Location: San Francisco; Palo Alto
Workplace: Hybrid
ABOUT THE ROLE
We're hiring software engineers for the Model Behavior team to help shape how Perplexity’s AI products behave: the style of their responses, and the way they use tools, skills, and memory. The team designs prompt and context engineering strategies to deliver high-quality user experiences across multiple domains and models.
The ideal candidate for this role has a strong software engineering background, and an analytical, experiment-driven approach to solving challenging problems. You’ll work on context and prompt engineering to shape model behavior and style, and to guide how models use tools, skills, and memory across our products.
WHAT YOU'LL DO
- Context Engineering: Design, test, and optimize the prompts, skills, tools, and memory that shape Perplexity responses across products, features, and use cases. Build self-improvement loops to steer the prompt, improve tool/skill use, and improve the ability to draw on memory.
- Model Releases: Help experiment with and release new models.
- Research & Analysis: Identify inconsistencies and failure modes in model outputs through well-designed research projects, for both internal and production systems.
- Knowledge Sharing: Help engineers across teams build intuition for prompt design and context engineering best practices.
- Staying Current: Track the latest prompting, context engineering, and alignment techniques from industry and academia, and bring the best ideas back to the team.
WHAT WE'RE LOOKING FOR
REQUIRED
- 2 to 10+ years of experience in software engineering or research.
- Strong background in software engineering fundamentals, and a technical understanding of LLM-driven and agentic systems.
- Experience shaping LLM behavior through prompts, tool and skill design, or memory systems.
- Strong written and verbal communication skills, particularly in explaining complex concepts to diverse stakeholders.
NICE TO HAVE
- Recent experience working on modern LLM-driven products.
- Experience working across teams or with external partners.
- Experience designing evaluations or benchmarks for AI systems.
Location: San Francisco; Palo Alto
Workplace: Hybrid
ABOUT THE ROLE
We're hiring software engineers for the Model Behavior team to help shape how Perplexity’s AI products behave: the style of their responses, and the way they use tools, skills, and memory. The team designs prompt and context engineering strategies to deliver high-quality user experiences across multiple domains and models.
The ideal candidate for this role has a strong software engineering background, and an analytical, experiment-driven approach to solving challenging problems. You’ll work on context and prompt engineering to shape model behavior and style, and to guide how models use tools, skills, and memory across our products.
WHAT YOU'LL DO
- Context Engineering: Design, test, and optimize the prompts, skills, tools, and memory that shape Perplexity responses across products, features, and use cases. Build self-improvement loops to steer the prompt, improve tool/skill use, and improve the ability to draw on memory.
- Model Releases: Help experiment with and release new models.
- Research & Analysis: Identify inconsistencies and failure modes in model outputs through well-designed research projects, for both internal and production systems.
- Knowledge Sharing: Help engineers across teams build intuition for prompt design and context engineering best practices.
- Staying Current: Track the latest prompting, context engineering, and alignment techniques from industry and academia, and bring the best ideas back to the team.
WHAT WE'RE LOOKING FOR
REQUIRED
- 2 to 10+ years of experience in software engineering or research.
- Strong background in software engineering fundamentals, and a technical understanding of LLM-driven and agentic systems.
- Experience shaping LLM behavior through prompts, tool and skill design, or memory systems.
- Strong written and verbal communication skills, particularly in explaining complex concepts to diverse stakeholders.
NICE TO HAVE
- Recent experience working on modern LLM-driven products.
- Experience working across teams or with external partners.
- Experience designing evaluations or benchmarks for AI systems.
Location: Hong Kong, Hong Kong SAR; Singapore, Singapore
Staff/Senior Java Engineer, OKX Wallet (Web3)
Who We Are
OKX Wallet is OKX's self-custody wallet, built for users worldwide to securely and conveniently store, manage, and use their on-chain assets. The wallet backend operates in a multi-chain, multi-asset, high-concurrency environment shaped by on-chain state uncertainty and strict fund-security requirements — combining the complex-systems challenges of traditional internet backends with the transaction, signing, and on-chain interaction problems unique to blockchain.
We're looking for a Senior Java Engineer with roughly 5–10 years of backend experience: someone with strong engineering fundamentals who can independently own core modules, exercise sound judgment on complex problems, and proactively coordinate across upstream and downstream teams to drive work to completion.
What You'll Do
Own core wallet backend modules.
Build and continuously improve address management, asset synchronization, transaction construction, broadcasting, on-chain confirmation, gas estimation, nonce management, and transaction-state tracking. Understand each module's role in the full wallet flow, and keep stability, performance, and maintainability front of mind. For complex requirements, break the problem down before choosing an implementation rather than stacking code or reusing old designs.
Build transaction and on-chain interaction scenarios.
Work on transfers, token approvals, contract interactions, cross-chain, swaps, DApp connections, and signature-request handling. Understand a transaction's full lifecycle — from initiation through construction, signing, broadcasting, on-chain confirmation, and final state update — and diagnose issues like stuck transactions, duplicate submissions, state inconsistencies, and on-chain success that isn't reflected in the business system, using logs, on-chain data, and call traces.
Support multi-chain and new-chain integration.
We already support EVM, Tron, and Solana, and continuously onboard new public chains, Layer 2 networks, and asset standards. Contribute to technical research, integration design, and feature development, accounting for differences in address models, account systems, transaction structures, signing methods, fees, and confirmation mechanisms — as well as node stability, asset sync, exception compensation, monitoring, and security boundaries.
Ensure stable operation.
Contribute to day-to-day stability work — monitoring, alerting, rate limiting, graceful degradation, retries, compensation, data reconciliation, and troubleshooting. When incidents occur, help investigate, narrow scope, and fix root causes; for recurring issues, drive systemic fixes such as added monitoring, stronger fallbacks, or design improvements.
Drive your projects to delivery.
Take ownership of the modules and projects you're responsible for. On work spanning product, QA, frontend, infrastructure, or other backend teams, proactively sync information, surface dependencies and risks, and drive issues to resolution. When requirements are unclear or opinions diverge, lay out the context, offer your own judgment, and help build consensus.
Continuously raise engineering quality.
Participate in design discussions, code reviews, and system optimization. Spot unreasonable designs, duplicated logic, and latent risks, and propose actionable improvements. Document technical decisions, post-incident learnings, and best practices, and help less-experienced teammates.
Apply AI in daily development.
Use AI coding tools (Claude Code, Cursor, Codex, etc.) to assist with code comprehension, scaffolding, unit tests, code review, troubleshooting, refactoring, and documentation — validating AI output for correctness, project conventions, performance, and security rather than using it unchecked.
What We're Looking For
Solid Java backend fundamentals.
~5–10 years of Java backend experience with a strong grasp of collections, concurrency, thread pools, the JVM, network communication, and common performance issues. Proficient with Spring Boot, Spring Cloud, MyBatis, or comparable stacks, able to independently design and build medium-to-large backend modules and reason about the mechanics behind the frameworks you use.
Strong system design ability.
