Location: UK, London
Workplace: OnSite
Here at Humanoid, we believe in a future where robots amplify human potential. That’s why we’ve set out on a mission to build the world’s most capable, commercially-scalable, and safe humanoid robots. We’re bringing that mission to life with HMND‑01 - our rapidly developed humanoid platform being deployed in real industrial environments - and we’re growing the team to take it even further.
ABOUT THE ROLE
We're hiring a Staff Controls Software Engineer to join our Controls team based in London.
We are seeking an experienced Staff Controls Software Engineer to lead the development, integration, and maintenance of our production-grade control software for humanoid robotic systems.
This role sits at the intersection of controls and software engineering - focused on turning advanced control strategies into robust, maintainable, and validated production systems. You’ll be responsible for ensuring that the control stack powering our robots is deterministic, safe, tested, and deployable at scale.
You bring both deep robotics control experience (10 years in robotic system development) and strong software engineering discipline — designing architectures that perform reliably in real-time environments.
WHAT YOU’LL DO
- Design and maintain modular, real-time control architectures supporting locomotion, manipulation, and teleoperation.
- Implement high-performance control loops and middleware interfaces for deterministic, safe operation.
- Industrialize algorithms, ensuring production readiness, maintainability, and performance.
- Establish clear software boundaries and interfaces between motion planning, control, and hardware layers.
- Translate research prototypes into scalable, maintainable, and testable control software.
- Apply modern software development practices (CI/CD, code reviews, testing frameworks, documentation).
- Define reliability, latency, and safety metrics and enforce them throughout the control stack.
- Lead the integration of real-time control software on embedded or Linux-based systems, ensuring consistent behavior across hardware targets.
- Develop automated testing frameworks (simulation, hardware-in-the-loop, regression, and performance testing).
- Drive release and version management of the control stack, ensuring stability across branches and deployments.
- Conduct profiling, benchmarking, and performance validation on robotic hardware.
- Define release protocols to ensure reproducibility and verifiable system behavior.
- Implement software-based fail-safes, watchdogs, and redundancy mechanisms for safety-critical control paths.
- Work closely with hardware and safety teams to ensure fault detection, graceful degradation, and safe state transitions.
- Lead by example through hands-on coding, code reviews, and system-level debugging.
- Mentor engineers on control software best practices, testing methodologies, and performance optimization.
- Contribute to the long-term control software roadmap, guiding architecture evolution and quality standards.
WHAT WE'RE LOOKING FOR
- B.S., M.S., or Ph.D. in Robotics, Control, Computer Engineering, or a related field.
- 10+ years of experience developing robotics control software for real-time systems.
- Proven expertise in C++ (modern standards) and Python for software implementation, testing, and automation.
- Strong background in control theory, robot kinematics & dynamics, and real-time control systems.
- Experience in deploying and validating control software both in simulation and on physical robotic platforms.
- Solid understanding of software architecture, version control (Git), CI/CD pipelines, and automated testing.
- Excellent debugging, profiling, and system performance optimization skills.
- Track record of shipping production-quality robotics software, not research prototypes.
- Proven experience managing software lifecycle, including release management and cross-team integration.
Nice to have:
- Experience with ROS2, real-time Linux, or RTOS environments.
- Familiarity with relevant tools and libraries like Eigen, Pinocchio, Placo, PyTorch, MuJoCo, etc.
- Familiarity with safety-critical systems, redundancy, and failover mechanisms.
- Background in whole-body control, actuator coordination, or real-time trajectory execution.
- Experience in Joint/Cartesian Impedance and force control
- Strong communication and leadership skills, with the ability to influence architecture decisions and engineering culture.
- Experience in learning-based control methods (e.g. RL, imitation learning)
WHAT WE OFFER
- Meaningful time off to rest and recharge: 23 days of annual leave (accrued), 15 days of paid sick leave, and paid company holidays.
- Fully funded private healthcare for UK employees, with broad provider access, virtual and in‑person care, and strong mental health and serious illness support.
- Equity included–we believe builders should share in what they build.
- Pension scheme with a total 8% contribution (5% employee, 3% employer) on full earnings.
- Free daily breakfast, catered lunch, and snacks in‑office.
- Collaboration with top‑tier engineers, researchers, and product experts in AI and robotics.
- Freedom to influence the product and own key initiatives.
Задачи:
— Разработка инструментов автоматизации процессов сборки, тестирования, внедрения
— Построение пайплайнов разной сложности
— Разработка сервисов интеграции с помощью брокеров сообщений и HTTP запросов
— Разработка web-сервисов для пользователей
— Поддержка созданных и текущих инструментов и сервисов
Требования:
— Опыт от 3 лет в DevOps / Platform / Tools development
— Опыт работы с Kubernetes (деплой, Helm, базовый troubleshooting)
— Опыт разработки на Python (коммерческий, не только скрипты)
— Опыт написания Jenkins-пайплайнов (Groovy)
— Уверенное знание Linux / bash
— Опыт с Docker и Git
— Понимание работы Nginx
— Понимание брокеров сообщений (Kafka будет плюсом)
— Готовность участвовать в разработке веб-сервисов (REST API)
— Готовность поддерживать созданные инструменты и сервисы
Будет плюсом:
— Опыт с OpenShift
— Опыт с Go или Java
— Опыт с ArgoCD / GitOps
— Опыт с Istio
— Опыт работы с Jenkins
Условия:
— Полностью удалённый формат работы (только РФ)
— Работа в крупном и стабильном финансовом холдинге
— Возможность участвовать в развитии и поддержке сложных инфраструктурных решений
Location: UK, London
Workplace: OnSite
Here at Humanoid, we believe in a future where robots amplify human potential. That’s why we’ve set out on a mission to build the world’s most capable, commercially-scalable, and safe humanoid robots. We’re bringing that mission to life with HMND‑01 - our rapidly developed humanoid platform being deployed in real industrial environments - and we’re growing the team to take it even further.
ABOUT THE ROLE
We are seeking a Teleoperation Control Engineer to help build the systems that let human operators safely, confidently, and precisely control advanced robots. This role sits at the intersection of robot control, real-time software, operator UX, hardware integration, and human-in-the-loop workflows.
You will develop the core teleoperation capability that enables operators to guide, recover, teach, and improve robot behavior in real time. That includes intuitive control mappings, reliable command pipelines, clear operator feedback, high-quality data capture, and safeguards for safe use around real hardware.
We are open to strong candidates from junior through staff level. The key traits are hands-on robotics ability, strong engineering judgment, care for software quality, and a product-minded instinct for making complex robot systems intuitive for operators.
WHAT YOU’LL DO
- Develop teleoperation capabilities for controlling robots across manipulation, mobility, and loco-manipulation tasks.
- Design intuitive operator experiences, including input mappings, visualizations, feedback loops, recovery flows, and workflows that reduce cognitive load and improve operator confidence.
- Integrate input devices such as VR controllers, gloves, haptic devices, motion capture systems, and custom operator stations into the robot software stack.
- Translate noisy, high-frequency human input into smooth, stable, physically feasible robot commands with predictable behavior.
- Build robust teleoperation infrastructure for real-time data streaming, calibration, replay, debugging, logging, operator training, and high-quality demonstration capture.
- Develop shared-autonomy and assistive-control features that blend human intent with robot capability to improve precision, safety, and ease of use.
- Create safe operating boundaries, limiters, alerts, emergency/recovery flows, and clear state feedback so robot operators can use teleoperation safely.
- Define and improve quality metrics for teleoperation systems, including latency, reliability, observability, operator success rate, demonstration quality, and failure modes.
- Stress-test teleoperation systems on real hardware and in simulation, then drive reliability improvements based on operator feedback and observed failures.
- Work closely with controls, manipulation, hardware, and operations teams to ensure teleoperation requirements shape robot design and field workflows.
