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: 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
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
Location: San Francisco; Palo Alto; New York City
We build and run the inference engine behind every Perplexity query and deploy dozens of model architectures at scale with tight latency and cost budgets. Our stack is Rust, Python, CUDA, and CuTe DSL - and we need another engineer to join us.
WHAT YOU WILL WORK ON
Examples of real work the team does:
- New models support. Support transformer-based retrieval, text-generation, and multimodal models in our inference infrastructure, from weight loading, request scheduling and KV-cache management to support in API Gateway.
- GPU kernels migration to CuTe DSL. Port our in-house CUDA kernels to NVIDIA's CuTe DSL so they run on GB200 today and are portable to Vera Rubin racks tomorrow.
- Rust-native serving runtime. Develop our internal Rust-based inference server to solve all Python pains and keep up with rapidly growing traffic.
- Performance optimisation. Profile and fix bottlenecks from network ingress through continuous batching and GPU kernel interleaving.
- Reliability and observability. Build dashboards, alerts, and automated remediation so we catch regressions before users do. Respond to and learn from production incidents.
WHO WE'RE LOOKING FOR
- Deep experience with GPU programming and performance work (CUDA, Triton, CUTLASS, or similar). Any other deep systems programming experience is a plus.
- You understand modern LLM architectures and are able to bring them up reliably in a production environment.
- You've built and operated production distributed systems under real load - ideally performance-critical ones.
- Comfortable working across languages and layers: Rust for the serving runtime, Python for model code, CUDA/CuteDSL for kernels.
- You own problems end-to-end. You can read a research paper on Monday, write a kernel on Wednesday, and debug a production incident on Friday.
- Self-directed. You do well in fast-moving environments where the path forward isn't laid out for you.
GOOD IF YOU TOUCHED ANY OF
- ML compilers and framework internals: PyTorch internals, torch.compile, custom operators.
- Distributed GPU communication: NCCL, NVLink, InfiniBand, RDMA libraries, model/tensor parallelism.
- Low-precision inference: INT8/FP8/FP4 quantization, mixed-precision serving.
- Profiling and debugging tools: Nsight Compute/Systems, CUDA-GDB, PTX/SASS analysis.
- Container orchestration: Kubernetes, GPU scheduling, autoscaling inference workloads.
QUALIFICATIONS
- 3+ years of professional software engineering experience with meaningful work on ML inference or high-performance systems.
- Familiarity with at least one deep learning framework (PyTorch, JAX, TensorFlow).
- Understanding of GPU architectures (memory hierarchy, warp scheduling, tensor cores).
- Understanding of common LLM architectures and inference optimization techniques (e.g. quantization, speculative decoding, prefill-decode disaggregation).
Location: San Francisco; Palo Alto; New York City
We build and run the inference engine behind every Perplexity query and deploy dozens of model architectures at scale with tight latency and cost budgets. Our stack is Rust, Python, CUDA, and CuTe DSL - and we need another engineer to join us.
WHAT YOU WILL WORK ON
Examples of real work the team does:
- New models support. Support transformer-based retrieval, text-generation, and multimodal models in our inference infrastructure, from weight loading, request scheduling and KV-cache management to support in API Gateway.
- GPU kernels migration to CuTe DSL. Port our in-house CUDA kernels to NVIDIA's CuTe DSL so they run on GB200 today and are portable to Vera Rubin racks tomorrow.
- Rust-native serving runtime. Develop our internal Rust-based inference server to solve all Python pains and keep up with rapidly growing traffic.
- Performance optimisation. Profile and fix bottlenecks from network ingress through continuous batching and GPU kernel interleaving.
- Reliability and observability. Build dashboards, alerts, and automated remediation so we catch regressions before users do. Respond to and learn from production incidents.
WHO WE'RE LOOKING FOR
- Deep experience with GPU programming and performance work (CUDA, Triton, CUTLASS, or similar). Any other deep systems programming experience is a plus.
- You understand modern LLM architectures and are able to bring them up reliably in a production environment.
- You've built and operated production distributed systems under real load - ideally performance-critical ones.
- Comfortable working across languages and layers: Rust for the serving runtime, Python for model code, CUDA/CuteDSL for kernels.
- You own problems end-to-end. You can read a research paper on Monday, write a kernel on Wednesday, and debug a production incident on Friday.
- Self-directed. You do well in fast-moving environments where the path forward isn't laid out for you.
GOOD IF YOU TOUCHED ANY OF
- ML compilers and framework internals: PyTorch internals, torch.compile, custom operators.
- Distributed GPU communication: NCCL, NVLink, InfiniBand, RDMA libraries, model/tensor parallelism.
- Low-precision inference: INT8/FP8/FP4 quantization, mixed-precision serving.
- Profiling and debugging tools: Nsight Compute/Systems, CUDA-GDB, PTX/SASS analysis.
- Container orchestration: Kubernetes, GPU scheduling, autoscaling inference workloads.
QUALIFICATIONS
- 3+ years of professional software engineering experience with meaningful work on ML inference or high-performance systems.
- Familiarity with at least one deep learning framework (PyTorch, JAX, TensorFlow).
- Understanding of GPU architectures (memory hierarchy, warp scheduling, tensor cores).
