Job intelligence
Engineering Manager, Machine Learning (Safety)
Discord
Executive opportunity brief
The decision in one screen
A compact evidence-first read of compensation, flexibility, mobility and what still needs verification. No universal quality score is used.
Fast read
Opportunity DNA
There is a useful advantage here: pay compares strongly with similar current roles. Still, location rules could change the fit could change the fit.
Around the 99th percentile within 39 comparable USD salary observations.
Geographic eligibility is restricted to a country or region.
One or more material qualification requirements are stated and may narrow the realistic applicant pool.
Sponsorship and relocation support are not clear from the current listing.
Part of the application route can be assessed, but the full external process may contain additional steps.
At least one recent enabled source can still renew this vacancy.
This fingerprint summarizes what is clear, constrained or still unanswered in the current listing. It is a reading aid, not an overall job score.
Decision evidence check
4 of 5 core facts stated
This checks whether the listing states the facts that commonly change an employment decision. It measures disclosure completeness, not whether the opportunity is good or bad.
Facts already stated
- Compensation
- Work arrangement
- Location eligibility
- Employment type
What to verify next
- Application closing time: Is there a firm application deadline, a rolling review window or no stated closing date?
Unknown information is never converted into a negative score. The questions above exist to prevent missing evidence from being mistaken for a favorable term.
Decision levers
What could make or break the fit?
Reasons to look closer
- Pay compares strongly with similar current roles: The annualized midpoint is around the 99th percentile among 39 comparable USD salary observations.
Trade-offs to weigh
- Location rules could change the fit: Geographic eligibility is restricted to a country or region.
- The experience requirement raises the entry bar: The listing appears to require at least about 5 years of experience.
Questions worth asking before you invest more time
- Confirm whether a degree is actually required, preferred, or replaceable with equivalent experience.
- Ask whether visa sponsorship is available before investing significant time in the application.
These questions come from details the listing leaves open. An unanswered point is not treated as a disadvantage.
Opportunity neighborhood
Keep your options open
These live roles sit close enough to this opportunity to make useful comparison points. Look across several employers before deciding what pay, flexibility or access trade-offs you are willing to accept.
AWS Data Engineer (Associate)
Mactores · USA
Why it is nearby: Same seniority band · Same country · Similar work arrangement
Principal Data Analyst
Tendo · Remote — Worldwide
Why it is nearby: Same seniority band · Similar work arrangement · Same employment type
About 58% lower advertised midpoint
Analytics Engineer
OnTrac · Remote — Worldwide
Why it is nearby: Same seniority band · Similar work arrangement · Same employment type
About 57% lower advertised midpoint
Senior Staff Data Scientist
Netlify · Anywhere in the World
Why it is nearby: Same seniority band · Similar work arrangement · Same employment type
This neighborhood is drawn from current inventory in the same broad occupation. Similarity is based on explicit listing facts; missing details do not count against a job.
Role market context
How much current choice is visible around this kind of work?
This compares the vacancy with current High Paid Job inventory in the broad Data & AI roles family. It describes visible choice and disclosure, not future demand or career quality.
200 most recent current roles sampled for the disclosure measures below.
Distinct employers in the bounded current sample, not an estimate of all employers hiring in the market.
Current sampled roles stating at least four of the five Core Decision Facts.
Requires a numeric amount, explicit ISO currency and supported pay period.
Listings with explicit enough remote, hybrid or on-site evidence to classify.
Missing deadline evidence remains unknown and is not interpreted as an open-ended application window.
Currencies with explicit pay evidence in the sample: USD (21) · EUR (5) · GBP (4) · CAD (2). Raw amounts across different currencies are not compared.
This describes current visible High Paid Job inventory in the same broad occupation family. Percentages use a bounded recent sample and are not a forecast, a complete labor-market census or an employer-quality measure.
Constraint opportunity lab
What changes the size of the current opportunity pool?
Each line applies one stricter evidence-based constraint to the same bounded current role-family sample. It helps you see the trade-off in visible choice without deciding which trade-off is right for you.
Only same-currency opportunities with usable annualized pay enter this comparison. Other currencies are not converted or treated as lower.
Counts only affirmative or possible sponsorship evidence, or relocation explicitly offered. Unknown is not treated as no.
A much stricter subset: only listings with explicit worldwide-remote evidence remain.
Requires amount, explicit ISO currency and a supported pay period. Missing pay evidence remains unknown.
Shows the subset with enough stated evidence for a more informed first comparison.