WHAT WE'RE LOOKING FOR
- Strong robotics fundamentals, including kinematics, coordinate frames, control interfaces, state estimation basics, and real-time system behavior.
- Experience building a subset of the following: teleoperation systems, operator UIs, shared-autonomy tools, human-robot interfaces, or robot learning data-collection pipelines.
- Ability to write reliable software in C++ and/or Python, with experience in ROS/ROS2, real-time data streaming, or robotic middleware.
- Good intuition for human-in-the-loop systems: how operators perceive robot state, issue commands, recover from errors, and build trust.
- A quality mindset: clean abstractions, testing, logging, observability, performance tuning, and tools that remain usable under pressure.
- Strong debugging skills across the stack, from operator input devices to robot motion, sensors, networking, and hardware behavior.
- Comfort iterating quickly on real robots, learning from operator feedback, and turning prototypes into robust capabilities.
- Clear communication and collaboration with cross-functional teams.
Nice to have:
- Hands-on experience building or debugging software for real robotic hardware, ideally in manipulation, mobile manipulation, humanoids, or dexterous systems.
- Experience designing safe workflows for hardware-facing systems where latency, instability, poor feedback, or misuse can create operational risk.
- Experience collecting high-quality demonstrations for imitation learning, behavior cloning, or other robot learning workflows.
- Exposure to intent inference, haptics, force feedback, motion capture, VR/AR interfaces, or custom control devices.
- A product-minded approach to robotics: caring not only that the robot moves, but that control is intuitive, safe, reliable, and pleasant for operators to use.
WHAT WE OFFER
- Competitive equity: stock options with meaningful upside as we scale.
- 30+ days time off, including 23 days annual leave, all UK bank holidays, and additional company closure days (including Christmas–New Year shutdown).
- Private healthcare, including virtual and in-person care.
- Pension scheme with 8% total contribution (5% employee, 3% employer) on full earnings.
- Free daily breakfast, catered lunch, and snacks in-office.
- Work at the frontier - collaborate daily with world-class engineers, researchers, and product experts building the next generation of AI and humanoid robotics.
- Real ownership - direct access to founding leadership, meaningful input on product direction, and the ability to drive key initiatives from day one.
Location: US, Boston, MA
Workplace: OnSite
Here at Humanoid, we believe in a future where robots amplify human potential. That’s why we’ve set out on a mission to build the world’s most capable, commercially-scalable, and safe humanoid robots. We’re bringing that mission to life with HMND‑01 - our rapidly developed humanoid platform being deployed in real industrial environments - and we’re growing the team to take it even further.
ABOUT THE ROLE
We design robots in simulation before building them in hardware.
As a Robotics Simulation & RL Engineer, you will help design and validate future generations of our robotic platforms - including bipedal and wheeled systems - using physics simulation and reinforcement learning.
You will develop tools to determine whether a robot design can perform real-world tasks before committing to hardware. Your work will directly inform robot architecture, actuator selection, sensor placement, and control strategies.
A key responsibility of this role is owning and validating the canonical robot models (URDF and simulation assets) used across simulation and control stacks.
WHAT YOU’LL DO
- Design and evaluate new robot platforms using physics simulation
- Analyze robot capabilities including workspace, manipulability, dynamic balance, and torque limits
- Use reinforcement learning to stress-test robot designs and explore capability limits
- Own and maintain URDF models of current and future robot platforms
- Maintain the CAD → URDF → simulation pipeline
- Develop tools and benchmarks to evaluate locomotion, manipulation, and platform robustness
- Provide quantitative feedback to hardware teams on actuator sizing, joint placement, mass distribution, and sensor layout
- Collaborate with mechanical, control, and perception teams to guide platform design decisions
WHAT WE'RE LOOKING FOR
- M.Sc http://M.Sc. or Ph.D. in Robotics, Mechanical Engineering, Control, or a related field
- Strong foundation in robot kinematics and dynamics
- Experience with robot simulation environments (MuJoCo, Isaac Sim, Gazebo, or similar)
- Experience with reinforcement learning in robotics or physics-based simulation
- Experience working with URDF or similar robot description formats
- Strong programming skills in Python and/or C++
- Experience training RL locomotion or manipulation policies
Nice to have:
- Experience with legged, humanoid, or wheeled robots;
- Experience with whole-body control or torque-controlled robots;
- Experience with simulation-driven hardware design;
- Experience building large-scale RL training pipelines.
WHAT WE OFFER
- Comprehensive health coverage for US‑based employees, including fully paid medical, dental, and vision insurance, with virtual care and employee assistance resources.
- Meaningful time off to rest and recharge: 23 days of PTO (accrued), separate sick leave, and paid company holidays.
- 401(k) retirement plan with a 4% employer match.
- Equity included–we believe builders should share in what they build.
- Free daily catered lunch, snacks, and drinks in‑office.
- Collaboration with top‑tier engineers, researchers, and product experts in AI and robotics.
- Freedom to influence the product and own key initiatives.
For this role in Massachusetts, the target base salary range is $200K–$300K USD per year; your placement in that range depends on how your experience maps to our internal leveling.
Location: UK, London
Workplace: OnSite
Here at Humanoid, we believe in a future where robots amplify human potential. That’s why we’ve set out on a mission to build the world’s most capable, commercially-scalable, and safe humanoid robots. We’re bringing that mission to life with HMND‑01 - our rapidly developed humanoid platform being deployed in real industrial environments - and we’re growing the team to take it even further.
ABOUT THE ROLE
We're hiring a Senior Dev/MLOps Engineer to join our Data & Compute Platform team based in London.
WHAT YOU’LL DO
- Own and manage the full lifecycle of both ML models and core infrastructure - from development and deployment to monitoring and continuous improvement.
- Build and maintain robust CI/CD pipelines for both software and ML workflows.
- Ensure reliability, scalability, observability, and security of production systems and ML infrastructure.
- Automate deployment, orchestration, and environment management using modern DevOps tooling.
- Collaborate closely with software engineers, data scientists, and product teams to bring ML-powered features to production.
- Proactively detect, troubleshoot, and resolve infrastructure and model performance issues.
- Stay up to date with industry best practices in DevOps, MLOps, and infrastructure engineering.
- Document infrastructure, workflows, and operational procedures clearly and thoroughly.
WHAT WE'RE LOOKING FOR
- Proven experience in a senior-level DevOps, MLOps, or related infrastructure-focused engineering role.
- Strong proficiency in Python and familiarity with ML frameworks such as TensorFlow or PyTorch.
- Deep experience with cloud platforms (AWS, GCP, or Azure) and container orchestration tools (Docker, Kubernetes).
- Solid understanding of CI/CD systems (e.g., GitHub Actions, GitLab CI, ArgoCD) and infrastructure-as-code tools (e.g., Terraform, Helm).
- Familiarity with data engineering concepts such as ETL pipelines, data lakes, and large-scale batch/stream processing.
- Ability to design scalable, secure, and observable systems in fast-moving environments.
- Strong debugging and problem-solving skills across distributed systems.
- Excellent collaboration and communication skills, with experience working in cross-functional teams.
- Understanding of security and compliance best practices for both software and ML systems.
WHAT WE OFFER
- Meaningful time off to rest and recharge: 23 days of annual leave (accrued), 15 days of paid sick leave, and paid company holidays.
- Fully funded private healthcare for UK employees, with broad provider access, virtual and in‑person care, and strong mental health and serious illness support.
- Equity included–we believe builders should share in what they build.
- Pension scheme with a total 8% contribution (5% employee, 3% employer) on full earnings.
- Free daily breakfast, catered lunch, and snacks in‑office.
- Collaboration with top‑tier engineers, researchers, and product experts in AI and robotics.
- Freedom to influence the product and own key initiatives.