Experience with complex or high-concurrency systems; comfortable with idempotency, retries, compensation, caching, message queues, distributed locks, data consistency, rate limiting, and service degradation. Able to own module- or service-level design and clearly explain the core flow, failure scenarios, and key trade-offs.
Cognitive ability and judgment.
Able to understand context and goals on ambiguous problems, separate symptom from root cause, and choose a fitting solution based on business value, user experience, stability, cost, and security — rather than reflexively adding complexity.
Drive and ownership.
Able to independently own a module or project end to end, from design through development, testing, and launch. Proactively communicates and resolves dependencies, risks, and blockers, and follows through on launch outcomes rather than stopping at code merge.
Blockchain or wallet experience.
Experience with wallets, blockchain, trading platforms, on-chain data services, or related systems. Understands addresses, public/private keys, mnemonics, transaction signing, broadcasting, on-chain confirmation, gas, and nonce; familiar with the transaction mechanics of at least one of EVM, Tron, or Solana, and with token standards such as ERC-20 and TRC-20. (Strong backend fundamentals and fast learning can offset gaps in blockchain coverage.)
High security awareness.
Sensitive to private-key, signing, permission, and user-asset security; familiar with replay protection, API authentication, tamper resistance, sensitive-data protection, and least-privilege principles. Actively considers malformed input, duplicate requests, privilege bypass, and data-leak risks when building transaction features.
Independent production troubleshooting.
Able to diagnose live issues via log analysis, metrics monitoring, distributed tracing, and thread/memory analysis; can form hypotheses and narrow scope even with incomplete information. Hands-on experience with performance degradation, timeouts, message backlogs, data inconsistencies, memory issues, or unstable third-party services.
Engineering in the AI era.
Willing to use AI coding tools to improve daily efficiency and able to judge whether AI output meets real business requirements before shipping it. Has a basic understanding of prompts, context management, RAG, AI agents, and MCP, or a genuine willingness to keep learning — treating AI as an engineering tool, not requiring an algorithm/model-training background.
Nice to Have
Integration work on new public chains, new asset standards, or cross-chain protocols
Familiarity with WalletConnect, DApp Browser, or signature-request handling
Knowledge of MPC, multisig, hardware wallets, or TEE-based key-security schemes
Experience with Swap, staking, cross-chain bridges, or DeFi aggregation
Address risk detection, allow/deny lists, anti-fraud, or wallet risk-control experience
High-concurrency transaction systems, blockchain node services, on-chain data indexing, or transaction-state-tracking systems
Familiarity with RPC calls, block scanning, chain reorgs, transaction compensation, and reconciliation mechanisms
JVM performance tuning, stability governance, or complex production-incident experience
Cross-team collaboration with a track record of driving projects to delivery
Real projects built with AI — e.g. AI code review, development agents, MCP servers, intelligent troubleshooting, or knowledge bases
Follows developments in AI coding assistants and LLM applications and shares practical takeaways with the team
Perks & Benefits
Competitive total compensation
Comprehensive insurance coverage for you and your dependents
More benefits to be discussed after you join
Notice:
All official
OKX
vacancies are published on this website.
While roles may appear on selected third-party platforms from time to time, information on other sites may be inaccurate or outdated.
If in doubt, please apply directly through our official careers website.
Information collected and processed as part of the recruitment process of any job application you choose to submit is subject to
OKX
's
Candidate Privacy Notice
.
Location: The Netherlands; Poland; Portugal; France; United Kingdom; Spain; Germany; Italy
Workplace: Remote
About the team
The Security Team is responsible for providing key security capabilities covering application, cloud and enterprise security, incident response, detection and GRC. Our team is looking for an experienced, hands-on security practitioner, who will drive the adoption of modern security processes and tooling, with focus on supporting our engineering and product teams in improving the security posture of our platforms and services.
Note: This position can be fully remote anywhere in the Netherlands.
What you will do:
- Collaborate with engineering and product on improving existing and building new product features with focus on threat modeling, assurance and secure implementation, some examples of recent work include implementation of secure key management, passwordless authentication, m2m authentication, sandboxing and compute/network/storage isolation
- Identify security gaps and vulnerabilities in ClickHouse Cloud and OSS, triage a wide range of vulnerabilities reported via our bug bounty program, responsible disclosure, GitHub Issues covering web, API and server - client assets including low level memory issues like heap or buffer overflows
- Improve and develop security assurance activities - pentests, vulnerability assessments, bug bounty programs, fuzzing
- Drive implementation and usage of engineering security tools - static, dynamic code analysis, dependency checks, code licensing compliance (working knowledge of Snyk, Semgrep, GitHub CodeQL)
- Nurture the engineering - security relationship, identify and implement process and technology improvements
- Handle information security events and incidents across ClickHouse products and services
- Develop processes, tooling and automation to scale security processes and mitigate risks to the business
What you bring along:
- Experience supporting engineering and product implementation efforts by performing threat assessments, assurance activities, advisory as well as, in some cases, implementation work across distributed systems covering web, API, client/server assets
- Strong knowledge of and experience with one or more cloud service providers (e.g. AWS, GCP, Azure), Kubernetes, Cilium
- Experience implementing and operating engineering security tools and processes (e.g. static / dynamic code analysis, software composition analysis, SBOM, OWASP SAMM, client and network fuzzing tools)
- Significant development and automation experience, ability to work with C++ code
- Security as code mindset, with focus on solving problems with automation and scale in mind
Bonus Points:
- BS, MS, or PhD in Computer Science or related field
- Previous contributions to open source projects
- Security or cloud related certifications (AWS, GCP, Azure)
PERKS
- Flexible work environment - ClickHouse is a globally distributed company and remote-friendly. We currently operate in over 25 countries.
- Healthcare - Employer contributions towards your healthcare.
- Equity in the company - Every new eligible team member who joins our company receives equity.
- Time off - Flexible time off in the US, generous entitlement in other countries.
- A USD$500 Home office setup if you’re a remote employee.
- Global Gatherings – We believe in the power of in-person connection and offer opportunities to engage with colleagues at company-wide offsites.
CULTURE - WE ALL SHAPE IT
As part of a rapidly scaling start-up, you will be instrumental in shaping our culture.
Are you interested in finding out more about our culture? Learn more about our values here https://clickhouse.com/company/careers. Check out our blog posts https://clickhouse.com/blog or follow us on LinkedIn https://www.linkedin.com/company/clickhouseinc/life/0c1ee7f4-2129-488d-b413-e7f6270659fd/?viewAsMember=true to find out more about what’s happening at ClickHouse.
EQUAL OPPORTUNITY & PRIVACY
ClickHouse provides equal employment opportunities to all employees and applicants and prohibits discrimination and harassment of any type based on factors such as race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
Please see here https://clickhouse.com/legal/applicant-privacy-notice for our Privacy Statement.
Location: United States
Workplace: Remote
About the team
The Security Team is responsible for providing key security capabilities covering application, cloud and enterprise security, incident response, detection and GRC. Our team is looking for an experienced, hands-on security practitioner, who will drive the adoption of modern security processes and tooling, with focus on supporting our engineering and product teams in improving the security posture of our platforms and services.