- Understanding of common LLM architectures and inference optimization techniques (e.g. quantization, speculative decoding, prefill-decode disaggregation).
Location: London
We are looking for an AI Inference Engineer to join our growing team. We build and run the inference engine behind every Perplexity query and deploy dozens of model architectures at scale with tight latency and cost budgets. Our stack is Rust, Python, CUDA, and CuTe DSL.
RESPONSIBILITIES:
- New models support. Support transformer-based retrieval, text-generation, and multimodal models in our inference infrastructure, from weight loading, request scheduling and KV-cache management to support in API Gateway.
- GPU kernels migration to CuTe DSL. Port our in-house CUDA kernels to NVIDIA's CuTe DSL so they run on GB200 today and are portable to Vera Rubin racks tomorrow.
- Rust-native serving runtime. Develop our internal Rust-based inference server to solve all Python pains and keep up with rapidly growing traffic.
- Performance optimisation. Profile and fix bottlenecks from network ingress through continuous batching and GPU kernels interleaving.
- Reliability and observability. Build dashboards, alerts, and automated remediation so we catch regressions before users do. Respond to and learn from production incidents.
WHO WE'RE LOOKING FOR:
- Deep experience with GPU programming and performance work (CUDA, Triton, CUTLASS, or similar). Any other deep systems programming experience is a plus.
- You understand modern LLM architectures and are able to bring them up reliably in a production environment.
- You've built and operated production distributed systems under real load - ideally performance-critical ones.
- Comfortable working across languages and layers: Rust for the serving runtime, Python for model code, CUDA/CuteDSL for kernels.
- You own problems end-to-end. You can read a research paper on Monday, write a kernel on Wednesday, and debug a production incident on Friday.
- Self-directed. You do well in fast-moving environments where the path forward isn't laid out for you.
NICE-TO-HAVE:
- ML compilers and framework internals: PyTorch internals, torch.compile, custom operators.
- Distributed GPU communication: NCCL, NVLink, InfiniBand, RDMA libraries, model/tensor parallelism.
- Low-precision inference: INT8/FP8/FP4 quantization, mixed-precision serving.
- Profiling and debugging tools: Nsight Compute/Systems, CUDA-GDB, PTX/SASS analysis.
- Container orchestration: Kubernetes, GPU scheduling, autoscaling inference workloads.
QUALIFICATIONS:
- 3+ years of professional software engineering experience with meaningful work on ML inference or high-performance systems.
- Familiarity with at least one deep learning framework (PyTorch, JAX, TensorFlow).
- Understanding of GPU architectures (memory hierarchy, warp scheduling, tensor cores).
- Understanding of common LLM architectures and inference optimization techniques (e.g. quantization, speculative decoding, prefill-decode disaggregation).
Final offer amounts are determined by multiple factors including experience and expertise.
Equity: In addition to the base salary, equity may be part of the total compensation package.
Location: London
We are looking for an AI Inference Engineer to join our growing team. We build and run the inference engine behind every Perplexity query and deploy dozens of model architectures at scale with tight latency and cost budgets. Our stack is Rust, Python, CUDA, and CuTe DSL.
RESPONSIBILITIES:
- New models support. Support transformer-based retrieval, text-generation, and multimodal models in our inference infrastructure, from weight loading, request scheduling and KV-cache management to support in API Gateway.
- GPU kernels migration to CuTe DSL. Port our in-house CUDA kernels to NVIDIA's CuTe DSL so they run on GB200 today and are portable to Vera Rubin racks tomorrow.
- Rust-native serving runtime. Develop our internal Rust-based inference server to solve all Python pains and keep up with rapidly growing traffic.
- Performance optimisation. Profile and fix bottlenecks from network ingress through continuous batching and GPU kernels interleaving.
- Reliability and observability. Build dashboards, alerts, and automated remediation so we catch regressions before users do. Respond to and learn from production incidents.
WHO WE'RE LOOKING FOR:
- Deep experience with GPU programming and performance work (CUDA, Triton, CUTLASS, or similar). Any other deep systems programming experience is a plus.
- You understand modern LLM architectures and are able to bring them up reliably in a production environment.
- You've built and operated production distributed systems under real load - ideally performance-critical ones.
- Comfortable working across languages and layers: Rust for the serving runtime, Python for model code, CUDA/CuteDSL for kernels.
- You own problems end-to-end. You can read a research paper on Monday, write a kernel on Wednesday, and debug a production incident on Friday.
- Self-directed. You do well in fast-moving environments where the path forward isn't laid out for you.
NICE-TO-HAVE:
- ML compilers and framework internals: PyTorch internals, torch.compile, custom operators.
- Distributed GPU communication: NCCL, NVLink, InfiniBand, RDMA libraries, model/tensor parallelism.
- Low-precision inference: INT8/FP8/FP4 quantization, mixed-precision serving.
- Profiling and debugging tools: Nsight Compute/Systems, CUDA-GDB, PTX/SASS analysis.
- Container orchestration: Kubernetes, GPU scheduling, autoscaling inference workloads.
QUALIFICATIONS:
- 3+ years of professional software engineering experience with meaningful work on ML inference or high-performance systems.
- Familiarity with at least one deep learning framework (PyTorch, JAX, TensorFlow).