Location: Hong Kong, Hong Kong SAR
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
You will be responsible for the core architecture design and technical delivery of an enterprise-grade AI Native engineering platform, driving the deep integration of large language models, AI Agents, knowledge capabilities, and the software development lifecycle. The platform will support intelligent capabilities across requirement analysis, solution generation, coding collaboration, test automation, and environment orchestration.This role focuses on engineering-grade AI implementation in complex R&D scenarios. You are expected to turn model capabilities into reusable, scalable, and governable platform capabilities, and continuously drive the evolution of the engineering platform toward an AI Native architecture.
What You’ll Be Doing
Lead the
overall architecture design and core capability development
of the AI Agent platform, including task orchestration, tool invocation, context management, memory mechanisms, and multi-agent collaboration.
Drive the
implementation of AI Native capabilities in engineering workflows
, including AI coding, technical solution generation, test case generation, test report generation, and automated environment deployment.
Build the
knowledge augmentation layer
for the platform, including the design, integration, and application of RAG, GraphRAG, and knowledge graph capabilities.
Establish the
runtime and governance framework
for AI Agents, including execution isolation, permission control, auditability, evaluation, stability, and cost governance.
Collaborate with product, engineering, QA, and operations teams to standardize, productionize, and scale platform capabilities, continuously improving engineering efficiency and delivery quality.
What We Look For In You
Bachelor’s degree or above
, preferably in Computer Science, Software Engineering, Artificial Intelligence, or related fields.
8+ years
of experience in backend engineering, platform engineering, or infrastructure engineering, with strong system design and delivery capabilities.
Proficient in
Java / Python
, with solid coding skills, architectural thinking, and experience building complex systems.
Strong understanding of
LLM
and AI Agent architectures
, including task decomposition, tool use, context management, memory, execution loops, and exception handling.
Hands-on experience with
LangChain and LangGraph
, and strong familiarity with mainstream AI coding tools or frameworks such as
Claude Code
, Codex,
Cursor
, and Copilot
.
Experience in designing or developing
RAG / GraphRAG / knowledge graph
solutions for enterprise knowledge augmentation and engineering use cases.
Good understanding of
DevOps
,
CI/CD
,
Kubernetes
, and cloud-native technologies
, with strong cross-functional collaboration and execution skills.
Nice to Haves
Experience contributing to
open-source projects
related to AI Agents, AI Coding, RAG, or knowledge graphs.
Experience building
enterprise engineering platforms,
DevOps
platforms, or AI platforms
.
Familiarity with open-source Agent projects such as
openclaw, openhands/openharness, or Hermes
.
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!
OKX Statement:
OKX is committed to equal employment opportunities regardless of race, color, genetic information, creed, religion, sex, sexual orientation, gender identity, lawful alien status, national origin, age, marital status, and non-job related physical or mental disability, or protected veteran status. Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
Discl
aimer:
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: Yerevan; Poland; Ukraine; Serbia; Valencia
Workplace: remote
About Provectus
Provectus is an AWS Premier Partner and an Anthropic Strategic Partner, working at the frontier of applied AI. We help enterprises turn Claude, agentic systems, and their own data into measurable business outcomes — through bespoke applications, managed services, and advisory engagements. With offices in North America, LATAM, and EMEA, we partner with clients worldwide.
Our work centers on two verticals — Financial Services & Insurance and Healthcare & Life Sciences — where we deploy five pre-built AI Blueprints: Submission Flow, Portfolio Lens, Asset Flow, Revenue Flow, and Evidence Lens. Each Blueprint rebuilds a critical business process front to back, shipped from working code and tuned to a client's specific book, regulators, and operating posture.
Our team holds 100+ AWS certifications, is Claude Code certified, and co-delivers Anthropic's Agentic SDLC program, Cowork Activation, and AI Blueprint engagements.
Where this role sits
You will work in a small, senior pod alongside an FDX; our delivery arc is Sprint → Enable → Realize:
Forward Deployed Executive (FDX)
owns the commercial relationship and the business outcome. Works alongside the client's leadership or C-suite level to move the client's KPIs — revenue growth, cost reduction, risk reduction.
Forward Deployed Engineer (FDE)
embeds with a client to change how that client operates. You own the method; nobody hands you a ticket. You map the client workflow as it actually happens, identify the business problem underneath it, build a working AI solution, present to the client in the language of outcomes, and transfer it. Provectus maintains industry Blueprints — working systems that have already shipped for a client in the same industry — so you begin from running code and tuning it to this client's specific book, regulators, and operating posture. You will be measured on whether the Business Unit's number moved, not on hours or scope delivered.
Requirements:
Mindset
Proactive and self-directed; identify problems before they're handed to you
Comfort with ambiguity and ownership. Engagements start underspecified by design. Closing that gap is the job
B2+ English, comfortable collaborating across distributed, multicultural teams
Client Engagement
You are willing to spend time understanding and doing someone else’s job on the client's side before you write a line of code
Credible with senior stakeholders — you can hold a redesign conversation with a BU head and a scoping conversation with a CTO, presenting outcomes to them
You can produce a scoped, phased delivery plan with clear deliverables, dependencies, and risks — and estimate what it will cost to build and to run
Technical depth
7+ years building and running production systems.
Solid AI/ML foundations. You understand what the models do well enough to reason about failure modes
Designed and shipped to production LLM applications and agentic workflows — not demos, not POCs, not notebooks
Agentic orchestration: multi-step workflows, graph-based orchestration, tool use, state management, and recovery from partial failure
Experience with LLM APIs (Anthropic, AWS Bedrock, or OpenAI) and agent frameworks.
Experience building and optimizing RAG systems in production
Strong engineering fundamentals — dropped into an unfamiliar codebase or language, you’re productive. Python and/or TypeScript proficiency; depth matters more than stack.
Experience in making and defending architectural trade-off decisions
Hands-on AWS production depth: Bedrock, Bedrock AgentCore, Lambda, ECS, S3, SQS, ECR, or similar. GCP or Azure is a plus
Cloud-native delivery: containers, ECS or Kubernetes, IaC, and CI/CD applied to AI pipelines
You evaluate. You have built or owned an eval suite for a non-deterministic system, and you can explain what you measured, how you produced ground truth, and what gated a release
Model and agent monitoring, drift detection
Cost and latency discipline: model tiering, caching, and the ability to say what a workload costs to run before it runs
Hands-on production experience with the Claude ecosystem — Claude Code, CLAUDE.md, hooks, skills files. Spec-driven development — writing the intent, constraints, and acceptance criteria before you let an agent build — is a strong plus
MCP: you can say why an agent would prefer it to a REST integration. Having authored a server is a plus
What you’ll do:
Take the seat
Sit with the client and the Forward Deployed Executive at the start of an engagement. Learn the function from inside, not from a requirements doc, and redesign the function from first principles.
Reach working fluency in a new domain — insurance underwriting, healthcare revenue cycle, asset flow.
Build
Design and ship production GenAI systems into the customer’s environment (cloud-native data, LLM-based, and agentic AI solutions). Implement and optimize RAG systems for production use cases
Build the evaluation harness before you build the feature. Define what working means, instrument it, and let the evals drive the design.
Write production code across the stack — AI, backend services, data pipelines. We choose tools to fit the customer.
Take systems to production on AWS (GCP or Azure where the customer requires it): containerised, CI/CD, automated testing, monitoring, and maintainable after we leave. Hand the system over to the client.
Start from the blueprint, and feed the blueprint. What you learn in the field becomes the baseline the next engagement starts from.
Lead architecture reviews, produce technical design documents, and contribute to standards. Mentor engineers and share knowledge across the team.
Own the outcome.
Work in a pair with a FDX who carries the Business Unit’s KPIs. Your work is measured against the same number.
Own the technical direction of technical proposals and scoping. Drive adoption. Change management is part of the engineering job here.