What you will do:
- Collaborate with engineering and product on improving existing and building new product features with focus on threat modeling, assurance and secure implementation, some examples of recent work include implementation of secure key management, passwordless authentication, m2m authentication, sandboxing and compute/network/storage isolation
- Identify security gaps and vulnerabilities in ClickHouse Cloud and OSS, triage a wide range of vulnerabilities reported via our bug bounty program, responsible disclosure, GitHub Issues covering web, API and server - client assets including low level memory issues like heap or buffer overflows
- Improve and develop security assurance activities - pentests, vulnerability assessments, bug bounty programs, fuzzing
- Drive implementation and usage of engineering security tools - static, dynamic code analysis, dependency checks, code licensing compliance (working knowledge of Snyk, Semgrep, GitHub CodeQL)
- Nurture the engineering - security relationship, identify and implement process and technology improvements
- Handle information security events and incidents across ClickHouse products and services
- Develop processes, tooling and automation to scale security processes and mitigate risks to the business
What you bring along:
- Experience supporting engineering and product implementation efforts by performing threat assessments, assurance activities, advisory as well as, in some cases, implementation work across distributed systems covering web, API, client/server assets
- Strong knowledge of and experience with one or more cloud service providers (e.g. AWS, GCP, Azure), Kubernetes, Cilium, Crossplane
- Experience implementing and operating engineering security tools and processes (e.g. static / dynamic code analysis, software composition analysis, SBOM, OWASP SAMM, client and network fuzzing tools)
- Significant development and automation experience, ability to work with C++ code preferred
- Security as code mindset, with focus on solving problems with automation and scale in mind
Bonus Points:
- BS, MS, or PhD in Computer Science or related field
- Previous contributions to open source projects
- Security or cloud related certifications (AWS, GCP, Azure)
PERKS
- Flexible work environment - ClickHouse is a globally distributed company and remote-friendly. We currently operate in over 25 countries.
- Healthcare - Employer contributions towards your healthcare.
- Equity in the company - Every new eligible team member who joins our company receives equity.
- Time off - Flexible time off in the US, generous entitlement in other countries.
- A USD$500 Home office setup if you’re a remote employee.
- Global Gatherings – We believe in the power of in-person connection and offer opportunities to engage with colleagues at company-wide offsites.
CULTURE - WE ALL SHAPE IT
As part of a rapidly scaling start-up, you will be instrumental in shaping our culture.
Are you interested in finding out more about our culture? Learn more about our values here https://clickhouse.com/company/careers. Check out our blog posts https://clickhouse.com/blog or follow us on LinkedIn https://www.linkedin.com/company/clickhouseinc/life/0c1ee7f4-2129-488d-b413-e7f6270659fd/?viewAsMember=true to find out more about what’s happening at ClickHouse.
EQUAL OPPORTUNITY & PRIVACY
ClickHouse provides equal employment opportunities to all employees and applicants and prohibits discrimination and harassment of any type based on factors such as race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
Please see here https://clickhouse.com/legal/applicant-privacy-notice for our Privacy Statement.
Location: USA
Workplace: remote
JTX is our trading app, and it runs on the fastest market infrastructure on Solana, which we also built. What nobody has done yet is make that speed something a trader can feel. That is this job.
JTX is live. Two frontend engineers built it to this point and you would be the third. The work now is one to a hundred: harden what exists, make it hold up under real volume, expand onto mobile, and raise the ceiling on every screen a trader touches.
We're a small team with product-market fit. That means:
High ownership: every team member drives significant technical decisions and shapes our product roadmap.
Fast execution: we ship rapidly and iterate based on real-world feedback. Progress, not motion.
High quality bar: the details are the product. We don't trade them for speed.
About the Position
You'll own the surface of JTX across web and mobile: order entry, market data, charts, positions, execution quality, onboarding, and the wallet flows underneath all of it.
The role suits a generalist with strong taste. You'll partner with design, product, and the infrastructure team, and you'll make architectural calls that stick for years. If you've spent time thinking about how markets actually work on Solana and want to build the product layer on top of that, this is the role.
Stack: React 19 + TypeScript on Next.js. Jotai + TanStack Query. Tailwind with a token-based design system. TradingView Advanced Charts on our own datafeed. Privy wallets. WebSockets to our engine. Web ships as a PWA; native mobile apps are in development.
What's Hard Right Now
Data freshness: several live WebSocket streams (order book, trades, candles, stats) feed many panels at once; keeping them fast, consistent with each other, and honest through async gaps (stale quotes, pending fills)
Performance: a data-dense terminal that stays smooth under constant streaming updates, including on mid-range hardware
Security: wallet signing, session auth, strict CSP, hardened supply chain
Shipping volume: three engineers own the entire surface of a live exchange; the backlog is bigger than the team, so throughput and prioritization are part of the job
Keeping product behavior and design language consistent between web and mobile while being very attentive to nuances of each mobile platform
Making execution quality something a trader can see in a glance instead of something they take on faith
What You'll Do
Build and own the JTX client across web and mobile
Ship real-time trading interfaces: order books, charts, order entry, positions, fill and execution visibility
Hit tight latency and render budgets against streaming market data, and decide what belongs on the client versus the server
Build wallet and signing flows, including self-custodial and embedded wallet onboarding
Own the shared component, state, and data layers the rest of the product team builds on
Make architectural decisions that hold as the codebase, the team, and the user base grow by an order of magnitude
Ship fast, watch real users, iterate
What We're Looking For
Attention to detail bordering on obsessive. You can look at a screen and say what is wrong with it, and it bothers you until it's fixed.
5+ years building production frontend, including something real-time, data dense, or financial
Deep React and TypeScript. You can explain why a component re-rendered and then fix it.
Mobile experience: React Native, Expo, or native iOS and Android
Strong fundamentals: browser performance, memory, websockets, network behavior under load
Security-first instincts around signing flows, key handling, and what should never touch a log
Comfortable in a codebase that is already live. You can refactor and clean up without stopping shipping.
Able to weigh business and engineering tradeoffs, and to explain complicated things simply
Relevant Background
If you have experience in any of the following, you may be a good fit:
Trading terminals, exchange or brokerage frontends
Consumer fintech apps at scale
Charting, time series, or high-frequency data visualization (canvas, WebGL)
Solana or EVM app development, wallet integrations, transaction signing
Maintaining a public TypeScript library or design system
Location: Remote - Bengaluru, India
MinIO is the data and memory foundation for enterprise AI. Built for the speed, scale, and economics that AI and analytics demand, AIStor and MemKV unify every layer of the data stack, from agentic and inference context memory to tables and objects across core, edge, and cloud. Trusted by 77% of the Fortune 100, MinIO is redefining how AI factories, intelligent applications, and autonomous agents secure, persist, and unlock the full value of their data.
The Field Architect role at MinIO is a senior customer-facing technical leadership position focused on defining, validating, and guiding AIStor architectures for AI, analytics, cloud-native applications, and large-scale data infrastructure. You will serve as a trusted technical advisor to customers, partners, and internal teams, translating business and application requirements into robust technical designs that deliver measurable outcomes.