- Understanding of GPU architectures (memory hierarchy, warp scheduling, tensor cores).
- Understanding of common LLM architectures and inference optimization techniques (e.g. quantization, speculative decoding, prefill-decode disaggregation).
Final offer amounts are determined by multiple factors including experience and expertise.
Equity: In addition to the base salary, equity may be part of the total compensation package.
Location: Sydney
Workplace: Hybrid
ABOUT US
Sierra is the leading platform for customer-facing AI agents, working with many of the world's biggest brands — including The GAP, Rocket Mortgage, SoFi, Sutter Health, and SoftBank — to transform how they serve customers and grow their businesses. We are primarily an in-person company based in San Francisco, with growing offices across North America, Europe, and Asia.
We are guided by a set of values that are at the core of our actions and define our culture: Trust, Customer Obsession, Craftsmanship, Intensity, and a commitment to balancing Family along the way. These values are the foundation of our work, and we are committed to upholding them in everything we do.
Sierra was co-founded by Bret Taylor https://www.linkedin.com/in/brettaylor/ and Clay Bavor https://www.linkedin.com/in/claybavor/ who first met while working together at Google over 20 years ago. Bret currently serves as Chairman of the Board of Open AI. Previously, he was co-CEO of Salesforce and CTO of Facebook. Clay spent 18 years at Google, where he most recently led Google Labs.
WHAT YOU’LL DO
- Design and deliver production-grade AI agents https://sierra.ai/blog/meet-the-ai-agent-engineer: You'll build and ship highly performant, reliable, and intuitive AI agents that are central, mission-critical and drive revenue directly to Sierra's growth. These aren't prototypes—they are powerful, scalable systems running in production environments across industries like finance, healthcare, and commerce.
- Drive the Agent Development Life Cycle https://sierra.ai/blog/agent-development-life-cycle (ADLC): You'll have complete ownership and autonomy from initial pilot through deployment and continuous iteration. You'll be responsible for building, tuning, and evolving AI agents in production environments, defining the standard for ADLC best practices along the way.
- Partner with large enterprises and cutting-edge startups: You’ll work directly with leaders at some of the world’s largest enterprises to understand their most pressing business challenges, and build AI agents that transform how they operate at scale. You'll also partner with the most cutting-edge startups, embedding AI agents across their entire business stack to drive innovation and efficiency.
- Build the future of the platform: Your direct work with customers will guide the evolution of Sierra's core platform. You'll surface unmet needs, prototype new tools and features, and collaborate with research, product, and platform to shape the future of AI agent development and Sierra's product.
EXAMPLE PROJECTS
These are some examples of projects that engineers on our team have worked on recently:
- Design and build AI agents for large telecommunications and media companies that consistently outperform human agents in managing subscription churn
- Develop and refine AI agents capable of navigating complex customer interactions, like troubleshooting a broken device and personalizing product recommendations
- Create generalizable AI agent frameworks tailored for industry-specific use cases. See some examples in our financial services blog https://sierra.ai/blog/five-ways-to-use-ai-agents-financial-services!
- Facilitate design partnerships for new product initiatives, such as new agent architectures, self-service capabilities, and generative agent development
- Experiment with the latest voice models and figure out how to integrate them at scale to enterprise-grade customers
WHAT YOU'LL BRING
- Experience building and scaling end-to-end production systems
- Strong technical problem-solving skills, especially in fast-changing, ambiguous environments
- A builder and tinkerer’s mindset with high agency - you find creative ways to overcome obstacles and ship
- Comfort working directly with customers to understand their needs and solve real-world problems
- Excellent communication skills - clear, direct, and persuasive across technical and non-technical audiences
EVEN BETTER...
- Experience building or deploying AI/LLM systems in production
- Have been a founder or founding engineer - you know what it means to balance craft, ownership, and speed
- Familiarity with tools that power today's AI agents: eval frameworks, agent tooling, RAG pipelines, and prompt engineering
- Prior experience with React, TypeScript, and/or Go
- Previous roles where you interfaced with customers or led technical projects with external stakeholders
OUR VALUES
- Trust: We build trust with our customers with our accountability, empathy, quality, and responsiveness. We build trust in AI by making it more accessible, safe, and useful. We build trust with each other by showing up for each other professionally and personally, creating an environment that enables all of us to do our best work.
- Customer Obsession: We deeply understand our customers’ business goals and relentlessly focus on driving outcomes, not just technical milestones. Everyone at the company knows and spends time with our customers. When our customer is having an issue, we drop everything and fix it.
- Craftsmanship: We get the details right, from the words on the page to the system architecture. We have good taste. When we notice something isn’t right, we take the time to fix it. We are proud of the products we produce. We continuously self-reflect to continuously self-improve.
- Intensity: We know we don’t have the luxury of patience. We play to win. We care about our product being the best, and when it isn’t, we fix it. When we fail, we talk about it openly and without blame so we succeed the next time.
- Family: We know that balance and intensity are compatible, and we model it in our actions and processes. We are the best technology company for parents. We support and respect each other and celebrate each other’s personal and professional achievements.