Be credible with the customer’s engineers and their executives.
Shape what we commit to before we commit to it.
Nice to Have:
Prior experience as a founder, CTO, or engineering leader who has chosen to return to individual contribution
Experience in one of the industries: financial services, insurance, healthcare
Consulting, professional services, or other embedded customer-facing delivery
A2A: you can explain agent-to-agent interoperability
AWS and Claude Code Certifications
CI/CD pipeline experience (GitHub Actions, GitLab CI)
Experience in an additional language (Go, TypeScript, or Rust)
Experience with Apache Spark, Apache Airflow, Kafkа
What We Offer:
The chance to shape how leading enterprises across LATAM, Europe, and North America adopt AI, from strategy through first deployment
A forward-deployed model working in small, senior teams alongside Principal Architects and Forward Deployed Engineers
A growing AI delivery practice where you help build the tooling and frameworks, not just use them
Remote-friendly culture
Internal training programs with full support for Claude, AWS, and other professional certifications, conference attendance
Career growth; we actively develop our engineers
Access to the latest AI tools and premium subscriptions
Long-term B2B collaboration
Private medical insurance or a budget for your medical needs
Paid sick leave, vacation, and public holidays
Equipment and all the tech you need for comfortable, productive work
How we hire:
Intro conversation. The role, your background and aspirations, tech questions.
Technical interview with live engineering sessions. Real problems, your own editor, you may use an LLM assistant
HR Interview. Soft skills and expectations
HM interview. Tech questions; a live engineering session is also possible
Location: Home based - EMEA
Canonical is a leading provider of open source software and operating systems to the global enterprise and technology markets. Our platform, Ubuntu, is very widely used in breakthrough enterprise initiatives such as public cloud, data science, AI, engineering innovation, and IoT. Our customers include the world's leading public cloud and silicon providers, and industry leaders in many sectors. The company is a pioneer of global distributed collaboration, with 1200+ colleagues in 75+ countries and very few office-based roles. Teams meet two to four times yearly in person, in interesting locations around the world, to align on strategy and execution.
The company is founder-led, profitable, and growing.
We are hiring multiple positions from early-career engineers to experienced architects focused on the different dimensions of dependable software: cybersecurity, quality, and safety.
What does it take to bring the world’s open source software into mission-critical systems? At Canonical, we are driving the engineering discipline needed to build secure, reliable, and high-quality products that our automotive and industrial partners can depend on. Ubuntu is already the world’s most widely used Linux distribution in general; we want to make it the world’s best choice for the automotive and industrial sectors too.
We operate at the boundary between upstream open source innovation and the industrial regulatory realities. Our engineers define the concepts, architectures, processes, verification strategies, and certification artifacts to transform a general-purpose platform into a dependable, certifiable foundation for automotive and industrial compute. This is systems-level engineering at scale, requiring precision, rigor, and a deep understanding of how complex software behaves in constrained, regulated environments.
We are looking for engineers and architects who combine an open source hacker and builder mindset with respect for rigorous, standards-driven engineering. You will work across Canonical engineering teams and with leading industrial partners, helping to build this capability from the ground up and shaping how open source enters the most demanding technical domains.
Location
: This is a remote role based in the EMEA region.
The role entails
Translate automotive and industrial cybersecurity, quality and safety standards into actionable engineering requirements and perform gap analyses against current capabilities.
Drive the creation of structured engineering artifacts, including requirements, traceability models, risk analysis, test strategies, and certification documentation.
Collaborate with Canonical engineering teams to align development practices with industrial compliance needs.
Design, implement, and execute verification and validation activities required to qualify Ubuntu and other components for regulated environments.
Develop and improve automation and tooling to scale traceability, testing, compliance evidence generation, and reporting.
Engage with industrial partners to understand their expectations, align external expectations and internal capabilities, and support audits and technical reviews.
Contribute to the continuous improvement of Canonical’s internal processes and standards capability as the team scales.
What we are looking for in you
Strong software engineering foundation with experience in developing complex systems on Linux.
Professional experience with C, C++, and Python in production environments.
Demonstrated experience working within automotive, industrial, or other regulated environments governed by safety, cybersecurity, or quality standards (such as ISO 26262, ISO/SAE 21434, IEC 61508, IEC 62443, SOTIF, or (A)SPICE), and applying them in practice.
Experience in system or software architecture, implementation, or verification and validation of complex embedded systems.
Strong written and verbal communication skills, with the ability to produce precise technical documentation.
Ability to collaborate effectively in a distributed team and engage with industrial partners.
Additional experience that is valuable
Contributions to open source projects, particularly in the area of Software Defined Vehicles.
Knowledge of Debian packaging.
Experience with Rust or safety-critical software development.
What we offer colleagues
We consider geographical location, experience, and performance in shaping compensation worldwide. We revisit compensation annually (and more often for graduates and associates) to ensure we recognize outstanding performance. In addition to base pay, we offer a performance-driven annual bonus. We provide all team members with additional benefits which reflect our values and ideals. We balance our programs to meet local needs and ensure fairness globally.
Distributed work environment with twice-yearly team sprints in person
Personal learning and development budget of USD 2,000 per year
Annual compensation review
Recognition rewards
Annual holiday leave
Maternity and paternity leave
Team Member Assistance Program & Wellness Platform
Opportunity to travel to new locations to meet colleagues
Priority Pass and travel upgrades for long-haul company events
About Canonical
Canonical is a pioneering tech firm at the forefront of the global move to open source. As the company that publishes Ubuntu, one of the most important open-source projects and the platform for AI, IoT, and the cloud, we are changing the world of software. We recruit on a global basis and set a very high standard for people joining the company. We expect excellence - in order to succeed, we need to be the best at what we do. Most colleagues at Canonical have worked from home since its inception in 2004. Working here is a step into the future and will challenge you to think differently, work smarter, learn new skills, and raise your game.
Canonical is an equal-opportunity employer
We are proud to foster a workplace free from discrimination. Diversity of experience, perspectives, and background create a better work environment and better products.
Whatever your identity we will give your application fair consideration
.
Location: Raleigh, NC
Workplace: Remote
ABOUT US
At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale.
With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world.
Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater.
ABOUT THE TEAM
The Deployed Engineering team works directly with companies building and running AI agents in production, helping turn ideas and prototypes into systems teams can rely on.
This is a hands-on, highly technical team that partners closely with customer engineers across the full lifecycle, from pre-sales evaluations to post-deployment advisory work. The focus is on achieving the technical win, co-designing agent architectures, and helping customers operate agents reliably at scale using the LangChain suite.
Deployed Engineers sit at the intersection of engineering, product, and go-to-market, shaping how LangChain is adopted in the field and feeding real-world insights back into the platform.
ABOUT THE ROLE
The Deployed Engineer…You’ll work on some of the hardest problems in applied AI — not demos, not research, but systems that real teams depend on in production. The feedback loop is fast, the impact is visible, and the work you do directly shapes how AI agents are built in the real world.