Uses only roles where a country is known. Roles without country evidence are excluded from this denominator.
Counts roles explicitly classified as worldwide remote, region-restricted remote or remote with restrictions still unclear.
Uses only roles with a stated employment type.
These are counterfactual filters over a bounded sample of current HPJ inventory in the same broad occupation family. They show how visible choice changes when one evidence-based constraint is applied; they do not tell you which constraint you should choose or predict hiring outcomes. The calculation uses the 200 most recent current roles from 899 visible roles in this broad family.
Salary transparency context
Is pay disclosure typical for this kind of role?
This listing states usable structured compensation. About 17% of the bounded current role sample does the same.
Compensation counts only when amount, ISO currency and supported pay period are all known.
Pay disclosure is uncommon in the current role sample.
This employer’s current visible listings disclose pay materially more often than the current same-role sample.
This compares salary-disclosure behavior in current visible listings. It does not compare raw salary amounts across currencies, infer undisclosed pay as zero, or rate employer quality.
Private offer & negotiation lab
Turn an offer into evidence, not guesswork
Enter an annual base offer and, if you want, your own target. HPJ compares only within one explicit currency and never chooses a target for you.
Negotiation evidence available: advertised pay range, current same-currency market context, strong decision evidence.
Enter an annual base offer to compare it with explicit same-currency evidence. HPJ will not suggest a target for you.
Review the full package · 10 terms
Mark what is confirmed, what needs clarification and what you want to prioritize. These choices and notes stay in this browser.
Usable advertised compensation is available.
Variable compensation is mentioned; verify amount, formula, target and eligibility.
Equity or long-term incentive language is mentioned; verify grant type, vesting and valuation basis.
Retirement or pension benefits are mentioned; verify employer contribution and vesting.
Health-benefit language is mentioned; verify coverage, dependants and employee cost.
Paid-leave language is mentioned; verify the exact entitlement and carry-over rules.
A work-arrangement signal is available; verify schedule details before relying on it.
Relocation support not established
Sponsorship not established
A review cycle is mentioned; verify timing and whether compensation can change at that review.
Questions worth taking into the offer conversation
- Is there a bonus, commission or other variable-pay component, and how is it calculated?
- What retirement or pension contribution does the employer provide?
- How much paid leave is provided and what are the carry-over or blackout rules?
- If relocation is relevant, what expenses, timing and repayment conditions are covered?
- What exact sponsorship or work-authorization conditions apply to this role?
- When is the first performance and compensation review after joining?
- Is there a firm application deadline, a rolling review window or no stated closing date?
Occupation intelligence
What broader career references connect to this role?
HPJ uses broad comparison families for current-market analysis. External taxonomy results are reference candidates for that broad family, not a declaration that this vacancy has been authoritatively classified into a specific occupation.
European occupation references
This service uses the ESCO classification of the European Commission.
U.S. occupation references
- Data Scientists 15-2051.00
- Computer and Information Research Scientists 15-1221.00
- Social Science Research Assistants 19-4061.00
- Atmospheric and Space Scientists 19-2021.00
- Bioinformatics Scientists 19-1029.01
This site incorporates information from O*NET Web Services by the U.S. Department of Labor, Employment and Training Administration (USDOL/ETA). O*NET® is a trademark of USDOL/ETA.
Career reference research
Skills worth investigating
Official occupational context, paired with exact phrases visible in this vacancy. It is not a skills test or an applicant-fit score.
ESCO · European occupation
data scientist
Usually essential in this ESCO occupation
- statistical modeling techniques
- perform project management
- query languages
- online analytical processing
- develop data processing applications
- data engineering
- manage data collection systems
Context-dependent ESCO skills
- manage ICT data architecture
- SPARQL
- use spreadsheets software
- computational biology
- state estimation
O*NET · U.S. occupation
Data Scientists
O*NET occupation skills
- Mathematics
- Critical Thinking
- Reading Comprehension
- Complex Problem Solving
- Programming
- Active Learning
- Speaking
- Active Listening
Build my private skill preparation brief Your evidence · Practice · Interview questions
Plan how you might demonstrate or investigate occupational skills. These are broad-family reference examples, not confirmed vacancy requirements. Nothing you enter is sent to High Paid Job.
Private to this browser. Up to 20 reference skills; not a qualification assessment or hiring prediction.
Useful next question: Which of these occupational reference skills does the hiring manager actually expect for this specific role, and what evidence would demonstrate them?