You will collaborate closely with the broader MinIO team to ensure customers are successful through technical discovery, architecture design, proof-of-value execution, production onboarding, performance validation, and long-term expansion. Success in this role requires deep technical curiosity, hands-on architecture skills, strong communication, and the ability to connect AIStor’s capabilities to the data-intensive workloads that matter most to our customers.
What You Will Do:
Technical Leadership & Architecture
Technical Architecture and Discovery: Lead technical discovery with customers and partners to understand their business goals, application requirements, data architecture, infrastructure constraints, and success criteria. Define scalable AIStor architectures that map directly to those requirements.
AI and Analytics Workload Design: Define and validate AIStor architectures for AI/ML training and inference, analytics platforms, data lakehouse environments, high-performance data pipelines, large object workloads, and modern application data services.
Object Storage and S3 Expertise: Serve as a subject matter expert in object storage, S3-compatible architectures, distributed systems, metadata, replication, erasure coding, security, performance tuning, and large-scale namespace design.
Customer Engagement & Advisory
Customer Technical Advisor: Build trusted relationships with customer technical stakeholders, including infrastructure, platform, analytics, AI, security, application, and operations teams. Guide customers toward informed architecture decisions and proactively identify opportunities to improve performance, resilience, scale, and operational efficiency.
Proof-of-Value Execution: Lead technical evaluations, system configurations, performance testing, interoperability validation, and proof-of-value engagements that demonstrate AIStor’s value in real customer environments.
Customer Success Beyond the Win: Partner with Customer Engineering, Product Management, and Engineering teams to help customers move from evaluation to production and from initial deployment to broader adoption across additional workloads, teams, and use cases.
Ecosystem, Enablement & Field Operations
Cloud-Native and Kubernetes Guidance: Provide technical leadership on Kubernetes, containers, automation, and cloud-native deployment patterns, including hybrid cloud, private cloud, public cloud, and edge infrastructure models.
Solution Integration and Ecosystem Collaboration: Work with technology partners, reseller partners, and customer teams to support complete solutions involving analytics engines, AI platforms, Kubernetes distributions, data protection tools, identity systems, observability platforms, and public cloud services.
Technical Presentations and Enablement: Build and deliver compelling architecture presentations, whiteboard sessions, demonstrations, best practices, workshops, and technical enablement sessions for customers, partners, and internal teams.
RFP, RFI, and Technical Response Support: Contribute to or lead technical portions of RFPs, RFIs, RFQs, security reviews, architecture questionnaires, and competitive evaluations.
Product Intelligence & Market Expertise
Product and Engineering Feedback: Advocate for customer requirements internally by capturing field feedback, competitive insights, workload patterns, integration needs, and enhancement opportunities. Work with Product and Engineering teams to help inform roadmap priorities and improve customer outcomes.
Competitive and Market Expertise: Stay current on object storage, data lakehouse, AI infrastructure, analytics, Kubernetes, cloud, and competitive storage trends. Help internal teams and customers understand where AIStor is differentiated.
Your Skills and Experience:
Strong background in enterprise storage, object storage, distributed systems, cloud infrastructure, data platforms, or high-performance data-intensive applications.
Strong understanding of object storage concepts and S3-compatible architectures; experience with HTTP, REST APIs, JSON, security models, replication, data protection, and scale-out system design is highly valuable.
10+ years of experience in a senior customer-facing technical role such as Field Architect, Solutions Architect, Sales Engineer, Systems Engineer, or Technical Consultant.
Hands-on experience with Linux, networking, storage systems, virtualization, containers, Kubernetes, and modern data center infrastructure.
Experience designing or supporting AI, machine learning, analytics, data lakehouse, or large-scale data pipeline environments.
Familiarity with ecosystem technologies such as Databricks, Starburst, Spark, Trino, Iceberg, Delta Lake, Kafka, PyTorch, TensorFlow, or other AI and analytics frameworks is a strong plus.
Experience with public cloud and hybrid cloud environments, including AWS, Azure, GCP, OCI, or private cloud platforms.
Ability to conduct technical discovery, design architectures, build demonstrations, guide proof-of-value execution, analyze performance, and communicate tradeoffs clearly.
Comfortable working with heterogeneous enterprise environments involving compute, storage, networking, security, identity, observability, backup, disaster recovery, and application teams.
Strong verbal, written, whiteboarding, and presentation skills, with the ability to communicate complex technical concepts to both technical and executive audiences.
Ability to work collaboratively across customers, partners, Sales, Product, Engineering, and Customer Engineering teams.
Strong customer-success orientation, intellectual curiosity, sense of ownership, and ability to prioritize effectively in a fast-moving environment.
Willingness to travel as needed to support customers, partners, field events, and internal team activities.
Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related technical field; equivalent practical experience will also be considered.
Equal Opportunity Policy (EEO)
MinIO is proud to be an equal opportunity workplace and an affirmative action employer. We review applications for employment without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, ancestry, citizenship, age, veteran status, genetic information, physical or mental disability, medical condition, marital status, or any other basis prohibited by law.
Задачи:
— Проектировать архитектуру сервисов верификации, подписей и платежей
— Внедрять ZK-схемы для приватных атрибутов
— Разрабатывать интеграции с Ethereum и PoA-сетью
— Работать с гибридным хранилищем: PostgreSQL, ScyllaDB, Redis, MongoDB
Требования:
— Гражданство РФ или РБ
— Опыт работы от 1 года с криптографией: хеширование, подписи, ZK-proofs
— Опыт работы от 2 лет с блокчейном: транзакции, gas, события, взаимодействие со смарт-контрактами
— Опыт работы от 1 года с Solidity и с ethers.js / viem / web3.js
— Опыт работы с Rust от 1 года
— Опыт работы с GraphQL от 3 лет
— Опыт работы от 6 лет с Node.js и TypeScript: event loop, streams, memory management
Условия:
— Fully remote work format
— Only fulltime
— Оформление по ТК РФ после ИС
— Компания аккредитована в «Минцифре»
— 100% оплата больничного
— Оплачиваемый отпуск 28 календарных дней
— Работа в продуктовой компании
Дополнительная информация:
— Кандидаты с преобладающим или последним опытом в роли технических менеджеров: Team Lead, CTO и т.п. не подходят
— Совмещение не допускается
— Требуется гражданство РФ или РБ
— Проживание в любой стране при условии часового пояса UTC+3
УдалённоПроживание в любой стране при условии часового пояса UTC+3
Location: Remote, Global
ABOUT SUPABASE
Supabase is the Postgres development platform, built by developers for developers. We provide a complete backend solution including Database, Auth, Storage, Edge Functions, Realtime, and Vector Search. All services are deeply integrated and designed for growth.
ABOUT THIS ROLE
We’re hiring experienced performance engineers to make performance measurement at Supabase rigorous, repeatable, and actionable by product teams. This role owns the benchmarking and profiling systems we use to detect regressions, explain performance changes, and publish credible numbers for customers and the market. You’ll build the tooling and the methodology and make it easy for product teams to use it correctly.
