Location: San Francisco, CA | New York City, NY
About Anthropic
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
About the Role
We're looking for a Staff Software Engineer to set technical direction at the intersection of engineering and research on the Claude Code team. In this role, you'll partner directly with Anthropic's researchers and engineering leadership to shape how we measure, understand, and improve Claude's coding capabilities. You'll architect the systems, tooling, and evaluation infrastructure that determine how quickly our research can move—and you'll be accountable for the technical decisions that ripple across the team and beyond. This is a senior individual contributor role for someone who has already built and owned systems at significant scale, and who is ready to operate as a technical leader: driving architecture, mentoring engineers, and influencing the direction of Claude Code itself.
Responsibilities
Set technical direction for evaluation systems, research infrastructure, and internal tooling across the Claude Code team
Architect eval frameworks that measure model capabilities across diverse coding tasks and scale with our research roadmap
Lead the design of infrastructure that enables researchers to run experiments at scale, and make the foundational tradeoffs that shape how the team operates for years
Identify the highest-leverage engineering investments—often before anyone has asked for them—and drive them to completion
Serve as a senior technical bridge between product and research, using strong product intuition to influence which capabilities we prioritize and how we measure progress against them
Mentor and raise the bar for other engineers on the team; review designs, unblock peers, and model the engineering standards we want to scale
Partner with research leads to translate ambiguous research questions into durable engineering solutions
Own critical systems end-to-end, from architecture through production reliability, and take responsibility for their long-term health
You may be a good fit if you:
Have 10+ years of software engineering experience, with a track record of operating as a Staff or Principal engineer (or equivalent) at a high-caliber organization
Have architected and owned complex, high-stakes systems—pipelines, infrastructure, or platforms that orchestrate many components, handle significant state and logic, and serve multiple teams
Have a history of setting technical direction that others follow—through design docs, architectural decisions, or technical strategy that shaped how a team or org operates
Thrive in high-intensity environments with fast iteration cycles, and have the judgment to know when to move fast and when to invest in durability
Take full ownership of ambiguous, open-ended problems and drive them to completion with minimal direction
Are a power user of agentic coding tools with deep intuition about model capabilities and limitations
Can dive into unfamiliar technical domains—ML systems, research workflows, novel infrastructure—and get to the frontier quickly
Care deeply about correctness and reliability, and have raised engineering standards on teams you've been part of
Are energized by working at the boundary between engineering and AI research, and by the prospect of influencing both
Strong candidates may also have experience with:
Designing or scaling eval/evaluation frameworks for ML systems
Reinforcement learning infrastructure or training systems
Leading technical initiatives in high-performance, demanding environments—trading firms, quant funds, frontier research labs, or fast-moving startups where intensity and technical excellence are the norm
Research computing, scientific infrastructure, or developer platforms at scale
A strong quantitative foundation (math, physics, or related fields)
Expertise in Python and TypeScript
The annual compensation range for this role is listed below.
For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.
Annual Salary:
$405,000
—
$485,000 USD
Logistics
Minimum education:
Bachelor’s degree or an equivalent combination of education, training, and/or experience
Required field of study:
A field relevant to the role as demonstrated through coursework, training, or professional experience
Minimum years of experience:
Years of experience required will correlate with the internal job level requirements for the position
Location-based hybrid policy:
Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
Visa sponsorship:
We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
For roles performing work in California:
We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act.
We encourage you to apply even if you do not believe you meet every single qualification.
Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.
Your safety matters to us.
To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit
anthropic.com/careers
directly for confirmed position openings.
How we're different
We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.
The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.
Guidance on Candidates' AI Usage:
Learn about
our policy
for using AI in our application process.
Location: London, UK
About Anthropic
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
About the Role:
Anthropic's ML Performance and Scaling team trains our production pretrained models, work that directly shapes the company's future and our mission to build safe, beneficial AI systems. As a Research Engineer on this team, you'll ensure our frontier models train reliably, efficiently, and at scale. This is demanding, high-impact work that requires both deep technical expertise and a genuine passion for the craft of large-scale ML systems.