WHAT YOU’LL DO
- Co-architect and co-build production AI agents with customer engineering teams
- Own the technical win in pre-sales by designing POCs, answering deep technical questions, and guiding evaluations
- Help customers deploy and operate agent-based applications such as conversational agents, research agents, and multi-step workflows
- Advise customers post-sale on architecture, best practices, and roadmap-level decisions
- Run technical demos, trainings, and workshops for developer audiences
- Surface field feedback and contribute reusable patterns, cookbooks, and example code that scale across customers
- Occasionally contribute code upstream when it meaningfully improves customer outcomes
WHAT YOU’LL BRING
- 3+ years in a relevant technical role (software engineering, customer engineering, solutions engineering, founding/product engineering), ideally in a startup or scale-up
- Strong Python, JavaScript and systems fundamentals
- Have designed agent-based or LLM-powered applications beyond simple API calls, including multi-step workflows, orchestration, and failure handling
- Are comfortable working directly with customers during POCs, architecture reviews, and technical evaluations
- Can explain technical tradeoffs clearly and build trust with developer audiences
- Take responsibility for outcomes, not just recommendations
- Have a bias toward action and enjoy figuring things out as you go
- Are excited about operating AI agents in production, not just building demos
NICE TO HAVE’S:
- You’ve deployed AI agents in production, especially using LangChain, LangGraph, or similar frameworks
- Worked with LLM evaluation, observability, or guardrails
- Have experience with cloud environments (AWS, GCP, Azure), containers, and basic Kubernetes concepts
- Have shipped and operated production software and are comfortable owning systems under real-world constraints
COMPENSATION
Annual OTE range: $150,000–$250,000 USD
Compensation Philosophy:
We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks.
We are hiring for this role across a range of scope, and the compensation band reflects that. Your offer depends on what we learn about your impact, craft, leadership, and communication during the interview process. We will tell you early where you’re tracking and talk comp with you before offer stage. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations.
BENEFITS
Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.
Location: Charlotte, NC
Workplace: Remote
ABOUT US
At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale.
With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world.
Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater.
ABOUT THE TEAM
The Deployed Engineering team works directly with companies building and running AI agents in production, helping turn ideas and prototypes into systems teams can rely on.
This is a hands-on, highly technical team that partners closely with customer engineers across the full lifecycle, from pre-sales evaluations to post-deployment advisory work. The focus is on achieving the technical win, co-designing agent architectures, and helping customers operate agents reliably at scale using the LangChain suite.
Deployed Engineers sit at the intersection of engineering, product, and go-to-market, shaping how LangChain is adopted in the field and feeding real-world insights back into the platform.
ABOUT THE ROLE
The Deployed Engineer…You’ll work on some of the hardest problems in applied AI — not demos, not research, but systems that real teams depend on in production. The feedback loop is fast, the impact is visible, and the work you do directly shapes how AI agents are built in the real world.
WHAT YOU’LL DO
- Co-architect and co-build production AI agents with customer engineering teams
- Own the technical win in pre-sales by designing POCs, answering deep technical questions, and guiding evaluations
- Help customers deploy and operate agent-based applications such as conversational agents, research agents, and multi-step workflows
- Advise customers post-sale on architecture, best practices, and roadmap-level decisions
- Run technical demos, trainings, and workshops for developer audiences
- Surface field feedback and contribute reusable patterns, cookbooks, and example code that scale across customers
- Occasionally contribute code upstream when it meaningfully improves customer outcomes
WHAT YOU’LL BRING
- 3+ years in a relevant technical role (software engineering, customer engineering, solutions engineering, founding/product engineering), ideally in a startup or scale-up
- Strong Python, JavaScript and systems fundamentals
- Have designed agent-based or LLM-powered applications beyond simple API calls, including multi-step workflows, orchestration, and failure handling
- Are comfortable working directly with customers during POCs, architecture reviews, and technical evaluations
- Can explain technical tradeoffs clearly and build trust with developer audiences
- Take responsibility for outcomes, not just recommendations
- Have a bias toward action and enjoy figuring things out as you go
- Are excited about operating AI agents in production, not just building demos
NICE TO HAVE’S:
- You’ve deployed AI agents in production, especially using LangChain, LangGraph, or similar frameworks
- Worked with LLM evaluation, observability, or guardrails
- Have experience with cloud environments (AWS, GCP, Azure), containers, and basic Kubernetes concepts
- Have shipped and operated production software and are comfortable owning systems under real-world constraints
COMPENSATION
Annual OTE range: $150,000–$250,000 USD
Compensation Philosophy:
We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks.
We are hiring for this role across a range of scope, and the compensation band reflects that. Your offer depends on what we learn about your impact, craft, leadership, and communication during the interview process. We will tell you early where you’re tracking and talk comp with you before offer stage. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations.
BENEFITS
Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.
Location: United States; Canada (BC & ON only)
Workplace: Remote
Webflow is the agentic web marketing platform for modern marketing teams, helping organizations build, manage, and optimize high-performing web experiences that drive predictable growth and strengthen brand trust. Building at Webflow will need grit, because we move fast, without ever sacrificing craft or quality.
We’re looking for a Senior Staff Machine Learning Scientist to help us solve challenging problems to address emerging customer needs and behaviors. The ideal candidate can move fast but with high quality, and views the early stages of product development as a creative canvas and opportunity for high impact.
ABOUT THE ROLE:
- Location: Remote-first (United States; BC & ON, Canada)
- Full-time
- Permanent
- Exempt
- Our cash compensation amount for this role ranges depending on the cost of labor of the geographic area. The ranges shared below may change if you are hired in another geographic location.
- United States (all figures cited below in USD and pertain to workers in the United States)
- Zone A: 232,000 - 290,000
- Zone B: 217,600 - 272,000
- Zone C: 204,800 - 256,000
- Canada (All figures cited below in CAD and pertain to workers in ON & BC, Canada)
- 253,000 - 316,000
Please visit our Careers page https://webflow.com/careers#pay-zones for more information on which locations are included in each of our geographic pay zones. However, please confirm the zone for your specific location with your recruiter.
- Application Information:
- Application deadline: applications accepted on an ongoing basis until position is closed and filled
- This posting is for a new position
- Reporting to the Director, Engineering
As a Senior Staff Machine Learning Scientist, you’ll:
- Lead and drive ambitious research initiatives that advance the state of the art in computer vision, multimodal understanding, and visual generation.
- Develop novel models, algorithms, and training methodologies for challenging vision problems such as image understanding, video understanding, visual search, scene representation, segmentation, detection, generation, and multimodal reasoning.
- Translate cutting-edge research into practical model improvements that can shape product direction and unlock new user experiences.
- Design, implement, train, and optimize large-scale vision and multimodal foundation models across diverse datasets and tasks.
- Partner closely with applied scientists, ML engineers, and product teams to move research from exploration to production-ready systems.
- Set technical direction for high-impact research areas, identifying promising bets and influencing longer-term strategy for vision and multimodal AI.
- Mentor other scientists and engineers, raise the quality bar for research, and help build a strong scientific culture across the team.
- Stay at the forefront of research in computer vision, multimodal learning, generative modeling, and foundation models, and apply emerging techniques to real-world problems.
ABOUT YOU:
Requirements:
- BA/BS degree or equivalent experience
You’ll thrive as a Senior Staff Machine Learning Scientist if you:
- Deep theoretical and practical expertise in computer vision, with strong foundations in areas such as representation learning, visual recognition, image or video generation, multimodal learning, and large-scale model training.
- Advanced degree in Computer Science, Electrical Engineering, Statistics, Applied Mathematics, or a related field; PhD strongly preferred.
- 8+ years of relevant industry and/or research experience, or equivalent impact, including a track record of driving major research initiatives in computer vision or multimodal machine learning.
- Strong experience with state-of-the-art vision and multimodal model architectures, including transformers, diffusion models, contrastive learning approaches, and foundation models.
- Proven ability to formulate research problems clearly, design rigorous experiments, and translate findings into meaningful model or product advances.
- Strong coding and prototyping skills in Python, with the ability to write clean, scalable, and well-documented research code.
- Proficiency in modern deep learning frameworks such as PyTorch and TensorFlow.
- Demonstrated technical leadership, including mentoring scientists or engineers and influencing research direction across a team or organization.
- Strong communication skills, with the ability to present complex research clearly to both technical and cross-functional audiences.
- Stay curious and open to growth — demonstrating a proactive embrace of AI, and actively building and applying fluency in emerging technologies to elevate how we work, drive faster outcomes, and expand collective impact.