You’d join a new performance team as one of its first members, working alongside a deeply seasoned performance engineer, with the team growing to roughly six this year. There’s no legacy process to inherit — you’ll help define how we measure and communicate performance metrics at Supabase.
WHAT YOU’LL DO
- Build and evolve benchmarking, profiling, and load-testing tooling (cloud, database, and end-to-end).
- Define benchmark suites and reference workloads that reflect real customer behavior (and evolve them as the products change).
- Establish performance baselines and regression gates across products (variance tracking, environment control, and detection of changes).
- Build mechanisms that turn benchmark results into action: triage workflows, owner routing, and clear, reproducible reports.
- Partner closely with database teams (e.g. Multigres, OrioleDB) to identify bottlenecks and land concrete performance improvements.
- Enable the company to publish credible, repeatable performance numbers for customers and the market.
- Help teams self-serve performance testing and make performance a first-class engineering concern.
PROBLEMS YOU MIGHT WORK ON
- Build our continuous benchmarking infrastructure so product teams can spot performance regressions early. Ideally, teams can run benchmarks directly on PRs or locally while developing a feature.
- Analyze and eliminate issues with load generators, workloads or benchmark environments to ensure that benchmarks are reliable indicators for actual product performance.
- Build regression triage tooling that pinpoints what changed (diffing, profiles/traces, query-level attribution).
- Help product teams so they can analyze the root cause of performance regressions in benchmark environments themselves.
WHAT WE’RE LOOKING FOR
- Deep experience in performance engineering, benchmarking, and profiling of complex distributed systems. Specifically, you have owned benchmarking systems where reproducibility and controlling variance mattered.
- Strong systems intuition (databases, storage, networking, cloud infrastructure).
- Comfortable working across product, infra, and database teams.
- Pragmatic, tooling-oriented mindset with strong communication skills.
- Depth on at least one end of that stack: Linux kernel internals (virtual memory, scheduling, networking, IO) or database internals (query planning, storage engines, buffer and WAL management)
WHAT WE OFFER
- Fully Remote
We hire globally. We believe you can do your best work from anywhere. There are no Supabase offices, but we provide a WeWork membership or co-working allowance you can use anywhere in the world.
- ESOP
Every team member receives ESOP (equity ownership) in the company. We want everyone to share in the upside of what we’re building together.
- Tech Allowance
Use this budget to set up your ideal work environment—laptop, monitor, headphones, or whatever helps you do your best work.
- Health Benefits
Supabase covers 100% of health insurance for employees and 80% for dependents, wherever you are. Your wellbeing and your family’s health are important to us.
- Annual Off-Sites
Once a year, the entire company gathers in a new city for a week of connection, collaboration, and fun. It’s a highlight of our year.
- Flexible Work
We operate asynchronously and trust you to manage your own time. You know what needs to be done and when.
- Professional Development
Every team member receives an annual education allowance to spend on learning—courses, books, conferences, or anything that supports your growth.
ABOUT THE TEAM
Supabase was born-remote and open-source-first. We believe our globally distributed team is our secret weapon in building tools developers love.
- ~400 team members
- 60+ countries
- 20+ languages spoken
- Over $1B raised (including our $500M Series F)
- 540,000+ community members
We move fast, build in public, and use what we ship. If it’s in your project, we probably use it in ours too. We believe deeply in the open-source ecosystem and strive to support—not replace—existing tools and communities.
Location: Remote, Global
ABOUT SUPABASE
Supabase is the Postgres development platform, built by developers for developers. We provide a complete backend solution including Database, Auth, Storage, Edge Functions, Realtime, and Vector Search. All services are deeply integrated and designed for growth.
ABOUT THE ROLE
We're hiring experienced performance engineers to find and land performance wins across the Supabase stack — from the query optimiser to block device level, and across the network paths and cloud infrastructure that connect our distributed platform. This is a performance delivery role: real, measured improvements to our database, platform, and APIs as we scale toward enterprise and platform-grade workloads. The methodologies you develop and tooling you build exist to multiply that delivery.
You'd join a new performance team as one of its first members, working alongside a deeply seasoned performance engineer, with the team growing to roughly six this year. There's no legacy process to inherit — you'll help define how performance engineering works at Supabase.
WHAT YOU'LL DO
- Find bottlenecks in live production systems and characterize them precisely enough that the owning team can act on them without you in the room.
- Partner closely with database teams (e.g. Multigres, OrioleDB) and infra teams to land concrete performance improvements.
- Build, communicate, and evolve performance methodologies and tooling that turn live production data into actionable insight.
- Partner with the observability team to capture the right signals and establish a unified view of platform performance (latency, throughput, tail behavior) across products.
- Help teams self-serve performance analysis and make performance a first-class engineering concern.
PROBLEMS YOU MIGHT WORK ON
- Tune the kernel's paging behavior to production workloads
- Reduce memory overhead in OrioleDB and Multigres
- Identify and eliminate sources of latency spikes from application to kernel level
- Identify scalability bottlenecks across the entire stack and work the appropriate teams in Supabase and the wider community to resolve them
WHAT WE'RE LOOKING FOR
- Deep experience in performance engineering, specifically performance analysis of complex distributed systems.
- You can walk the whole stack: follow a tail-latency problem from the query optimizer through the syscall boundary to the IO scheduler — or across pooler hops, network paths, and availability zones — reading profiles and traces at every layer.
- Depth on at least one end of that stack: Linux kernel internals (virtual memory, scheduling, networking, IO) or database internals (query planning, storage engines, buffer and WAL management)
- Strong working knowledge of networking and cloud infrastructure performance: TCP behavior under load, network virtualization overhead, and the performance characteristics of AWS primitives (EBS throughput and IOPS, instance network limits, placement groups, cross-AZ latency).
- Proven ability to turn performance insights into real product and architecture improvements — including getting teams you don't belong to to prioritize and ship the fix.
- Strong written communication: your problem characterisations are precise, reproducible, and compelling on their own.
- Pragmatic, tooling-oriented mindset; comfort working across product, infra, and database teams.
WHAT WE OFFER
- Fully Remote
We hire globally. We believe you can do your best work from anywhere. There are no Supabase offices, but we provide a WeWork membership or co-working allowance you can use anywhere in the world.
- ESOP
Every team member receives ESOP (equity ownership) in the company. We want everyone to share in the upside of what we’re building together.
- Tech Allowance
Use this budget to set up your ideal work environment—laptop, monitor, headphones, or whatever helps you do your best work.
- Health Benefits
Supabase covers 100% of health insurance for employees and 80% for dependents, wherever you are. Your wellbeing and your family’s health are important to us.
- Annual Off-Sites
Once a year, the entire company gathers in a new city for a week of connection, collaboration, and fun. It’s a highlight of our year.
- Flexible Work
We operate asynchronously and trust you to manage your own time. You know what needs to be done and when.
- Professional Development
Every team member receives an annual education allowance to spend on learning—courses, books, conferences, or anything that supports your growth.
ABOUT THE TEAM
Supabase was born-remote and open-source-first. We believe our globally distributed team is our secret weapon in building tools developers love.