These skills belong to one reference occupation selected for HPJ’s broad career family, not a verified classification of this vacancy. Text overlap only means a phrase appears in the available listing text; it does not establish an employer requirement, your proficiency, or a qualification gap. A missing mention is unknown, not a deficit.
Adjacent current roles to investigate
Product Manager, AI Transformation & Salesforce
Goodleap · USA
same stated country · same seniority band · same employment typePrincipal Software Engineer, Infrastructure Security
OpenAI · USA
same stated country · same employment type · similar work-arrangement evidenceSenior Full-Stack Engineer (Web + Infrastructure)
Searoutes · Germany
same seniority band · same employment type · similar work-arrangement evidenceAdjacent-family roles are exploration prompts from current HPJ inventory. They are not inferred qualification matches and they do not imply a promotion path.
Career move map
What sits one step away?
This listing is currently read as Senior / lead. Nearby roles one visible seniority step away can help you judge whether to widen the search, stretch upward or compare the responsibilities more carefully.
Broader-entry direction
Data Engineer Analyst
Blend360 · Remote — Worldwide
Similar work arrangement · Same employment type · Recently postedData Engineer
DIGITALL Nature Corp · Remote — Worldwide
Similar work arrangement · Same employment type · Recently postedStretch direction
Sr. Data Engineer
Carrot · USA
USD 145,000–165,000 / year Same country · Similar work arrangement · Same employment type Advertised midpoint is about 49% lower(765) Data Analyst (Healthcare Fraud)
Arlo Solutions · USA
Same country · Similar work arrangement · Same employment typeThese are live roles one visible seniority step away in the same broad occupation family. They can reveal nearby options, but they are not a guaranteed promotion path and do not account for your personal experience.
Skill bridge
What does this role connect to?
Large Language Models is one of the signals this listing shares with skills appearing often across current Data & AI roles opportunities.
Skills named in this listing
Shared with the current career sample
- Large Language Models Seen in 33 sampled listings
- Machine Learning Seen in 43 sampled listings
Application edge
- If these skills match your background, prepare one concrete example that shows how you used Large Language Models and Machine Learning rather than relying on a keyword-only claim.
- The listing states about 5 years of required experience. Check that the dates and scope in your application make that experience easy to verify.
If the named skills are genuinely transferable in your own experience, the occupation map also points to adjacent current families worth researching: Software engineering roles and Product roles. This is exploration context, not a qualification match.
Skill signals come from explicit text mentions. A mention is not automatically a requirement, and absence from the current top-skill list does not make a skill rare or unimportant. The current career comparison draws on 120 sampled listings; 115 contain a recognized skill signal.
Application Decision Lab
Turn the listing into a preparation plan
Separate what the listing actually states from what you still need to prepare or verify. Your selections and short notes stay in this browser and are never submitted to High Paid Job.
At least about 5 years of experience required
The available wording contains an explicit minimum/required years-of-experience signal. Preferred years are tracked separately and never promoted into the required minimum.
Large Language Models
This skill or technology is explicitly mentioned in the available listing text. A mention is not automatically a mandatory requirement; prepare a concrete example only if it is relevant to your experience.
Machine Learning
This skill or technology is explicitly mentioned in the available listing text. A mention is not automatically a mandatory requirement; prepare a concrete example only if it is relevant to your experience.
Questions worth resolving before you rely on the opportunity
- Application closing time: Is there a firm application deadline, a rolling review window or no stated closing date?
- Work authorization / sponsorship: If sponsorship or work authorization matters to you, what exact immigration or employer-sponsorship conditions apply to this role?
- Application process: What interview, assessment, portfolio, reference or screening stages are part of the hiring process?
Decision analysis
What the listing really tells you
A closer look at Engineering Manager, Machine Learning (Safety) at Discord points most strongly to pay has a useful comparison point, the location rules are clear enough to judge, and the entry path is becoming clearer. Those signals shape the practical upside and the questions still worth asking.
Pay has a useful comparison point
Among 39 current comparable salaries in USD, the normalized annual midpoint is around the 99th percentile. This compares advertised pay in the same currency and does not include every element of total compensation.
The location rules are clear enough to judge
The work-location pattern is “Remote with some uncertainty or restrictions”, with Remote Freedom at 62/100. One practical limit to notice is geographic eligibility is restricted to a country or region..
The entry path is becoming clearer
At least about 5 years of experience required · 1 additional stated barrier. Unstated education or experience requirements stay open rather than being assumed.
The visible application effort can be estimated
Provider-mediated application path. The external application may contain additional steps that are not visible from the listing itself.