This role lives at the boundary between research and engineering. You'll work across our entire production training stack: performance optimization, hardware debugging, experimental design, and launch coordination. During launches, the team works in tight lockstep, responding to production issues that can't wait for tomorrow.
Responsibilities:
Own critical aspects of our production pretraining pipeline, including model operations, performance optimization, observability, and reliability
Debug and resolve complex issues across the full stack—from hardware errors and networking to training dynamics and evaluation infrastructure
Design and run experiments to improve training efficiency, reduce step time, increase uptime, and enhance model performance
Respond to on-call incidents during model launches, diagnosing problems quickly and coordinating solutions across teams
Build and maintain production logging, monitoring dashboards, and evaluation infrastructure
Add new capabilities to the training codebase, such as long context support or novel architectures
Collaborate closely with teammates across SF and London, as well as with Tokens, Architectures, and Systems teams
Contribute to the team's institutional knowledge by documenting systems, debugging approaches, and lessons learned
You May Be a Good Fit If You:
Have hands-on experience training large language models, or deep expertise with JAX, TPU, PyTorch, or large-scale distributed systems
Genuinely enjoy both research and engineering work—you'd describe your ideal split as roughly 50/50 rather than heavily weighted toward one or the other
Are excited about being on-call for production systems, working long days during launches, and solving hard problems under pressure
Thrive when working on whatever is most impactful, even if that changes day-to-day based on what the production model needs
Excel at debugging complex, ambiguous problems across multiple layers of the stack
Communicate clearly and collaborate effectively, especially when coordinating across time zones or during high-stress incidents
Are passionate about the work itself and want to refine your craft as a research engineer
Care about the societal impacts of AI and responsible scaling
Strong Candidates May Also Have:
Previous experience training LLM’s or working extensively with JAX/TPU, PyTorch, or other ML frameworks at scale
Contributed to open-source LLM frameworks (e.g., open_lm, llm-foundry, mesh-transformer-jax)
Published research on model training, scaling laws, or ML systems
Experience with production ML systems, observability tools, or evaluation infrastructure
Background as a systems engineer, quant, or in other roles requiring both technical depth and operational excellence
What Makes This Role Unique:
This is not a typical research engineering role. The work is highly operational—you'll be deeply involved in keeping our production models training smoothly, which means being responsive to incidents, flexible about priorities, and comfortable with uncertainty. During launches, the team often works extended hours and may need to respond to issues on evenings and weekends.
However, this operational intensity comes with extraordinary learning opportunities. You'll gain hands-on experience with some of the largest, most sophisticated training runs in the industry. You'll work alongside world-class researchers and engineers, and the institutional knowledge you build will compound in ways that can't be easily transferred. For people who thrive on this type of work, it's uniquely rewarding.
We're building a close-knit team of people who genuinely care about doing excellent work together. If you're someone who wants to be part of training the models that will define the future of AI—and you're excited about the full reality of what that entails—we'd love to hear from you.
Location:
This role requires working in-office 5 days per week in London.
Deadline to apply:
None. Applications will be reviewed on a rolling basis.
The annual compensation range for this role is listed below.
For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.
Annual Salary:
£260,000
—
£630,000 GBP
Logistics
Minimum education:
Bachelor’s degree or an equivalent combination of education, training, and/or experience
Required field of study:
A field relevant to the role as demonstrated through coursework, training, or professional experience
Minimum years of experience:
Years of experience required will correlate with the internal job level requirements for the position
Location-based hybrid policy:
Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
Visa sponsorship:
We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
For roles performing work in California:
We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act.
We encourage you to apply even if you do not believe you meet every single qualification.
Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.
Your safety matters to us.
To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit
anthropic.com/careers
directly for confirmed position openings.
How we're different
We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.
The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.
Guidance on Candidates' AI Usage:
Learn about
our policy
for using AI in our application process.
Location: San Francisco, CA
About Anthropic
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
About the Role:
Anthropic's ML Performance and Scaling team trains our production pretrained models, work that directly shapes the company's future and our mission to build safe, beneficial AI systems. As a Research Engineer on this team, you'll ensure our frontier models train reliably, efficiently, and at scale. This is demanding, high-impact work that requires both deep technical expertise and a genuine passion for the craft of large-scale ML systems.