WHAT WE OFFER
We want our benefits to reflect our values and offer the following to full-time employees:
- Flexible (unlimited) paid time off
- Medical, dental, and vision benefits for you and your family
- Life insurance and disability benefits
- Retirement plan dependent on country of employment
- Parental leave
- Fertility and family building benefits
- Lunch, as well as delicious snacks and coffee to keep you energized when working onsite
- Discretionary benefit stipend giving people the ability to spend where it matters most
- Free alphorn lessons
These benefits are further detailed in Sierra's policies, may vary by region and employment type, and are subject to change at any time, consistent with the terms of any applicable compensation or benefits plans. Eligible full-time employees can participate in Sierra's equity plans subject to the terms of the applicable plans and policies.
BE YOU, WITH US
We're working to bring the transformative power of AI to every organization in the world. To do so, it is important to us that the diversity of our employees represents the diversity of our customers. We believe that our work and culture are better when we encourage, support, and respect different skills and experiences represented within our team. We encourage you to apply through the link on this page even if your experience doesn't precisely match the job description.
Sierra is a proud equal opportunity employer. All qualified applicants will receive consideration for employment without regard to any characteristic protected by applicable federal, state or local laws, including veteran status and disability status. Hiring decisions are made by people, based on merit. If you need a reasonable accommodation for a disability, a religious practice, pregnancy or any related condition at any point in the application or interview process, contact us at accommodations@sierra.ai. Requests are handled confidentially and do not affect your candidacy.
We will consider qualified applicants with arrest and conviction records in accordance with applicable fair chance laws.
Location: Denver, CO; Seattle, WA; Chicago, IL (Remote); United States (Remote);
At Signifyd, we help merchants confidently grow their businesses by building trusted relationships with their customers. Our advanced technology, combined with a team genuinely invested in our clients’ success, creates frictionless shopping experiences, approving more good orders, protecting revenue, and keeping customers happy.
Trusted by thousands of leading merchants across more than 100 countries, we securely process billions of transactions each year. Our people are the heart of everything we do, driving our mission forward with commitment, empathy, and creativity. Join us on our mission to empower confident, fraud-free commerce by helping online retailers provide superior customer experiences and eliminate fraud. Learn about our company values
here
!
The
Senior Machine Learning Engineer
will join our ML team. This team is responsible for building, maintaining, and monitoring the production ML models and offline experimentation frameworks that are at the core of Signifyd’s product. This includes the core fraud detection model that decides the majority of our traffic, alongside our model training and evaluation infrastructure. We work closely with Platform Engineering teams to contribute novel modeling methods, advanced feature engineering, and robust statistical practices.
Our Culture
We value tenacity, curiosity, and a hunger for learning. Our adversaries are highly motivated fraudsters looking to exploit any gap. We seek equally motivated individuals who are passionate about keeping our customers safe while pulling the field of adversarial machine learning forward.
The Role
As a
Senior Machine Learning Engineer
, you will be a driver of technical execution within the ML team. You won’t just build models—you’ll own the end-to-end lifecycle of high-impact ML projects, from offline experimentation to deployment to production. You will be responsible for improving model performance, refining our experimentation processes, and ensuring our fraud detection systems are robust, scalable, and scientifically sound.
Responsibilities:
Expand ML Capabilities
– Identify, prototype, and integrate new ML technologies and infrastructure to enhance fraud detection effectiveness and scalability.
Enable High-Velocity Experimentation
– Own the design and implementation of ML pipeline components that accelerate our innovation
Collaborate Across Functions
– Partner with Product, Engineering, and Risk teams to translate business requirements into technical solutions and ensure ML initiatives align with customer needs.
Raise the Bar
– Foster a culture of technical excellence by championing best practices in testing, documentation, model monitoring, and development.
Requirements:
Education:
A degree in Computer Science, Statistics, or a comparable quantitative field.
Experience:
4-6+ years
of post-undergrad work experience in a production-grade ML environment.
Technical Depth:
Strong foundation in machine learning theory, statistical evaluation, and experience with supervised/unsupervised learning at scale.
Execution Focus:
Proven track record of taking ML projects from research/prototype to high-scale production environments.
Communication:
Ability to communicate technical findings clearly to both technical peers and non-technical stakeholders.
Tech Stack:
Proficiency in Python
,
SQL, key ML libraries, and Spark
Mindset:
A strong outcome-oriented mindset—you care about the "why" behind the models and the business impact they create.
Attention to detail
is critical in fraud prevention. To demonstrate this, please start your response to the first application question with the word 'Stochastic'
Nice to have:
Previous experience in fraud, fintech, payments, or e-commerce.
Passion for writing well-tested production-grade code
A Master’s Degree or PhD.
Why Join Us?
Make an Impact
– Your work will directly shape the future of fraud prevention, protecting billions of payments.
Lead & Grow
– Drive high-visibility initiatives and develop leadership skills in a fast-paced, high-growth environment.
Innovate at Scale
– Work with cutting-edge ML technologies and experiment freely to push the boundaries of what’s possible.
Collaborative Culture
– Join a team that values curiosity, ownership, and continuous learning.
#LI-Remote
Benefits in our US offices:
Discretionary Time Off Policy (Unlimited!)