- ~400 team members
- 60+ countries
- 20+ languages spoken
- Over $1B raised (including our $500M Series F)
- 540,000+ community members
We move fast, build in public, and use what we ship. If it’s in your project, we probably use it in ours too. We believe deeply in the open-source ecosystem and strive to support—not replace—existing tools and communities.
Location: Europe; United States
Workplace: Remote
ABOUT CANTINA:
Cantina Labs is a social AI company, developing a suite of advanced real-time models that push the boundaries of expression, personality, and realism. We bring characters to life, transforming how people tell stories, connect, and create. We build and power ecosystems. Cantina, our flagship social AI platform, is just the beginning.
If you're excited about the potential AI has to shape human creativity and social interactions, join us in building the future!
ABOUT THE ROLE:
We are looking for an ML Engineer to own the production inference stack for our text-to-speech (TTS) and speech recognition (ASR) models, end to end. Our research team delivers trained model checkpoints; you will productionize them as low-latency, real-time streaming services that run cost-efficiently on GPUs. The role covers the inference engines, the Kubernetes infrastructure they run on, and the performance benchmarking and accuracy validation that let us ship changes safely. You will bridge research and production, and own latency, throughput, cost and accuracy as we scale.
WHAT YOU’LL DO:
- Build and optimize streaming inference engines for TTS and ASR models, including multi-stage model pipelines.
- Optimize latency (time to first chunk, p50/p99) and throughput using continuous batching, CUDA Graphs, torch.compile and mixed precision.
- Maintain numerical parity with the reference implementation through automated accuracy regression tests, per stage and end to end.
- Deploy and operate GPU inference services on Kubernetes: autoscaling, containerization and infrastructure as code.
- Build CI/CD for model artifacts, with model versioning and reproducible releases.
- Own observability and performance benchmarking: p50/p99 latency, real-time factor (RTF), GPU utilization and cost per request.
- Partner with research to productionize new models.
WHAT YOU’LL BRING:
- Hands-on experience deploying, scaling and optimizing ML models in production, beyond consuming model APIs.
- Working knowledge of the full inference stack, from CUDA kernels to serving frameworks, with depth in some layers; expertise across all of them is not expected.
- GPU performance optimization: profiling (Nsight Systems, PyTorch Profiler), memory bandwidth, CPU-GPU synchronization.
- Solid understanding of model serving: continuous batching, KV cache management, request scheduling.
- Production experience with Kubernetes, CI/CD and cloud infrastructure.
- Strong Python and PyTorch, and a rigorous approach to performance benchmarking.
- Experience with speech or audio models (TTS, ASR, voice conversion).
- Experience with inference frameworks such as vLLM (vLLM-Omni), SGLang, TensorRT-LLM, TensorRT or Triton Inference Server.
COMPENSATION:
When determining compensation, a number of factors will be considered, including skills, experience, job scope, location, and competitive compensation market data.
BENEFITS FOR U.S.-BASED ROLES:
- Competitive salary and generous company equity
- Medical, dental, and vision insurance – 99.99% of premiums covered by Cantina
- 42 days of paid time off, including:
- 15 PTO days
- 10 sick days
- 15 company holidays
- 2 floating holidays
- Generous parental leave & fertility support
- 401(k) retirement savings plan
- Lifestyle spending account – $500/month to use however you’d like
- Complimentary lunch and snacks for in-office employees
- One Medical membership, and more!
Location: ES - Barcelona, Spain
We are looking for a
Senior Graphics Engineer
in Ireland, UK, Spain, or Portugal in a hybrid or remote basis. We can support with visa sponsorship from any location.
We are looking for strong rendering expertise and a passion for delivering high-quality, high-performance visuals. You will work on real-time rendering features and optimizations that help our game look and run its best across a wide range of devices.
We are in the early stages of development on an ambitious, unannounced, cross-platform Strategy/MMO title, creating a team of talented and passionate game makers to join us on this exciting journey!
At Scopely, we care deeply about what we do and want to inspire play, every day — whether in our work environments alongside our talented colleagues or through our deep connections with our communities of players. We are a global team of game lovers who are developing, publishing, and innovating the mobile games industry, connecting millions of people around the world daily.
What You Will Do
Develop and optimize real-time rendering features on mobile platforms using Vulkan (Android) and Metal (iOS).
Work with clustered/meshlet-based geometry systems, implementing GPU-driven visibility, culling, and LOD.
Integrate and refine modern rendering techniques such as clustered/tiled lighting, temporal anti-aliasing (TAA), and super-resolution (TSR).
Assist in the development of real-time global illumination features in collaboration with senior technical staff, ensuring scalability across different device tiers.
Write and optimize shaders (HLSL/GLSL/MSL) for power-efficient mobile performance.
Profile GPU/CPU performance and analyze rendering bottlenecks using tools like RenderDoc, Perfetto, Xcode GPU Debugger, and Mali/Snapdragon profilers.
Contribute to GPU memory layout design, draw submission strategies, and render pass optimizations for tile-based GPUs.
Collaborate closely with engine and content teams to ensure visuals meet quality and performance goals across platforms.
Stay informed on industry rendering trends and suggest improvements to our pipeline.
What We Are Looking For
5+ years of graphics programming experience, with a focus on mobile platforms.
Strong C++ skills with experience working in performance-critical rendering code.
Solid knowledge of Vulkan and/or Metal APIs.
Experience with Unity’s Scriptable Render Pipeline (SRP), including extending or customizing SRPs.
Understanding of mobile GPU architecture (tiling, bandwidth, power constraints).
Proficiency in GPU performance profiling and optimization workflows.
Familiarity with compute-based rendering techniques, GPU-driven pipelines, and modern culling/visibility approaches.
Bonus Points
Experience with UE5’s Nanite/Lumen or equivalent advanced rendering solutions.
Background in custom engine development or low-level rendering systems.
Contributions to open-source graphics tools or technical publications.
Cross-platform rendering experience beyond mobile (PC/console).
This role can be based
remotely
in the UK, Ireland, Portugal, Spain or from our
Barcelona
hub on a
hybrid basis
. If you're open to working in any of these locations, there's no need to apply more than once. We'll discuss location preferences during the hiring process.
About Scopely
Scopely is a leading video game and global interactive entertainment company, home to many of the world’s most beloved and enduring experiences, including two of the most successful mobile games of all-time “MONOPOLY GO!” and “Pokémon GO,” along with “Stumble Guys,” “Star Trek™ Fleet Command,” “MARVEL Strike Force,” “WWE Champions,” the Scrabble® franchise, “Yahtzee® With Buddies,” and many others. Across mobile, web, PC, and console, Scopely creates, develops, publishes, and live-operates one of the most diversified and award-winning portfolios in the games industry — bringing hundreds of millions of players together through a shared love of play.