This role lives at the boundary between research and engineering. You'll work across our entire production training stack: performance optimization, hardware debugging, experimental design, and launch coordination. During launches, the team works in tight lockstep, responding to production issues that can't wait for tomorrow.
Responsibilities:
Own critical aspects of our production pretraining pipeline, including model operations, performance optimization, observability, and reliability
Debug and resolve complex issues across the full stack—from hardware errors and networking to training dynamics and evaluation infrastructure
Design and run experiments to improve training efficiency, reduce step time, increase uptime, and enhance model performance
Respond to on-call incidents during model launches, diagnosing problems quickly and coordinating solutions across teams
Build and maintain production logging, monitoring dashboards, and evaluation infrastructure
Add new capabilities to the training codebase, such as long context support or novel architectures
Collaborate closely with teammates across SF and London, as well as with Tokens, Architectures, and Systems teams
Contribute to the team's institutional knowledge by documenting systems, debugging approaches, and lessons learned
You May Be a Good Fit If You:
Have hands-on experience training large language models, or deep expertise with JAX, TPU, PyTorch, or large-scale distributed systems
Genuinely enjoy both research and engineering work—you'd describe your ideal split as roughly 50/50 rather than heavily weighted toward one or the other
Are excited about being on-call for production systems, working long days during launches, and solving hard problems under pressure
Thrive when working on whatever is most impactful, even if that changes day-to-day based on what the production model needs
Excel at debugging complex, ambiguous problems across multiple layers of the stack
Communicate clearly and collaborate effectively, especially when coordinating across time zones or during high-stress incidents
Are passionate about the work itself and want to refine your craft as a research engineer
Care about the societal impacts of AI and responsible scaling
Strong Candidates May Also Have:
Previous experience training LLM’s or working extensively with JAX/TPU, PyTorch, or other ML frameworks at scale
Contributed to open-source LLM frameworks (e.g., open_lm, llm-foundry, mesh-transformer-jax)
Published research on model training, scaling laws, or ML systems
Experience with production ML systems, observability tools, or evaluation infrastructure
Background as a systems engineer, quant, or in other roles requiring both technical depth and operational excellence
What Makes This Role Unique:
This is not a typical research engineering role. The work is highly operational—you'll be deeply involved in keeping our production models training smoothly, which means being responsive to incidents, flexible about priorities, and comfortable with uncertainty. During launches, the team often works extended hours and may need to respond to issues on evenings and weekends.
However, this operational intensity comes with extraordinary learning opportunities. You'll gain hands-on experience with some of the largest, most sophisticated training runs in the industry. You'll work alongside world-class researchers and engineers, and the institutional knowledge you build will compound in ways that can't be easily transferred. For people who thrive on this type of work, it's uniquely rewarding.
We're building a close-knit team of people who genuinely care about doing excellent work together. If you're someone who wants to be part of training the models that will define the future of AI—and you're excited about the full reality of what that entails—we'd love to hear from you.
Location:
This role requires working in-office 5 days per week in San Francisco.
Deadline to apply:
None. Applications will be reviewed on a rolling basis.
The annual compensation range for this role is listed below.
For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.
Annual Salary:
$350,000
—
$850,000 USD
Logistics
Minimum education:
Bachelor’s degree or an equivalent combination of education, training, and/or experience
Required field of study:
A field relevant to the role as demonstrated through coursework, training, or professional experience
Minimum years of experience:
Years of experience required will correlate with the internal job level requirements for the position
Location-based hybrid policy:
Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
Visa sponsorship:
We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
For roles performing work in California:
We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act.
We encourage you to apply even if you do not believe you meet every single qualification.
Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.
Your safety matters to us.
To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit
anthropic.com/careers
directly for confirmed position openings.
How we're different
We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.
The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.
Guidance on Candidates' AI Usage:
Learn about
our policy
for using AI in our application process.
Location: Hong Kong, Hong Kong SAR
OKX will be prioritising applicants who have a current right to work in Hong Kong, and do not require OKX's sponsorship of a visa.
Who We Are
At OKX, we believe that the future will be reshaped by crypto, and ultimately contribute to every individual's freedom.