401K Match
Stock Options
Annual Performance Bonus or Commissions
Paid Parental Leave (12 weeks)
On-Demand Therapy for all employees & their dependents
Dedicated learning budget through Learnerbly
Health Insurance
Dental Insurance
Vision Insurance
Flexible Spending Account (FSA)
Short Term and Long Term Disability Insurance
Life Insurance
Company Social Events
Signifyd Swag
Compensation:
In the United States, each work location is assigned a specific pay zone, which determines the salary range for a given position. The starting base salary for the selected candidate will be based on a variety of factors, including job-related skills, experience, qualifications, geographic location, and current market conditions.
Base Salary Ranges by Pay Zone:
Tier 1 (NYC/SF Bay Area/Seattle): $160,000 - $190,000 annually
Tier 2 (DC Metro/Austin/Chicago/Denver/Boston/Los Angeles/San Diego):$150,000 - $180,000 annually
Tier 3 (US - All Other): $140,000 - $170,000 annually
Equity: This role is eligible for a stock option grant of 4,000 stock options, based on the position level and internal compensation guidelines.
Bonus:
This role is eligible for an annual performance bonus of up to 10% of base salary.
We want to provide an inclusive interview experience for all, including people with disabilities. We are happy to provide reasonable accommodations to candidates in need of individualized support during the
hiring
process.
Signifyd's Applicant Privacy Notice
Location: Colombia; Mexico; Argentina; Brazil; Costa Rica
We are seeking an
Engineering Manager – Mechanical & Electrical
to lead and develop a distributed team of LATAM-based engineering resources.
This role is
mechanically driven
, with strong responsibility for design quality, execution, and manufacturability, while also overseeing electrical engineering integration.
You will act as the
key bridge between U.S.-based stakeholders and LATAM execution teams
, ensuring all deliverables are accurate, aligned, and delivered on time.
This is a
technical leadership role
, requiring deep involvement in engineering work, not a people-only management position.
Engineering Leadership & Team Management
Lead and develop LATAM-based CAD Technicians, Drafters, Mechanical Design Engineers, and Electrical Engineers
Set clear expectations for quality, delivery, and technical rigor
Assign and prioritize work across multiple programs
Mentor engineers to improve technical capabilities and execution
Provide performance feedback and support ongoing development
Mechanical Engineering (Primary Focus)
Own mechanical design execution across modular systems, enclosures, and industrial structures
Review and approve designs for accuracy and manufacturability
Ensure proper application of materials, tolerances, and fabrication methods
Drive design-for-manufacturability (DFM) and design-for-assembly (DFA) best practices
Partner with Manufacturing Engineering to align designs with build strategies
Electrical Engineering Oversight
Provide leadership and oversight for electrical engineering deliverables
Ensure clean integration between electrical systems and mechanical layouts
Review schematics, layouts, and documentation for completeness and consistency
Coordinate and resolve mechanical–electrical interface challenges
Standards, Quality & Governance
Establish and enforce engineering standards, templates, and best practices
Ensure consistent use of CAD tools, drawing standards, and revision control
Maintain quality control across engineering output from LATAM teams
Support engineering change management and design revisions
Cross-Functional Collaboration
Collaborate with Engineering, Manufacturing, Supply Chain, and Program teams
Translate project requirements into clear engineering work packages
Support project timelines, milestones, and risk identification
Act as a technical escalation point for complex design challenges
Global Team Execution
Manage distributed teams across time zones with clear communication and structure
Ensure alignment between stakeholders and LATAM engineering execution
Drive accountability without micromanagement
Build repeatable workflows for offshore engineering support
Technical Review & Risk Management
Review complex designs for technical risk, cost drivers, and manufacturability concerns
Identify issues early and drive corrective action
Ensure designs meet compliance, safety, and customer requirements
Requirements
Must-Have
Bachelor’s degree in Mechanical Engineering or related discipline
10+ years of experience in industrial, modular, or engineered-to-order environments
5+ years of experience leading engineering teams
Strong mechanical engineering background with design experience
Experience managing remote or distributed teams
Ability to review and approve mechanical and electrical designs
Strong communication and technical leadership skills
Nice-to-Have
Experience with modular systems, enclosures, or industrial equipment
Experience working with CAD teams and drafting resources
Familiarity with SolidWorks and SolidWorks Electrical
Experience integrating mechanical and electrical systems
Experience working with LATAM or offshore engineering teams
Exposure to manufacturing, fabrication, or production environments
Benefits
Work for the most exciting companies in the North American Market.
Flexible schedules.
Work from anywhere.
Highly competitive compensation.
Location: Jeddah, Saudi Arabia; Lusail, Qatar; Dubai, United Arab Emirates; Cairo, Egypt; Lahore, Pakistan; New Delhi, India
We are seeking a skilled Maintenance Engineer - Biomedical to join our team in Saudi Arabia. The Maintenance Engineer - Biomedical will be responsible for maintaining, troubleshooting, and repairing biomedical equipment to ensure optimal functionality and safety standards are met. This role involves performing preventive maintenance, conducting inspections, and supporting the installation and commissioning of new biomedical devices.
The Maintenance Engineer - Biomedical is responsible for ensuring the effective and reliable delivery of maintenance services across all community facilities and systems at KAUST. The role focuses on monitoring, auditing, and verifying the performance of service providers to ensure compliance with contractual, technical, and safety standards.