Founded in 2011, Scopely is powered by its exceptional team — including thousands of world-class gamemakers around the globe, a distinctive tenet-driven culture, and its proprietary technology platform, Playgami. Together, these strengths have fueled Scopely’s position as the #1 mobile games company in the U.S. and #2 globally, generating more than $10 billion in lifetime revenue. Whether building global sensations like “MONOPOLY GO!” from the ground up, or expanding through strategic acquisitions, including the FoxNext, GSN, and Scopely Explore games businesses — Scopely consistently delivers experiences players love today and return to for years to come.
Recognized multiple times as one of the "100 Most Influential Companies in the World" by TIME magazine and one of Fast Company's "World's Most Innovative Companies" and “Best Workplaces for Innovators,” Scopely believes that video games can be a force for good — creating meaningful connections, vibrant communities, and making life better through play.
Scopely has global operations and partners across four continents in more than a dozen countries worldwide. For more information, visit:
https://www.scopely.com/
.
Notice to Candidates: Scopely will never request payment or financial information during the application or hiring process. Please apply only through our official
website
and verify that all Talent Partner communications come from an email address ending in @
scopely.com
.
Should you have any questions or encounter any fraudulent requests/emails/websites, please immediately contact recruiting@scopely.com. Our job applicant privacy policies are available here:
California Privacy Notice
and
EEA/UK Privacy Notice
.
Employment at Scopely is based solely on a person's merit and qualifications. Scopely does not discriminate against any employee or applicant because of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), or any other basis protected by law. We also consider qualified applicants with arrest or conviction records, consistent with applicable federal, state and local law.
Location: Singapore
About the Company
Our client is a stealth AI startup backed by one of Southeast Asia's leading technology companies and is currently building its global founding team.
The company is developing an AI-native communication platform designed to simplify everyday tasks by integrating AI directly into conversations. Instead of switching between multiple applications, users can plan, organize, compare, research, and complete tasks within a single intelligent assistant.
Serving a market of billions of users still relying on traditional productivity tools, the platform focuses on delivering reliable AI workflows, persistent context, multi-step reasoning, and seamless task execution. The mission is to create an AI assistant that significantly improves productivity while making everyday work simpler and more intuitive.
About the Role
Our client is seeking a
VP of Research (Machine Learning)
to define and lead the research direction behind its AI platform. This leadership role will shape how AI systems reason, learn, evaluate, and continuously improve within a product designed for high-frequency, real-world usage.
Working closely with product and engineering leadership, this position will drive the long-term intelligence strategy, balancing cutting-edge research with practical production impact.
Key Responsibilities
Define and evolve the research roadmap for the platform's core AI intelligence, including context representation, memory, reasoning, planning, and orchestration.
Evaluate and determine when to develop proprietary model architectures versus leveraging or adapting frontier open-source and commercial AI models.
Design evaluation frameworks that measure real-world performance, robustness, safety, and long-term system behavior beyond traditional benchmark metrics.
Lead the company's AI alignment, safety, and guardrail strategy as a core component of product development.
Drive research and experimentation across advanced machine learning techniques, including:
Retrieval-Augmented Training (RAG)
Mixture of Experts (MoE)
Model Distillation
Multi-Agent Orchestration
Multimodal AI Systems
Partner closely with product and engineering teams to define and execute the intelligence strategy for AI-powered applications.
Establish and maintain high standards for research quality, technical judgment, and engineering excellence across the organization.
Requirements
Extensive experience designing, building, and deploying machine learning systems in production environments.
Strong technical expertise in model behavior, failure analysis, system evaluation, and long-term AI performance.
Proven ability to translate advanced research into reliable, production-ready AI solutions.
Demonstrated experience making high-impact technical decisions in fast-moving and ambiguous environments.
Deep understanding of AI evaluation methodologies, model robustness, safety, and system reliability.
Strong ownership mindset with the ability to lead technical strategy and execution.
Passion for building practical AI systems that deliver measurable real-world impact rather than focusing solely on academic research or benchmark performance.
Preferred Technical Skills
Experience with the following technologies is preferred:
Python
PyTorch and/or JAX
GPU-based model training and inference systems
Location: Singapore
About the Company
Our client is a stealth AI startup backed by one of Southeast Asia's leading technology companies and is currently building its global founding team.
The company is developing an AI-native communication platform designed to simplify everyday tasks by integrating AI directly into conversations. Instead of switching between multiple applications, users can plan, organize, compare, research, and complete tasks within a single intelligent assistant.
Serving a market of billions of users still relying on traditional productivity tools, the platform focuses on delivering reliable AI workflows, persistent context, multi-step reasoning, and seamless task execution. The mission is to create an AI assistant that significantly improves productivity while making everyday work simpler and more intuitive.
About the Role
Our client is seeking a
Technical Lead, Machine Learning
to lead the execution of its AI platform by translating research into scalable, production-ready machine learning systems. This role sits at the intersection of research, infrastructure, and product, with responsibility for ensuring models are trainable, deployable, observable, and optimized for real-world performance.
Working closely with research, engineering, and product teams, this position will drive the development of robust ML infrastructure while balancing performance, reliability, latency, and cost.
Key Responsibilities
Lead the end-to-end execution of machine learning systems, including data pipelines, training workflows, evaluation frameworks, inference architecture, and production deployment.
Fine-tune and optimize models using modern techniques such as
LoRA, QLoRA, Supervised Fine-Tuning (SFT), Direct Preference Optimization (DPO), and model distillation
.
Design, build, and operate scalable inference systems with a focus on latency, cost efficiency, and reliability.
Develop and maintain data pipelines for both synthetic and real-world training datasets.
Build evaluation frameworks to measure model performance, robustness, safety, and bias in collaboration with research teams.
Optimize production deployments through GPU utilization, memory efficiency, inference optimization, and scaling strategies.
Partner closely with application engineering teams to integrate machine learning systems into backend, desktop, and mobile products.
Continuously improve production systems through rapid iteration, monitoring, and data-driven optimization.
Requirements
Proven experience building and deploying production-grade machine learning systems used by real users.
Strong expertise working with large language models and understanding model behavior, limitations, and failure modes.
Experience developing scalable ML infrastructure, training pipelines, and inference systems.
Strong software engineering skills with the ability to write maintainable, production-quality code.
Experience balancing real-world production constraints, including latency, reliability, scalability, cost, and safety.
Strong ownership mindset with the ability to independently drive technical initiatives from design through deployment.
Excellent communication and collaboration skills, with experience working in cross-functional, high-performing engineering teams.
Preferred Technical Skills
Experience with the following technologies is preferred:
Python
PyTorch and/or JAX
GPU-based model training and inference systems
Location: Singapore
About the Company
Our client is a stealth AI startup backed by one of Southeast Asia's leading technology companies and is currently building its global founding team.
The company is developing an AI-native communication platform designed to simplify everyday tasks by integrating AI directly into conversations. Instead of switching between multiple applications, users can plan, organize, compare, research, and complete tasks within a single intelligent assistant.
Serving a market of billions of users still relying on traditional productivity tools, the platform focuses on delivering reliable AI workflows, persistent context, multi-step reasoning, and seamless task execution. The mission is to create an AI assistant that significantly improves productivity while making everyday work simpler and more intuitive.