The listing can be traced to a current source
1 recent enabled source can currently renew this vacancy across 1 source classes. That improves traceability, although it does not verify the employer itself.
How this analysis is assembled
Built from the pay, location, qualification, mobility, application and source details available for this vacancy. Anything the listing leaves unresolved stays unresolved.
Analysis evidence coverage
How much analysis can the current evidence support?
Uses the explainable High Pay Score within the job’s current occupation/seniority/currency comparison sample.
Measures observable location flexibility and explicit restrictions; it does not determine whether remote work is personally desirable.
The configured source supplied structured salary fields, a usable currency and a focused comparison value.
The listing was posted about 13 days ago.
At least one enabled source recently observed the vacancy. The source chain is traceable, but this is not independent employer verification.
There is no universal opportunity score because pay, flexibility and access matter differently to different people. Compare Jobs lets you weight the evidence around your own priorities.
Decision checklist
What is supported, uncertain or worth checking?
This checklist separates supported strengths, visible cautions and missing evidence. It is not an overall recommendation or guarantee that the job is suitable for you.
Supported strengths
- Advertised pay is above much of the current comparable disclosed-salary sample.
Visible cautions
- Geographic eligibility is restricted to a country or region.
- This is remote work with a geographic restriction, not a worldwide-remote vacancy.
- At least about 5 years of experience required
Still unknown
- Visa sponsorship is not established by the available listing data.
Pay vs. barriers
Strong pay with stated barriers to weigh
Pay compares strongly, but qualification or location constraints are also visible. Higher pay does not erase those practical requirements.
Comparable disclosed-pay evidence places this job at about 99 / 100 within its current occupation/seniority sample.
1 explicit required barrier is visible in the available wording.
The listing states at least about 5 years of required experience.
1 explicit Remote Freedom restriction signal is present and is shown separately from qualification requirements.
- Education requirement is not established.
This section weighs pay context against clearly stated barriers without collapsing unlike requirements into one universal score. Degree, experience, licensing, clearance and location limits remain separate, and missing qualification details stay unknown.
Beyond the headline
Not enough evidence for a hidden-value finding
Potential hidden value appears only when several distinct non-pay advantages are actually supported. Missing requirements or benefits are never counted as positives.
The annualized salary midpoint is at or above about 99% of the current comparable disclosed-salary sample.
Still check: At least about 5 years of experience required · The current application path is provider-mediated rather than directly classified as an employer-authorized or official route.
Hidden Value is an experimental evidence summary, not an investment-style score or guarantee of employability. It only uses explicit current listing evidence and does not infer that an unmentioned qualification is unnecessary.
Explainable opportunity highlight
Why this opportunity stands out
These are supported signals from the current listing and comparison sample—not a guarantee that this is the best job for you.
Its annualized salary midpoint is at or above about 99% of the current comparable disclosed-salary sample.
The source provides structured salary information with a comparatively focused range, improving the usefulness of pay comparisons.
Compensation intelligence
How competitive is this pay?
Exceptional pay in current sample
The annualized midpoint is above the 75th percentile boundary of the current comparable sample.
The highlighted band is the middle 50% of the current comparable sample after the outlier guard. The dark marker is this job’s annualized salary midpoint.
Why this analysis?
- This score reflects the current advertised-pay distribution for comparable active jobs in the same currency. It measures pay position, not overall job quality.
- Salary confidence: High. The configured source supplied structured salary fields, a usable currency and a focused comparison value.
- Range quality: Focused salary range.
Employer compensation communication
Pay transparency at Discord
Good current pay transparency
This score uses the employer’s current visible listings and combines how often pay is disclosed with how useful those ranges are. Bonus, equity and benefit mentions are shown separately and do not raise the score.
This pattern comes from the employer’s current visible vacancies. It describes hiring and pay transparency in those listings, not employee satisfaction or a permanent judgement of the employer.
Current employer intelligence
Discord — current opportunity snapshot
Employer Evidence Profile
How often this employer’s current visible sampled vacancies state decision-critical information. These percentages describe evidence coverage, not employer quality.
Current sampled listings with advertised compensation evidence.
Current sampled listings whose work arrangement is clearer than unknown.
Current sampled listings with a supported country signal.
Current sampled listings with an explicit closing time.
Current sampled listings with a usable posting date.
Current sampled listings that explicitly indicate confirmed, possible or unavailable sponsorship evidence.
Current sampled listings with an explicit relocation signal.