Key responsibilities include managing both preventive and corrective maintenance activities, ensuring they are carried out efficiently, safely, and in accordance with established schedules and procedures. By conducting regular inspections, technical evaluations, and performance reviews, the engineer safeguards asset quality and reliability while fostering continuous improvement and operational excellence.
Responsibilities
Ensure effective execution, reliability, and quality of maintenance activities across all assigned facilities and assets.
Support and oversee preventive, corrective, and predictive maintenance operations to ensure safe and efficient performance.
Monitor daily maintenance activities carried out by service providers, ensuring compliance with schedules, SOPs, and KPIs.
Review work orders, reports, and field activities to verify completion, accuracy, and maintenance quality.
Provide technical expertise, troubleshooting support, and guidance across multiple asset categories and disciplines.
Ensure full compliance with contractual requirements, safety regulations, and industry standards (JCI, CBAHI/SBAHI, SFDA).
Conduct audits, inspections, and performance evaluations of service providers and maintenance processes.
Lead root cause analysis of equipment failures and implement corrective and preventive actions.
Maintain and update asset data in CMMS (SAP/Maximo) and support asset lifecycle and reliability strategies.
Oversee biomedical equipment maintenance, calibration, testing, and performance verification, ensuring compliance and operational readiness.
Requirements
Bachelor’s degree in Engineering (preferably Biomedical Engineering).
5–7 years of experience in biomedical equipment maintenance and operations.
Strong knowledge of preventive, corrective, and predictive maintenance methodologies.
Proficiency in CMMS systems such as SAP or Maximo.
Knowledge of international healthcare and engineering standards (JCI, CBAHI/SBAHI, SFDA, IEC 60601, HTM).
Expertise in biomedical equipment calibration, performance testing, and lifecycle management.
Proven experience in contractor coordination, audits, inspections, and technical reporting.
Professional certifications (CMRP, BMET) and safety training (OSHA/EHS) are preferred.
Location: Remote
Company Description
We are Olsson. We engineer and design solutions that improve the world around us. As a company, we promise to always be responsive, transparent, and focused on results – for our people, our clients, and our company.
We’re a people-centric firm, so it’s no surprise our greatest asset is our people. The impact this creates is an environment that encourages our people to grow and be creative with their talents. This approach builds a culture that is uniquely Olsson. It allows us to grow our people as we grow our business. This, in turn, creates a lasting impact on the world around us.
Job Description
Olsson provides multidisciplinary design services for some of the largest and most forward-thinking and desirable companies in the world to work for. We design large hyperscale data center campuses and colocation data centers throughout the U.S.. This role will give you the opportunity to work on some of the largest and most complex engineering-driven projects being built today. Our clients are relationship based and truly value the work we do for them, affording us the opportunity to contribute to society’s technological and connected community through the design of the critical infrastructure that is the foundation of these projects.
As a Project Civil Engineer on our Data Center Civil Team, you will be a part of the firm’s largest and most complex projects. You will serve as a project manager on some projects and lead design engineer on others. Prepare planning and design documents, process design calculations, and develop and maintain team and client standards. You may lead quality assurance/quality control and act as an advisor on complex projects. You will also coordinate with other Olsson teams, professional staff, technical staff, clients, and other consultants.
You may travel to job sites for observation and attend client meetings.
We have several current openings and will consider
candidates interested in being located out of any Olsson office location, hybrid, or fully remote in various locations of the US. This role includes
flexible work options to accommodate diverse working preferences and promote work-life balance.
Qualifications
You are passionate about:
Working collaboratively with others
Having ownership in the work you do
Using your talents to positively affect communities
Empowering others to use their talents
You bring to the team:
Strong communication skills
Ability to contribute and work well on a team
Bachelor's degree in civil engineering
Must be a registered professional engineer
Proficiency in Civil 3D software
6 or more years of related project experience
The salary range for this position correlates with our Colorado office locations and is commensurate with experience relative to the position.
#LI-AA1 #LI-Remote
Actual compensation will vary based on factors such as experience, qualifications, geographic location, skills, education, and internal equity.
Colorado Pay Range
$103,000
—
$135,000 USD
Additional Information
Olsson specializes in engineering and design, client advisory services, planning, field services, and environmental. Improving the world has been our mindset from the very beginning, back when Olsson first opened for business in 1956. And it will be our mindset for years to come.
As an Olsson employee, you will:
Receive a competitive 401(k) match
Be empowered to build your career with tailored development paths
Have the possibility for flexible work arrangements
Engage in work that has a positive impact on communities
Participate in a wellness program promoting balanced lifestyles
In addition, full-time employees will receive our traditional benefits package (health care, vision, dental, paid time off, etc.) and the opportunity to participate in a bonus system that rewards performance.
Olsson is an Equal Opportunity Employer. We encourage qualified minority, female, veteran, and disabled candidates to apply and be considered for open positions. We do not discriminate against any applicant for employment or any employee because of race, color, religion, national origin, sex, sexual orientation, gender identity, gender, disability, age, military status, or other protected status.
Olsson understands the importance of privacy and is committed to protecting job applicants’ personal information. Pursuant to the California Consumer Privacy Act, as amended by the California Privacy Rights Act (collectively, the “CCPA”), this notice explains Olsson’s practices regarding the collection, use, and disclosure of personal information for job applicants residing in California. Please read this Notice carefully to understand our privacy practices.