OUR CORE BEHAVIORS
- Build lasting customer trust. We build trust by taking action that puts customer trust first.
- Win together. We play to win, and we win as one team. Success at Webflow isn't a solo act.
- Reinvent ourselves. We don't just improve what exists, we imagine what's possible.
- Own it all the way. We move fast because the moment demands it, and we hold ourselves accountable to deliver outcomes — for each other, and for customers.
BENEFITS
- Ownership in what you help build. Every permanent Webflower receives equity (RSUs) in our growing, privately held company.
- Health coverage that actually covers you. Comprehensive medical, dental, and vision plans for full-time employees and their dependents, with Webflow covering most premiums.
- Support for every stage of family life. 12 weeks of paid parental leave for all parents and 6+ weeks of additional paid leave for birthing parents. Plus inclusive care for family planning, menopause, and midlife transitions.
- Time off that’s actually off. Flexible vacation, paid holidays, and a sabbatical program to help you recharge and come back inspired.
- Wellness for the whole you. Access to mental health resources, therapy and coaching.
- Invest in your future. A 401(k) with 100% employer match (up to $6,000/year) in the U.S., and support for retirement savings globally.
- Monthly stipends that flex with your life. Localized support for work and wellness expenses — from Wi-Fi to workouts.
- Bonus for building together. All full-time, permanent, non-commission employees are eligible for our annual WIN bonus program.
Temporary employees may be eligible for paid holiday and time off, statutory leaves of absence, and company-sponsored medical benefits depending on their Fixed Term Contract and their country/state of employment.
BE YOU, WITH US
At Webflow, equality is a core tenet of our culture. We are an Equal Opportunity (EEO)/Veterans/Disabled Employer and are committed https://webflow.com/diversity-equity-inclusion to building an inclusive global team that represents a variety of backgrounds, perspectives, beliefs, and experiences. Employment decisions are made on the basis of job-related criteria without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other classification protected by applicable law. Pursuant to the San Francisco Fair Chance Ordinance, Webflow will consider for employment qualified applicants with arrest and conviction records.
STAY CONNECTED
Not ready to apply, but want to be part of the Webflow community? Consider following our story on our Webflow Blog https://webflow.com/blog, LinkedIn https://www.linkedin.com/company/webflow-inc-/, X (Twitter) https://twitter.com/webflow, and/or Glassdoor https://www.glassdoor.com/Reviews/Webflow-Reviews-E890506.htm.
PLEASE NOTE:
We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Upon interview scheduling, instructions for accommodation requests will be administered.
To join Webflow, you'll need a valid right to work authorization depending on the country of employment.
If you are extended an offer, that offer may be contingent upon your successful completion of a background check, which will be conducted in accordance with applicable laws. We may obtain one or more background screening reports about you, solely for employment purposes.
Webflow uses AI tools to assist in screening and evaluating applications. AI does not make final hiring decisions. For details on how we process your personal information, see Webflow’s Applicant Privacy Notice https://webflow.com/legal/applicant-privacy-notice.
Location: Espoo
Workplace: Hybrid
- Title: RF Engineer, Radar Payload Team
- Location: Espoo, Finland
- Department: Spacecraft Hardware
- Reports to: Radar Payload Team Leadd
- Employment type: Permanent
- Workplace model: Hybrid / Office
- Employment is subject to applicable security screening (incl. SUPO)
WHY THIS ROLE MATTERS:
As an RF Engineer, you’ll support the performance, reliability, and continuous improvement of ICEYE’s radar payloads by maintaining and evolving RF hardware that enables high-quality Earth observation from space.
WHO WE ARE
ICEYE delivers space-based intelligence, surveillance, and reconnaissance (ISR) capabilities to governments and allied nations. This includes sovereign and turnkey ISR missions leveraging ICEYE’s world-leading synthetic aperture radar (SAR) satellite technology, as well as access to data from the world’s largest SAR satellite constellation. These capabilities enable partners to detect and respond to critical changes anywhere on Earth with unprecedented speed and accuracy, day or night and in any weather, supported by ultra high-resolution imagery and high-frequency revisits.
As a trusted partner for defense, intelligence, security, and maritime domain awareness, ICEYE’s near real-time data creates a tactical advantage for mission-critical operations. Designed for dual use, the platform also serves civil protection and commercial users for natural-catastrophe intelligence, insurance, maritime monitoring including oil-spill detection, and finance, contributing to global security and community resilience.
ICEYE is headquartered in Finland and operates globally across Europe, North America, the Middle East, and Asia-Pacific. We have more than 900 employees, united by a shared vision: improving life on Earth by becoming the global source of truth in Earth Observation.
YOUR DAY-TO-DAY RESPONSIBILITIES
- Support maintenance, updates, and continuous improvement of existing RF hardware systems
- Assist in the design, simulation, and validation of RF circuits for X-band and above
- Perform hands-on lab work including testing, debugging, root-cause analysis, and tuning using RF test equipment
- Run EM and circuit simulations and correlate results with measurements
- Create, review, and update schematics and PCB layouts with RF-critical design considerations
- Support verification activities including test plans, procedures, and validation of prototypes
- Maintain and produce technical documentation for hardware updates and processes
- Collaborate closely with senior engineers and cross-functional teams across the payload development lifecycle
WHAT WE’RE LOOKING FOR
MUST HAVES:
- 4+ years of experience in RF engineering with a focus on practical product development
- Hands-on experience performing RF measurements and troubleshooting in lab environments
- Experience with RF test equipment such as VNA, spectrum analyzers, and signal generators
- Experience with PCB design tools such as Altium and understanding of RF layout best practices
- Familiarity with RF simulation tools such as ADS and 3D EM tools such as HFSS or CST
- Solid understanding of RF fundamentals including linearity, noise figure, phase noise, and filtering
- Ability to collaborate effectively within cross-functional engineering teams
NICE TO HAVES:
- Experience with Python for analysis or automation
- Experience with radar payloads, spaceborne RF systems, or aerospace hardware
- Experience with high-power RF or low-noise receiver design
- Familiarity with qualification standards such as ECSS or MIL and environmental testing
APPLICATION PROCESS
- Recruiter screening
- Hiring manager interview
- Technical task
- Technical panel interview
- Final interview
WORKING AT ICEYE
At ICEYE, you’ll join a diverse and highly engaged team united by the ambition to make the impossible possible. As a global scale-up, we combine speed and ambition with the opportunity to take real ownership from day one. Your growth, wellbeing, and success are a priority, with continuous professional development, training opportunities, and a culture where collaboration is how we win.
HOW WE WORK (OUR VALUES)
Make the impossible possible: We set ambitious goals and stay calm under pressure. We bring grit, optimism, and ownership when things get hard, and we keep moving until we find a way.
- Be curious: Go deep, ask questions, listen carefully, and think critically. Understand the why behind decisions.
- See the big picture: Stay close to what’s happening across the company so you can make better decisions. Consider how your work affects others.
- Drive effective teamwork: Create psychological safety, invite different perspectives, and build inclusive teams. There are no bad questions.
- Act as one team: We win together. We match tasks to the right owner and stay agile as priorities shift.
- Have fun: What we do matters and it should be enjoyable. Celebrate progress, take pride in results, and share the wins.
BENEFITS
Our benefits are designed to support your health and wellbeing, at work and beyond. We keep improving them based on employee feedback, and offerings vary by location. Talent Acquisition will confirm what applies for this role and location during the process.
OUR COMMITMENT TO DIVERSITY, EQUITY, AND INCLUSION
We want ICEYE to be a place where people can be themselves and do great work. Different backgrounds and perspectives make us stronger, which is why we work to create an environment where people feel included, respected, and able to speak up. Whatever your background, we want you to bring your authentic self to the table.
We’re committed to fair, inclusive hiring and equal opportunity. Everyone is welcome to apply. If you need any adjustments or support during the recruitment process, tell us and we will do our best to help.