OKX is a leading crypto exchange, and the developer of OKX Wallet, giving millions access to crypto trading and decentralized crypto applications (dApps). OKX is also a trusted brand by hundreds of large institutions seeking access to crypto markets. We are safe and reliable, backed by our Proof of Reserves.
Across our multiple offices globally, we are united by our core principles:
We Before Me
,
Do the Right Thing
, and
Get Things Done
. These shared values drive our culture, shape our processes, and foster a friendly, rewarding, and diverse environment for every OK-er.
About The Opportunity
The trading bot domain has emerged as one of OKX's most critical and rapidly growing sectors over the past two years. It constitutes a significant share of our platform's daily active traders and trading volume. With this swift growth, escalating user demands, and a promising future for this business, we are committed to allocating more resources to this sector. Our aim is to build top-tier products and ultimately grow this line into a billion-dollar enterprise.
What You’ll Be Doing
Develop strategies to boost trading bot volume and user acquisition. Collaborate with cross-functional teams, including design, engineering, and data analysis.
Based on trading users' needs, design trading bots efficient for particular market situations.
Conduct user research and competitor assessments to identify potential opportunities for product innovation and optimization, enhancing user conversion and retention.
Advocate for robust engineering solutions and scalable product/system architecture designs, ensuring efficient new product development.
Manage projects with efficient scope, timeline, and stakeholder coordination, prioritizing quick iterations and impactful outcomes.
What We Look For In You
Bachelor's degree in a relevant field or equivalent practical experience, preferably in Financial Engineering, Mathematics or Engineering.
5+ years of product management experience, particularly within the crypto or internet industry.
Strong grasp of strategy design and backend logic.
Passion for problem-solving and delivering exceptional user experiences.
Self-motivated, independent, persistent, objective, with strong logical thinking, capable of project ownership.
Curious with a strong ability for self-learning, open to exploring innovative projects for driving product growth.
Excellent communication skills, both written and verbal, with the ability to influence and present ideas effectively.
Nice-To-Haves
Experience in Crypto/FX/Stocks trading, including quant trading, bot trading, or technical analysis.
Strong understanding of the industry and market dynamics.
Fluency in Mandarin will be a plus to work with cross tech teams based in Greater China Region.
Perks & Benefits
Competitive total compensation package
L&D programs and Education subsidy for employees' growth and development
Various team building programs and company events
Wellness and meal allowances
Comprehensive healthcare schemes for employees and dependants
More that we love to tell you along the process!
Please note that Hong Kong is a group-level service hub, and OKX does not carry on a business of operating a virtual asset trading platform in Hong Kong.
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: Singapore, Singapore
OKX will be prioritising applicants who have a current right to work in Singapore, and do not require OKX's sponsorship of a visa.
Who We Are
At OKX, we believe that the future will be reshaped by crypto, and ultimately contribute to every individual's freedom.
OKX is a leading crypto exchange, and the developer of OKX Wallet, giving millions access to crypto trading and decentralized crypto applications (dApps). OKX is also a trusted brand by hundreds of large institutions seeking access to crypto markets. We are safe and reliable, backed by our Proof of Reserves.
Across our multiple offices globally, we are united by our core principles:
We Before Me
,
Do the Right Thing
, and
Get Things Done
. These shared values drive our culture, shape our processes, and foster a friendly, rewarding, and diverse environment for every OK-er.
About The Opportunity
The trading bot domain has emerged as one of OKX's most critical and rapidly growing sectors over the past two years. It constitutes a significant share of our platform's daily active traders and trading volume. With this swift growth, escalating user demands, and a promising future for this business, we are committed to allocating more resources to this sector. Our aim is to build top-tier products and ultimately grow this line into a billion-dollar enterprise.
What You’ll Be Doing
Develop strategies to boost trading bot volume and user acquisition. Collaborate with cross-functional teams, including design, engineering, and data analysis.
Based on trading users' needs, design trading bots efficient for particular market situations.
Conduct user research and competitor assessments to identify potential opportunities for product innovation and optimization, enhancing user conversion and retention.