For more information about the types of information we collect and how we use it in connection with your general access and use of our website, please review our general California Privacy Notice
here
.
Location: India
Workplace: Remote
ClickHouse is the open-source, real-time analytical database behind a lot of today's AI. More than 4,000 companies build on ClickHouse, including Anthropic, OpenAI, Tesla and Meta.
As a Consulting Engineer, you're the hands-on engineer on our customers' most important projects. When a customer needs to migrate, integrate, or prove ClickHouse on a real workload, you work in the build alongside their engineers: you design it, build it, test it and hand it over.
You'll work on a broad mix of projects for customers across India, from moving large workloads off other databases to building new real-time analytics on ClickHouse. Each one is scoped with clear goals from the start, so you know what success looks like and can get stuck in. It's a fast way to build deep experience across lots of different data problems.
The consulting function at ClickHouse is less than a year old, so you'll help shape how ClickHouse delivers this work as the team grows. Between projects you take cases alongside support engineers, which keeps you close to day-to-day support.
WHAT YOU'LL DO
- Turn customer goals into a scoped project with measurable success criteria, sizing and a timeline
- Design a target architecture and prove it against the customer's own data: schema and engine design, capacity and sizing, proofs of concept
- Do the build: implementation, pipelines and integrations, migration execution, tooling and automation
- Measure it before it matters, with benchmarking, load and functional testing, then support the cutover
- Tune what production reveals, then hand over with an engagement report and knowledge transfer, so the customer's team can run it without you
- Take L1 to L3 cases alongside support engineers when you're between projects
- Feed what you see in the field back to Product and Engineering, and turn your work into reference architectures, knowledge base articles and blog posts
- Work in a constant feedback loop with the Pre-sales team to ensure that the demos and POCs they present are credible when you put them into production
WHAT YOU'LL BRING
- 5+ years delivering hands-on technical work for customers, whether your title was consultant, professional services, solutions architect, senior support, SRE or something else
- Real depth in databases, whether analytical, transactional or relational
- Hands-on SQL. You regularly write complex queries from scratch, and tune and debug them yourself
- You've owned implementations, migrations or POCs for external customers from start to finish
- Hands-on cloud experience (AWS, GCP and/or Azure)
- You've deployed and run workloads on Kubernetes yourself
- You've run distributed systems, such as distributed databases, in production
- You give precise technical answers and explain them clearly
- Fluent English
NICE TO HAVE
- Experience with ClickHouse
- Migrating analytical workloads from systems such as PostgreSQL, Snowflake, BigQuery or Elastic
- Terraform
- Data pipelines and streaming, such as Kafka, Kinesis, Spark or Debezium
- Python, Bash or Go
- Involvement in open source, as a user, contributor or community member
GOOD TO KNOW
- This role is remote in India
- Travel to customer sites is part of the job, up to 35% of your time, depending on the project: some need none, others weekly visits
- You'll join our India Support Services team, alongside Support Engineers and TAM Architects
- You'll be part of the on-call rotation, about one week a quarter, with time off in lieu if you're paged at a weekend
HOW WE HIRE
- A 30-minute call with our recruiter
- A conversation with the hiring manager
- A take-home exercise, designed to take three to four hours, with three working days to complete it
- A 90-minute technical interview with the team: you'll walk us through your take-home, then join a working session where you write and tune SQL live
- A final conversation with our VP of Support Services
- References, then an offer
The working session is without AI tools, so make sure you're comfortable writing queries from scratch. Download open-source ClickHouse and practise: it's free, easy to install, and great preparation.
PERKS
- Flexible work environment - ClickHouse is a globally distributed company and remote-friendly. We currently operate in over 25 countries.
- Healthcare - Employer contributions towards your healthcare.
- Equity in the company - Every new eligible team member who joins our company receives equity.
- Time off - Flexible time off in the US, generous entitlement in other countries.
- A USD$500 Home office setup if you’re a remote employee.
- Global Gatherings – We believe in the power of in-person connection and offer opportunities to engage with colleagues at company-wide offsites.
CULTURE - WE ALL SHAPE IT
As part of a rapidly scaling start-up, you will be instrumental in shaping our culture.
Are you interested in finding out more about our culture? Learn more about our values here https://clickhouse.com/company/careers. Check out our blog posts https://clickhouse.com/blog or follow us on LinkedIn https://www.linkedin.com/company/clickhouseinc/life/0c1ee7f4-2129-488d-b413-e7f6270659fd/?viewAsMember=true to find out more about what’s happening at ClickHouse.
EQUAL OPPORTUNITY & PRIVACY
ClickHouse provides equal employment opportunities to all employees and applicants and prohibits discrimination and harassment of any type based on factors such as race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
Please see here https://clickhouse.com/legal/applicant-privacy-notice for our Privacy Statement.
Location: CCA
THE ROLE
As a Forward Deployed Engineer at Wonderful, you’ll turn complex enterprise workflows into AI agents that work in the real world.
You’ll operate at the intersection of engineering, product, and customer delivery. Embedding directly with enterprise teams, you’ll uncover how their operations actually run, identify where AI can create meaningful value, and build the systems that deliver it.
You’ll lead projects from initial discovery through production deployment, combining customer insight with hands-on engineering. After launch, you’ll measure real-world impact and keep iterating until the solution delivers meaningful results.