Low coverage means the current visible listings state the information less often. It does not prove that the employer lacks the policy, benefit or support.
Common current occupation families: Software engineering (4) · Data & AI (3)
Visible seniority mix: Senior / lead (8)
Current employment-type mix: Full time (9)
Most visible hiring countries in this sample: United States (7)
Other current roles from this employer
QA/DevOps Engineer
USA
Senior / lead · Region-restricted remoteUSD 156,000–175,500 / yearSenior Data Engineer, Ads
USA
Senior / lead · Region-restricted remoteUSD 220,500–245,000 / yearSenior Software Engineer, Application Security
USA
Senior / lead · Region-restricted remoteUSD 196,000–245,000 / yearSenior Stock Administrator
USA
Senior / lead · Region-restricted remoteUSD 132,000–148,500 / yearThese are other current vacancies visible from the same employer, not endorsements or evidence of future hiring plans.
Current disclosed salary medians by currency
- USD 232,750 median · 7 disclosed salaries
Questions worth asking this employer
- If work authorization matters to you, what sponsorship policy applies to this specific role and location?
- If a move is required, is relocation assistance available for this position?
- What is the expected application and interview timeline if the listing does not state a closing date?
These questions are prompted by missing or thin evidence in the employer’s current visible vacancies. Missing evidence is not treated as a negative judgement.
This employer snapshot uses the employer’s current visible listings. Remote and sponsorship rates use only vacancies with explicit evidence, while missing information stays unknown. Salary medians are shown separately by currency and need at least five disclosed salaries. Zero confirmed sponsorship means none was explicitly found in this sample, not that sponsorship is unavailable.
This snapshot describes the employer’s current visible vacancies—things such as pay disclosure and work arrangement. It is not an employee-satisfaction or hiring-quality rating, and different currencies stay separate.
Work-location intelligence
Remote Freedom
Remote with some uncertainty or restrictions
Why this score?
- The role is remote but the source identifies a country or regional restriction.
Location restrictions detected
- Geographic eligibility is restricted to a country or region.
Remote Freedom measures observable location flexibility only. Unknown work-location information remains unscored. Timezone wording is penalized only when it appears restrictive; general collaboration across time zones is not treated as a restriction. A score does not guarantee legal work eligibility, payroll availability or visa sponsorship.
International applicant intelligence
Visa & relocation signals
Sponsorship status is shown only when the listing provides clear enough wording. Employer history or headquarters location is not used to guess an answer.
The available listing details do not contain a clear enough sponsorship statement.
The available listing details do not contain a clear enough relocation statement.
Tradeoff check
What’s the catch?
These are visible conditions worth checking before treating the headline compensation as the whole story:
- This is remote work with a geographic restriction, not a worldwide-remote vacancy.
Current alternatives
Better-paying alternatives
These current roles show a materially higher annualized salary midpoint in the same broad occupation and currency. Similar seniority, country, work arrangement, employment type and recency are preferred where possible; higher pay alone does not make an alternative a better fit.
Staff Machine Learning Engineer
MoonPay · London - Hybrid
USD 5,200–65,000,000 / year On-site / hybridWhy comparable: Same seniority band · Same employment type
Check: The alternative has an unusually broad advertised salary range.
Alternatives are drawn from the current inventory rather than presented as application recommendations. A pay difference needs to be meaningful—about 3% or more at the midpoint—and different currencies are not compared.
Application-path intelligence
What can we see about the application process?
Provider-mediated application path
The current application path comes through a publisher or aggregator. The destination may still lead to an employer-authorized hiring system, but that is not clear enough to assume.
Current destination: jobicy.com · HTTPS
No additional required application step is clear in the available listing text. This does not mean the external application is one-click or friction-free.
Application effort is estimated from visible listing and source details. Optional steps are kept separate from mandatory ones, and the external form may contain additional requirements that are not visible here.
Application safety context
Application safety check
Basic application-safety context available
The current application destination has a basic transport-safety signal such as HTTPS. This does not verify the employer, vacancy, recruiter or application process.
Evidence checked: Source provenance · Application destination · Listing wording
Observable transport-safety signals
- The available application destination uses HTTPS.
Before you share money or sensitive information
- Confirm the vacancy on the employer’s official careers site when practical, especially if a recruiter contacts you outside the listed application path.
- Check that recruiter email domains and application destinations are consistent with the employer or an identifiable recruiting provider.
- Do not pay application, processing, training or equipment fees merely to be considered for a job.
- Do not send cryptocurrency, gift cards, online-banking credentials or PINs as part of an application.