Advocate for robust engineering solutions and scalable product/system architecture designs, ensuring efficient new product development.
Manage projects with efficient scope, timeline, and stakeholder coordination, prioritizing quick iterations and impactful outcomes.
What We Look For In You
Bachelor's degree in a relevant field or equivalent practical experience, preferably in Financial Engineering, Mathematics or Engineering.
5+ years of product management experience, particularly within the crypto or internet industry.
Strong grasp of strategy design and backend logic.
Passion for problem-solving and delivering exceptional user experiences.
Self-motivated, independent, persistent, objective, with strong logical thinking, capable of project ownership.
Curious with a strong ability for self-learning, open to exploring innovative projects for driving product growth.
Excellent communication skills, both written and verbal, with the ability to influence and present ideas effectively.
Nice-To-Haves
Experience in Crypto/FX/Stocks trading, including quant trading, bot trading, or technical analysis.
Strong understanding of the industry and market dynamics.
Fluency in Mandarin will be a plus to work with cross tech teams based in Greater China Region.
Perks & Benefits
Competitive total compensation package
L&D programs and Education subsidy for employees' growth and development
Various team building programs and company events
Wellness and meal allowances
Comprehensive healthcare schemes for employees and dependants
More that we love to tell you along the process!
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: Abu Dhabi, United Arab Emirates; Luxembourg; Berlin, Germany; Bratislava, Slovakia; Bucuresti, Romania; Budapest, Hungary; Dresden, Germany; Dubai, United Arab Emirates; Düsseldorf, Germany; Erevan, Armenia; London, United Kingdom; Frankfurt, Germany; Hamburg, Germany; Hannover, Germany; Krakow, Poland; Kyiv, Ukraine; Leverkusen, Germany; Leipzig, Germany; Manchester, United Kingdom; Poland; Praha, Czechia; Skopje, North Macedonia; Sofia, Bulgaria; Stuttgart, Germany; Tallinn, Estonia; Tashkent, Uzbekistan; Tbilisi, Georgia; Warsaw, Poland
Workplace: remote
TechBiz Global is a leading recruitment and software development company. Our diverse, globally distributed team provides IT recruitment, outstaffing, outsourcing, software development, and different consulting services with a primary focus on making our partners achieve their business goals successfully.
With headquarters in Germany we have successful clients all over the world. We can understand your unique needs. Our team has hands-on experience with the challenges that come with rapid growth and the IT sector. That’s why all of our offerings are built with a tech mindset.
We are looking for a Head of HFT
for our client in a remote set up role.
Requirements
1.
3+ years
of hands-on experience in high-frequency or algorithmic trading.
2. Proven track record of working with
top-tier trading firms
, proprietary trading desks, or hedge funds.
3. Experience leading or contributing to successful HFT strategies and systems.
4. Deep understanding of
low-latency systems
, high-throughput data processing, and network optimization.
5. Fluent in
English
(written and spoken).
What You’ll Do
Lead the design, development, and optimization of high-frequency trading strategies.
Build and manage a high-performing HFT team, including quants and engineers.
Collaborate with leadership to align trading strategy with overall business goals.
Analyze and act on large data sets in real-time to identify profitable opportunities.
Maintain and continuously improve latency-sensitive infrastructure.
Ensure robust risk management protocols and compliance with relevant regulations.
Drive innovation and research in algorithmic trading within the Web3 and crypto space.
УдалённоheadAbu Dhabi, United Arab Emirates; Luxembourg; Berlin, Germany; Bratislava, Slovakia; Bucuresti, Romania; Budapest, Hungary; Dresden, Germany; Dubai, United Arab Emirates; Düsseldorf, Germany; Erevan, Armenia; London, United Kingdom; Frankfurt, Germany; Hamburg, Germany; Hannover, Germany; Krakow, Poland; Kyiv, Ukraine; Leverkusen, Germany; Leipzig, Germany; Manchester, United Kingdom; Poland; Praha, Czechia; Skopje, North Macedonia; Sofia, Bulgaria; Stuttgart, Germany; Tallinn, Estonia; Tashkent, Uzbekistan; Tbilisi, Georgia; Warsaw, Poland
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