience with security\-data and analytics platforms such as Snowflake, Domo, or comparable technologies.
- Experience applying automation, advanced analytics, or AI\-enabled capabilities to vulnerability analysis, prioritization, validation, or remediation workflows.
At SIE, we consider several factors when setting each role’s base pay range, including the competitive benchmarking data for the market and geographic location.
Please note that the base pay range may vary in line with our hybrid working policy and individual base pay will be determined based on job\-related factors which may include knowledge, skills, experience, and location.
In addition, this role is eligible for SIE’s top\-tier benefits package that includes medical, dental, vision, matching 401(k), paid time off, wellness program and coveted employee discounts for Sony products. This role also may be eligible for a bonus package.
This is a flexible role that can be remote, with varying pay ranges based on geographic location. For example, if you are based out of Seattle, the estimated base pay range for this role is listed below.
$175,500—$263,300 USD
Please note, Sony Interactive Entertainment conducts background checks at the offer stage for all new employees (which may include criminal background checks for some roles) and will need to process personal information to support these checks.
Please refer to our Candidate Privacy Notice for more information about what personal information we collect, how we use it, who we share it with, and your data protection rights.
Equal Opportunity Statement:
*Sony is an Equal Opportunity Employer. All persons will receive consideration for employment without regard to gender (including gender identity, gender expression and gender reassignment), race (including colour, nationality, ethnic or national origin), religion or belief, marital or civil partnership status, disability, age, sexual orientation, pregnancy, maternity or parental status, trade union membership or membership in any other legally protected category.*
*We strive to create an inclusive environment, empower employees and embrace diversity. We encourage everyone to respond.*
*Sony Interactive Entertainment is a Fair Chance employer and qualified applicants with arrest and conviction records will be considered for employment.*
Salary Context
This $175K-$263K range is above the median for Research Engineer roles in our dataset (median: $207K across 63 roles with salary data).
View full Research Engineer salary data →Role Details
About This Role
Research Engineers bridge the gap between research and production. They implement papers, build experiment infrastructure, optimize training pipelines, and make research prototypes production-ready. They're the engineers who make research work at scale.
The role sits at a unique intersection. You need to understand the math well enough to implement novel architectures correctly, and you need the engineering chops to make them run efficiently on distributed systems. When a research scientist has a breakthrough idea, you're the person who turns it from a notebook prototype into a training pipeline that runs on 256 GPUs.
Across the 4,317 AI roles we're tracking, Research Engineer positions make up 2% of the market. At PlayStation, this role fits into their broader AI and engineering organization.
Research Engineer roles are growing as AI labs recognize that research velocity depends on engineering quality. The role is less competitive than Research Scientist (no PhD required), but the bar for engineering skill is very high. These roles are concentrated at major labs and well-funded startups.
What the Work Looks Like
A typical week involves: implementing a new attention mechanism from a recent paper, profiling and optimizing a training pipeline that's bottlenecked on data loading, building evaluation infrastructure for a new benchmark, debugging distributed training issues across a GPU cluster, and pair-programming with a research scientist on their latest experiment. The work is deeply technical.
Research Engineer roles are growing as AI labs recognize that research velocity depends on engineering quality. The role is less competitive than Research Scientist (no PhD required), but the bar for engineering skill is very high. These roles are concentrated at major labs and well-funded startups.
Skills Required
Strong software engineering fundamentals plus ML knowledge. Python, C++, and CUDA experience are common requirements. You'll need to read papers and turn ideas into working code. Distributed systems experience (especially distributed training) is highly valued. Performance optimization skills separate great candidates from good ones.
Experience with large-scale training infrastructure (FSDP, DeepSpeed, Megatron), GPU programming (CUDA, Triton), and the internals of ML frameworks (PyTorch internals, custom autograd functions) is what makes candidates stand out. The best research engineers can debug issues that span the full stack from GPU memory management to numerical precision to algorithmic correctness.
Strong postings mention the team's recent research, the infrastructure scale, and the specific technical challenges. They often list the research areas you'd support. Look for roles that emphasize both implementation quality and research understanding.
Compensation Benchmarks
Research Engineer roles pay a median of $272,100 based on 227 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($219K) sits 19% below the category median. Disclosed range: $175K to $263K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and AI Engineering Manager ($244,000). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
PlayStation AI Hiring
PlayStation has 1 open AI role right now. They're hiring across Research Engineer. Based in Remote, US. Compensation range: $263K - $263K.
Remote Work Context
Remote AI roles pay a median of $180,000 across 1,196 positions. About 15% of all AI roles offer remote work.
Career Path
Common paths into Research Engineer roles include Software Engineer, ML Engineer, Research Intern.
From here, career progression typically leads toward Senior Research Engineer, Research Scientist, ML Architect.
This is one of the best entry points into AI research without a PhD. Build a strong engineering portfolio with ML projects, contribute to open-source ML frameworks, and demonstrate that you can implement complex ideas correctly and efficiently. The transition to Research Scientist is possible with published first-author work, which some research engineer roles support.
What to Expect in Interviews
Technical screens test both engineering skill and research understanding. Expect coding rounds with performance-critical implementations (GPU optimization, efficient data loading). Be prepared to discuss papers relevant to the team's research area and explain how you'd implement key ideas. System design questions focus on training infrastructure: distributed training, experiment tracking, and compute resource management.
When evaluating opportunities: Strong postings mention the team's recent research, the infrastructure scale, and the specific technical challenges. They often list the research areas you'd support. Look for roles that emphasize both implementation quality and research understanding.
AI Hiring Overview
The AI job market has 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 roles).
Research Engineer roles are growing as AI labs recognize that research velocity depends on engineering quality. The role is less competitive than Research Scientist (no PhD required), but the bar for engineering skill is very high. These roles are concentrated at major labs and well-funded startups.
The AI Job Market Today
The AI job market spans 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (138) are outnumbered by mid-level (2,071) and senior (1,655) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $287,500 median, while Prompt Engineer roles sit at $145,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
Get Weekly AI Career Intelligence
Salary data, skills demand, and market signals from 16,000+ AI job postings. Every Monday.