- Treat unusually fast offers or interviews conducted only through informal messaging channels as reasons to verify the employer independently.
This is a limited safety screen, not employer verification and not a fraud determination. Never send money, cryptocurrency, passwords or sensitive banking credentials merely because a listing appears on a job platform.
Original listing details
The section below comes from the listing source. The decision sections above use the job’s structured pay, location, qualification, mobility and application details to give you additional context.
Discord has a highly engaged community of millions of daily active users who use the platform for many different reasons, but there’s one thing that nearly everyone does: play video games. Discord plays a uniquely important role in the future of gaming, and we are focused on making it easier and more fun for people to hang out before, during, and after playing games.
Discord's Safety ML team builds the machine learning systems that protect 200M+ users. The team's mission is to make Discord a place where people can build genuine friendships without exposure to harm, at a scale where manual review alone can never keep up.
We're looking for a highly technical, hands-on, and mission-driven Engineering Manager to lead our Safety ML team. As the manager responsible for Safety ML, you will own the detection systems that sit between attackers and our users; real-time and batch models for content understanding, account integrity, and platform abuse.
What You'll Be Doing
- Build and lead an exceptional team of highly-engaged ML engineers by hiring, coaching, and instilling a sense of ownership and impact.
- Drive the technical vision and roadmap for Safety ML by collaborating with your team and partners across Trust & Safety, Product, Policy, Legal, and Data Science.
- Own the end-to-end lifecycle of production safety models: defining new capabilities, measuring performance, and monitoring the operational health of systems that make millions of enforcement decisions per day.
- Manage processes and leverage your technical expertise to continually raise the bar and ensure your team delivers extraordinary results.
- Partner with Trust & Safety on label quality, golden sets, and automating manual investigations.
- Work with other Engineering Managers to continuously improve the Engineering organization and uphold our workplace philosophy.
What you should have
- You have 5+ years of experience as a Machine Learning Engineer, Data Scientist, or Applied Scientist.
- You have 3+ years of experience as an Engineering Manager and successfully managed a team of 5+ engineers.
- You have hands-on depth in at least one of: abuse/fraud detection, content classification, behavioral modeling, graph-based modeling, or LLM-based classification systems.
- You have strong communication skills and the ability to work well cross-functionally.
- You thrive in ambiguous environments and get excited about figuring out solutions to complex problems, and then executing on them.
- You are a first principles thinker that can work with others to come up with pragmatic solutions.
- You have a proven record of shipping ML systems to production at scale.
- You are passionate about coaching and leading other engineers, but can roll up your sleeves and get elbow deep in code when needed.
- You keep up with the industry trends and continuously identify new technologies to leverage to solve technical problems
The US base salary range for this full-time position is $272,000 to $340,000 + equity + benefits. Our salary ranges are determined by role and level. Within the range, individual pay is determined by additional factors, including job-related skills, experience, and relevant education or training. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include equity, or benefits.
Why Discord?
Discord plays a uniquely important role in the future of gaming. We're a multiplatform, multigenerational and multiplayer platform that helps people deepen their friendships around games and shared interests, and helps developers build and grow their businesses. We believe games give us a way to have fun with our favorite people, whether listening to music together or grinding in competitive matches for diamond rank. Join us in our mission! Your future is just a click away!
Discord is committed to inclusion and providing reasonable accommodations during the interview process. We want you to feel set up for success, so if you are in need of reasonable accommodations, please let your recruiter know.
Please see our Applicant and Candidate Privacy Policy for details regarding Discord’s collection and usage of personal information relating to the application and recruitment process by clicking HERE.
Listing provenance
Where did this job come from?
See where this vacancy came from and whether more than one current source can still support it. Source names help with traceability and attribution; they are not endorsements or guarantees.
At least one enabled source recently observed the vacancy. The source chain is traceable, but this is not independent employer verification.
- Continuity
- One recent renewable source
- Source-class independence
- One renewable source class
- Last source observation
- Observed in the current source window
This records when High Paid Job last observed the vacancy in source evidence. It confirms source presence, not that the employer edited the vacancy at that time.
- 1 enabled source recently observed this vacancy.
Source confidence is about traceability and continuity. It is separate from application safety and should not be read as an employer reputation rating.
The vacancy is supplied by an external job publisher. Source information helps show where the listing came from; it is not a guarantee about the employer or vacancy.
Listing source: Jobicy. Destination: jobicy.com. The application opens in a new tab so you can keep this report open.