Apply now to start your ICEYE journey and help us continue to make the impossible possible together. Read more about ICEYE and working with us at iceye.com http://iceye.com.
Задачи:
— Участие в разработке и деплое ML/LLM решений.
— Применение Prompt Engineering и методов Fine-tuning/PEFT.
— Построение RAG пайплайнов и работа с векторными базами данных.
— Оптимизация производительности LLM и оценка их качества.
— Разработка с использованием мультимодальных моделей.
Требования:
— Уверенное владение Python.
— Опыт деплоя ML/LLM решений с использованием Docker, Kubernetes, облачных платформ AWS, GCP, Azure.
— Опыт работы с Prompt Engineering (few-shot, chain-of-thought, ReAct).
— Знание Fine-tuning / PEFT (LoRA, QLoRA, adapters).
— Опыт построения RAG пайплайнов (chunking → embedding → retrieval → генерация).
— Умение работать с векторными базами данных (Qdrant, Pinecone, Milvus, FAISS).
— Опыт RLHF или работы с синтетическими данными (предпочтения, генерация и фильтрация).
— Знание фреймворков LangChain, LlamaIndex, Hugging Face.
— Опыт оценки LLM (BLEU, ROUGE, MMLU, кастомные эвалы).
— Опыт оптимизации инференса (vLLM, TensorRT, ONNX).
— Опыт работы с мультимодальными моделями (LLaVA, GPT-4V, Qwen-VL).
— Грейд Middle/Middle+.
Условия:
— Полная занятость.
— Удалённый формат работы.
— Интересные проекты в области ИИ.
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. OKX is part of OKG, a group that brings the value of Blockchain to users around the world, through our leading products OKX, OKX Wallet, OKLink and more.
About the Opportunity
You will be responsible for the core architecture design and technical delivery of an enterprise-grade AI Native engineering platform, driving the deep integration of large language models, AI Agents, knowledge capabilities, and the software development lifecycle. The platform will support intelligent capabilities across requirement analysis, solution generation, coding collaboration, test automation, and environment orchestration.This role focuses on engineering-grade AI implementation in complex R&D scenarios. You are expected to turn model capabilities into reusable, scalable, and governable platform capabilities, and continuously drive the evolution of the engineering platform toward an AI Native architecture.
What You’ll Be Doing
Lead the
overall architecture design and core capability development
of the AI Agent platform, including task orchestration, tool invocation, context management, memory mechanisms, and multi-agent collaboration.
Drive the
implementation of AI Native capabilities in engineering workflows
, including AI coding, technical solution generation, test case generation, test report generation, and automated environment deployment.
Build the
knowledge augmentation layer
for the platform, including the design, integration, and application of RAG, GraphRAG, and knowledge graph capabilities.
Establish the
runtime and governance framework
for AI Agents, including execution isolation, permission control, auditability, evaluation, stability, and cost governance.
Collaborate with product, engineering, QA, and operations teams to standardize, productionize, and scale platform capabilities, continuously improving engineering efficiency and delivery quality.
What We Look For In You
Bachelor’s degree or above
, preferably in Computer Science, Software Engineering, Artificial Intelligence, or related fields.
6+ years
of experience in backend engineering, platform engineering, or infrastructure engineering, with strong system design and delivery capabilities.
Proficient in
Java / Python
, with solid coding skills, architectural thinking, and experience building complex systems.
Strong understanding of
LLM
and AI Agent architectures
, including task decomposition, tool use, context management, memory, execution loops, and exception handling.
Hands-on experience with
LangChain and LangGraph
, and strong familiarity with mainstream AI coding tools or frameworks such as
Claude Code
, Codex,
Cursor
, and Copilot
.
Experience in designing or developing
RAG / GraphRAG / knowledge graph
solutions for enterprise knowledge augmentation and engineering use cases.
Good understanding of
DevOps
,
CI/CD
,
Kubernetes
, and cloud-native technologies
, with strong cross-functional collaboration and execution skills.
Nice to Haves
Experience contributing to
open-source projects
related to AI Agents, AI Coding, RAG, or knowledge graphs.
Experience building
enterprise engineering platforms,
DevOps
platforms, or AI platforms
.
Familiarity with open-source Agent projects such as
openclaw, openhands/openharness, or Hermes
.
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: San Francisco; Palo Alto
Workplace: Hybrid
Perplexity serves tens of millions of users daily with reliable, high-quality answers grounded in an LLM-first search engine and specialized data sources. The Answer Quality team ensures that our prompts, tools, search systems, datasets, and models work together to create the best possible experience for our users.
As our product and agent capabilities evolve, we need evaluation systems that are fast, reliable, production-faithful, and actionable. In this role, you will build and improve the technical foundations that support Answer Quality across Perplexity. This includes our shared evaluation infrastructure and the platform used to replay and analyze agent traces. You will work closely with data scientists, engineers, and product teams to identify quality problems, measure their impact, and turn evaluation findings into product improvements.
RESPONSIBILITIES
- Build shared evaluation infrastructure that helps teams run reliable evals, analyze results, and make product and model decisions
- Develop the platform for replaying and analyzing agent traces to reproduce production behavior and diagnose failures
- Build and operate scalable systems for processing, storing, and monitoring interaction, trace, and evaluation data
- Partner with data scientists, engineers, and product teams to turn answer-quality problems into evaluations, analyses, and product improvements
- Operate in a small, high-impact team where your work directly shapes how Perplexity measures and improves Answer Quality
QUALIFICATIONS
- 4+ years of software, data, or machine learning engineering experience shipping and operating production systems
- Strong proficiency in Python and SQL, with solid fundamentals in system design, data modeling, and distributed systems
- Experience building big-data systems, including distributed compute, large-scale storage, and high-volume pipelines
- Demonstrated ownership of ambiguous technical projects from initial design through production operation
- Ability to work effectively with data scientists, engineers, and product partners
PREFERRED QUALIFICATIONS
- Experience building evaluation, experimentation, observability, or machine learning infrastructure
- Familiarity with LLM and agent systems, including tool use, execution traces, replay, and simulation
- Experience building on top of large-scale data processing platforms such as Databricks, Snowflake, or ClickHouse
Location: Mississauga, Ontario
Workplace: hybrid
At PointClickCare our mission is simple: to help providers deliver exceptional care. And that starts with our people. As a leading health tech company that’s founder-led and privately held, we empower our employees to push boundaries, innovate, and shape the future of healthcare.
With the largest long-term and post-acute care dataset and a Marketplace of 400+ integrated partners, our platform serves over 30,000 provider organizations, making a real difference in millions of lives. We also reinvest a significant percentage of our revenue back into research and development, ensuring our employees have the resources to innovate and make a lasting impact. Recognized by Forbes as a top private cloud company and honored as one of Canada’s Most Admired Corporate Cultures, we offer flexibility, growth opportunities, and meaningful work.
At PointClickCare, we empower our people to be the architects of a smarter healthcare future; one that is human-first and accelerated by AI to create meaningful and lasting change. Employees harness AI as a catalyst for creativity, productivity, and thoughtful decision-making. By integrating AI tools into our daily workflows, collaboration is enhanced, outcomes are improved, and every team member has the proficiency to maximize their impact. It all starts with our hiring practices where we uncover AI expertise that complements our mission, and we continue to invest in training and development to nurture innovation throughout the employee journey.
Join us in redefining healthcare — so it doesn’t just survive, it thrives. To learn more about PointClickCare, check out Life at PointClickCare and connect with us on Glassdoor and LinkedIn.
**Travel to Office expectations**
For Remote Roles: If this role is remote, there will be in-office events that will require travel to and from the Mississauga and/or Salt Lake City office. These will include, but not limited to, onboarding, team events, semi-annual and annual team meetings.