About the Role
Our client is seeking a
Principal Machine Learning Engineer
to build and deploy production-grade machine learning systems that power its AI platform. This role focuses on translating research into scalable solutions by developing robust training pipelines, inference systems, evaluation frameworks, and deployment infrastructure.
Working closely with research and application engineering teams, this position will play a key role in delivering reliable, high-performance ML systems that operate effectively under real-world production constraints.
Key Responsibilities
Build and own end-to-end machine learning pipelines covering data processing, model training, evaluation, inference, and deployment.
Fine-tune and adapt models using modern techniques such as LoRA, QLoRA, Supervised Fine-Tuning (SFT), Direct Preference Optimization (DPO), and model distillation.
Design and operate scalable inference systems while balancing latency, cost, and reliability.
Develop and maintain data pipelines for both synthetic and real-world training datasets.
Build evaluation frameworks to assess model performance, robustness, safety, and bias in collaboration with research teams.
Optimize production deployments through GPU optimization, memory efficiency, latency reduction, and scaling strategies.
Collaborate with application engineering teams to integrate machine learning systems into backend, mobile, and desktop applications.
Continuously improve ML systems through rapid iteration and real-world performance monitoring while balancing production constraints such as latency, cost, reliability, and safety.
Requirements
Strong background in deep learning and transformer-based architectures.
Hands-on experience training, fine-tuning, or deploying large-scale machine learning models in production.
Proficiency with modern machine learning frameworks such as
PyTorch
or
JAX
.
Experience with distributed training and inference frameworks, including technologies such as
DeepSpeed, FSDP, Megatron, ZeRO, or Ray
.
Strong software engineering skills with experience building robust, maintainable, production-grade systems.
Experience optimizing GPU workloads, including memory efficiency, quantization, and mixed precision.
Ability to independently own end-to-end machine learning systems in fast-moving environments.
Strong problem-solving skills with a focus on rapid iteration and continuous improvement.
Preferred Qualifications
Experience with one or more of the following is preferred:
LLM inference frameworks such as
vLLM, TensorRT-LLM, or FasterTransformer
Open-source contributions to machine learning or systems libraries
Scientific computing, compiler technologies, or GPU kernel development
Reinforcement Learning from Human Feedback (RLHF) pipelines, including
PPO, DPO, or ORPO
Training or deploying multimodal or diffusion models
Large-scale data processing frameworks such as
Apache Arrow, Spark, or Ray
Location: Singapore
About the Company
Our client is a stealth AI startup backed by one of Southeast Asia's leading technology companies and is currently building its global founding team.
The company is developing an AI-native communication platform designed to simplify everyday tasks by integrating AI directly into conversations. Instead of switching between multiple applications, users can plan, organize, compare, research, and complete tasks within a single intelligent assistant.
Serving a market of billions of users still relying on traditional productivity tools, the platform focuses on delivering reliable AI workflows, persistent context, multi-step reasoning, and seamless task execution. The mission is to create an AI assistant that significantly improves productivity while making everyday work simpler and more intuitive.
About the Role
Our client is seeking an
iOS Software Engineer
to build and enhance its AI-native mobile experience. This role is responsible for developing production-grade iOS applications where AI interactions are central to the user experience, ensuring performance, reliability, and user trust across all mobile interactions.
Working closely with backend and machine learning teams, this position will focus on delivering scalable iOS applications that integrate advanced AI capabilities while maintaining a seamless and intuitive user experience.
Key Responsibilities
Build and maintain production iOS applications using
Swift
and
SwiftUI
.
Integrate AI-powered features through backend APIs.
Design user experiences for AI interactions, including loading states, streaming responses, retries, and fallback mechanisms.
Optimize application performance, memory usage, and battery efficiency.
Implement user feedback and analytics mechanisms to support AI evaluation and continuous product improvement.
Collaborate closely with backend and machine learning engineers on API design and system behavior.
Maintain high standards of application quality, stability, and reliability for App Store releases.
Requirements
Minimum
3 years of iOS development experience
using Swift.
Hands-on experience integrating AI-powered features into mobile applications.
Strong understanding of
async/await
, concurrency, and background task management.
Solid experience optimizing iOS application performance, memory usage, and responsiveness.
Experience developing, releasing, and maintaining production iOS applications.
Familiarity with designing applications that operate reliably under latency, partial failures, and non-deterministic AI behavior.
Exposure to
CoreML
or lightweight on-device machine learning is an advantage.
Familiarity with feature flags or remote configuration systems is preferred.
Strong understanding of user experience design for AI-powered applications, with an emphasis on usability and user trust.
Preferred Technical Skills
Experience with the following technologies is preferred:
Swift
SwiftUI
Swift Package Manager (SPM)
SQL and NoSQL databases
TensorFlow Lite (on-device inference)
Location: Singapore
About the Company
Our client is a stealth AI startup backed by one of Southeast Asia's leading technology companies and is currently building its global founding team.
The company is developing an AI-native communication platform designed to simplify everyday tasks by integrating AI directly into conversations. Instead of switching between multiple applications, users can plan, organize, compare, research, and complete tasks within a single intelligent assistant.
Serving a market of billions of users still relying on traditional productivity tools, the platform focuses on delivering reliable AI workflows, persistent context, multi-step reasoning, and seamless task execution. The mission is to create an AI assistant that significantly improves productivity while making everyday work simpler and more intuitive.
About the Role
Our client is looking for a
Full Stack Engineer – AI Systems
to build AI-native product experiences that transform advanced AI capabilities into intuitive, production-ready workflows. This role combines frontend, backend, and AI engineering to develop intelligent features that are reliable, scalable, and user-centric.
Working closely with product, backend, and machine learning teams, this position will focus on designing end-to-end AI workflows, integrating large language models (LLMs), and delivering seamless user experiences across web applications.
Key Responsibilities
Build end-to-end product features across frontend, backend, and AI integrations.
Design and develop AI agent workflows that support planning, tool usage, failure handling, and recovery across multiple steps.
Integrate LLMs, memory systems, and external tools into scalable, production-grade applications.
Design responsive AI interactions with streaming capabilities, partial results, and low-latency performance.
Improve system reliability, observability, and fallback mechanisms for AI-powered features.
Collaborate closely with product, backend, and machine learning teams to deliver features from concept to production.
Continuously iterate and improve product functionality based on user feedback, production insights, and real-world usage.
Requirements
Strong experience in full stack software engineering across frontend and backend development.
Solid understanding of system design, scalable architecture, and API development.
Experience building AI-powered applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), or similar technologies.
Ability to work effectively in fast-paced environments with evolving requirements.
Strong ownership mindset with experience delivering features from ideation through production deployment.
Excellent problem-solving skills and the ability to make pragmatic engineering decisions in ambiguous situations.
Preferred Technical Skills
Experience with some or all of the following technologies is preferred:
Next.js
Python
Node.js
PyTorch
OpenAI, Anthropic, or open-source Large Language Models (LLMs)
SQL and NoSQL databases
Kubernetes
Docker
seniorHong Kong, Hong Kong SAR; Singapore, Singapore
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