For Hybrid Roles: If this role is Hybrid, there will be an expectation to reside within commutable distance to the office/location specified in the job listing. This will include, but not limited to, weekly/bi-weekly/monthly events in the office with your specific team. This is a requirement for this role.
Job title: Senior Software Engineer
About the role:
You will join a high-impact team transforming healthcare through technology. Our platform
connects fragmented clinical systems to enable real-time care coordination across
thousands of healthcare facilities, serving millions of users. You will design and build
scalable platform services, leveraging modern AI-augmented engineering practices to
accelerate delivery, improve reliability, and enhance clinical and operational outcomes
What your day-to-day will look like:
• Build robust platform services supporting clinical operations
• Partner with product and clinical teams to understand and solve real workflow
challenges
• Drive architectural decisions for business platform services
• Own the reliability and performance of critical healthcare solutions
• Mentor team members on modern engineering practices
What qualifications we’re looking for:
Required Technical Experience
•Strong track record building and shipping production software in modern languages
(Java, Python, or similar)
• Deep understanding of cloud-native architecture and distributed systems design
patterns
• Expertise in design, optimization, and scaling for relational (SQL) database
systems, bonus points for NoSQL database systems
• Experience designing and implementing RESTful APIs and microservices
• Proficiency with test-driven development, automated testing, and maintaining high
code quality
• Hands-on experience with modern frontend frameworks, primarily React or Vue.js.
• Working knowledge of CI/CD pipelines and infrastructure-as-code practices
• Experience with production observability, monitoring, and performance
optimization tools
Modern Engineering Practices
• Comfortable using AI-augmented development tools (e.g., GitHub Copilot, Claude
Code) as part of your workflow
• Experience applying AI tools throughout the development lifecycle from
requirements analysis, documentation to incident response
• Strong code review skills demonstrated through giving and receiving constructive
feedback
• Experience with Git workflows and collaborative development practices
• Ability to balance feature delivery with system reliability and technical excellence
• Comfortable with on-call responsibilities and incident response
What Would Make You Stand Out
• Experience building and scaling SaaS platforms
• Track record of mentoring engineers or leading technical initiatives
• Background with Spring Boot and Java ecosystem
• Experience with Azure cloud services and Kubernetes (AKS)
• Experience in healthcare technology or regulated industries
• Understanding of HIPAA compliance and handling sensitive data
Our Stack
• Front-End: React/Vue JS, Micro-Frontends, Material-UI
• Backend: Java, Spring Boot
• Data: PostgreSQL, MSSQL, Redis
• CI/CD: GitHub Actions, Jenkins
• Infrastructure: Azure, AKS, Terraform
• AI Tooling: Claude Code, Copilot
#LI-AJ1
#LI-Hybrid
PointClickCare Benefits & Perks:
Benefits starting from Day 1!
Retirement Plan Matching
Flexible Paid Time Off
Wellness Support Programs and Resources
Parental & Caregiver Leaves
Fertility & Adoption Support
Continuous Development Support Program
Employee Assistance Program
Allyship and Inclusion Communities
Employee Recognition … and more!
It is the policy of PointClickCare to ensure equal employment opportunity without discrimination or harassment on the basis of race, religion, national origin, status, age, sex, sexual orientation, gender identity or expression, marital or domestic/civil partnership status, disability, veteran status, genetic information, or any other basis protected by law. PointClickCare welcomes and encourages applications from people with disabilities. Accommodations are available upon request for candidates taking part in all aspects of the selection process. Please contact recruitment@pointclickcare.com should you require any accommodations. As part of our commitment to a streamlined and equitable hiring experience, PointClickCare uses AI tools to assist with candidate screening and assessment.
When you apply for a position, your information is processed and stored with Lever, in accordance with Lever’s Privacy Policy. We use this information to evaluate your candidacy for the posted position. We also store this information, and may use it in relation to future positions to which you apply, or which we believe may be relevant to you given your background. When we have no ongoing legitimate business need to process your information, we will either delete or anonymize it. If you have any questions about how PointClickCare uses or processes your information, or if you would like to ask to access, correct, or delete your information, please contact PointClickCare’s human resources team: recruitment@pointclickcare.com
PointClickCare is committed to Information Security. By applying to this position, if hired, you commit to following our information security policies and procedures and making every effort to secure confidential and/or sensitive information.
At PointClickCare, base salary is one of the many components that make up our total rewards package. The CAD base salary range for this position is $142,000-158,000 (not overtime eligible) + bonus + benefits. Compensation is assessed individually and aligned to experience, skills, and market context. The posted range reflects typical expectations for this role.
Location: London
Workplace: Hybrid
We are looking for an AI Infra engineer to join our growing team. We work with Kubernetes, Slurm, Python, C++, PyTorch, and primarily on AWS. As an AI Infrastructure Engineer, you will be partnering closely with our Inference and Research teams to build, deploy, and optimize our large-scale AI training and inference clusters.
RESPONSIBILITIES
- Design, deploy, and maintain scalable Kubernetes clusters for AI model inference and training workloads
- Manage and optimize Slurm-based HPC environments for distributed training of large language models
- Develop robust APIs and orchestration systems for both training pipelines and inference services
- Implement resource scheduling and job management systems across heterogeneous compute environments
- Benchmark system performance, diagnose bottlenecks, and implement improvements across both training and inference infrastructure
- Build monitoring, alerting, and observability solutions tailored to ML workloads running on Kubernetes and Slurm
- Respond swiftly to system outages and collaborate across teams to maintain high uptime for critical training runs and inference services
- Optimize cluster utilization and implement autoscaling strategies for dynamic workload demands
QUALIFICATIONS
- Strong expertise in Kubernetes administration, including custom resource definitions, operators, and cluster management
- Hands-on experience with Slurm workload management, including job scheduling, resource allocation, and cluster optimization
- Experience with deploying and managing distributed training systems at scale
- Deep understanding of container orchestration and distributed systems architecture
- High level familiarity with LLM architecture and training processes (Multi-Head Attention, Multi/Grouped-Query, distributed training strategies)
- Experience managing GPU clusters and optimizing compute resource utilization
REQUIRED SKILLS
- Expert-level Kubernetes administration and YAML configuration management
- Proficiency with Slurm job scheduling, resource management, and cluster configuration
- Python and C++ programming with focus on systems and infrastructure automation
- Hands-on experience with ML frameworks such as PyTorch in distributed training contexts
- Strong understanding of networking, storage, and compute resource management for ML workloads
- Experience developing APIs and managing distributed systems for both batch and real-time workloads
- Solid debugging and monitoring skills with expertise in observability tools for containerized environments
PREFERRED SKILLS
- Experience with Kubernetes operators and custom controllers for ML workloads
- Advanced Slurm administration including multi-cluster federation and advanced scheduling policies
- Familiarity with GPU cluster management and CUDA optimization
- Experience with other ML frameworks like TensorFlow or distributed training libraries
- Background in HPC environments, parallel computing, and high-performance networking
- Knowledge of infrastructure as code (Terraform, Ansible) and GitOps practices
- Experience with container registries, image optimization, and multi-stage builds for ML workloads
REQUIRED EXPERIENCE
- Demonstrated experience managing large-scale Kubernetes deployments in production environments
- Proven track record with Slurm cluster administration and HPC workload management
- Previous roles in SRE, DevOps, or Platform Engineering with focus on ML infrastructure
- Experience supporting both long-running training jobs and high-availability inference services
- Ideally, 3-5 years of relevant experience in ML systems deployment with specific focus on cluster orchestration and resource management
ОфисUK, London; We are open to strong candidates from junior through staff level
Не хотите искать каждый день?
Настройте подбор один раз, и подходящие вакансии будут сами приходить в Telegram.
Настройте подбор, и подходящие вакансии будут приходить в Telegram.