This role is for versatile engineers who enjoy combining deep technical work with customer context. You’re comfortable entering unfamiliar environments, asking incisive questions, and shipping practical solutions without waiting for a perfect specification.
WHAT YOU’LL DO
- Embed with customers to understand their workflows, constraints, and measures of success.
- Turn loosely defined operational problems into clear technical plans and production systems.
- Design and build AI agents that integrate with customer tools, data, and business processes.
- Own deployments from prototype through launch, monitoring, and continuous improvement.
- Test with real-world data, measure business outcomes, and iterate based on evidence.
- Make pragmatic tradeoffs across architecture, reliability, speed, and user experience.
- Partner closely with Wonderful’s Product and Engineering teams to improve the core platform.
- Turn lessons from individual deployments into reusable tools, patterns, and best practices.
WHAT WE’RE LOOKING FOR
- 5+ years of experience building software or solving complex technical problems.
- Strong foundations in software architecture, system design, and production engineering.
- Experience working across APIs, integrations, data flows, and distributed systems.
- The ability to bring structure and momentum to ambiguous problems.
- Confidence working directly with customers, from operational teams to technical stakeholders.
- Clear communication, sound judgment, and a strong sense of ownership.
- Genuine curiosity about applied AI and its potential to transform how businesses operate.
NICE TO HAVE
- Experience in a forward-deployed, solutions engineering, consulting, or customer-facing technical role.
- Experience building AI agents, workflow automation, or conversational systems.
- Familiarity with LLM evaluation, observability, and reliability in production.
- Experience deploying and improving systems in complex enterprise environments.
Candidate Privacy Notice https://www.wonderful.ai/careers/candidate_notice
Location: Global
Talent is everywhere, opportunity is not. Sora Union changes that.
Sora Union
is a globally distributed professional services company that specializes in Design, Software Engineering, QA. Our experienced talent comes from communities where there is displacement or risk of displacement due to conflict or climate change. We provide services to global companies and start-ups across various industries, including healthcare, financial services, technology, and education.
We are seeking a Forward Deployed Engineer to join our growing team, where you will act as an internal entrepreneur, driving AI initiatives from ideation to production both internally and for our customers.
As a FDE, you will work closely with the Engineering , Product/Brand Design, and QA teams.
You'll be responsible for:
Customer-Facing AI Solutions: Act as the primary technical partner for customers, translating operational needs into production-grade AI experiences.
End-to-End Implementation: Own projects entirely, from data cleaning and prototyping to full deployment, monitoring, and debugging in customer environments.
Performance Optimization
:
Implement model compression, quantization, and efficient serving techniques to meet strict latency and throughput requirements for customer-facing applications.
Advanced Prompt Engineering & LLM Customization: Develop sophisticated prompt chaining, self-correction mechanisms, and context management strategies (e.g., using RAG architectures) to enhance LLM application performance and accuracy.
Ideally, you'll have:
AI/ FDE Development Experience: 3+ years of experience building and deploying production-level AI/ML models.
MLOps Tooling: Hands-on experience with MLOps platforms and tools such as MLflow, Kubeflow, or Weights & Biases for experiment tracking and model registry.
Technical Proficiency: Strong expertise in Python and deep learning frameworks (TensorFlow, PyTorch), along with experience in LLM orchestration frameworks (e.g., LangChain, LlamaIndex).
Data Engineering/API Skills: Proven ability to build and maintain high-performance, low-latency RESTful APIs (e.g., using FastAPI or Flask) for serving models, and strong proficiency in SQL/NoSQL databases for data integration.
Customer-Facing Experience: Proven ability to work directly with stakeholders to define requirements and deliver value, ideally in a consulting or specialized engineering role.
Deployment Expertise: Experience containerizing models (Docker) and deploying to cloud environments (AWS, GCP, or Azure).
Entrepreneurial Mindset: Ability to thrive in a fast-paced environment, taking initiative to solve ambiguous problems
Sora Union is committed to creating and fostering a diverse team. We encourage people from underrepresented backgrounds and all walks of life to apply. We are committed to providing reasonable accommodations to all applicants throughout the application process.
О ПРОЕКТЕ
Chrona agency ищет эксперта в инфраструктурную Web3-платформу, обслуживающую десятки тысяч блокчейн-нод в 120+ сетях (Ethereum, Solana, Cosmos и др.). Мы обеспечиваем 99.99% uptime для валидаторов и RPC-узлов, используя non-custodial модель.
ОСНОВНЫЕ ЗАДАЧИ
— Развертывание и эксплуатация блокчейн-нод различных типов (Validator, Archive, RPC).
— Обеспечение отказоустойчивости и минимального latency в геораспределенной инфраструктуре.
— Настройка мониторинга, алертинга и систем глубокой аналитики производительности.
— Автоматизация процессов обновления сетей и деплоя инфраструктурных компонентов.
— Работа с сетевой архитектурой (L2/L3) и оптимизация ресурсов кластеров.
— Применение SRE-практик для контроля SLA/SLO и планирования мощностей.
ТРЕБОВАНИЯ К КАНДИДАТУ
— Глубокий коммерческий опыт эксплуатации блокчейн-инфраструктуры.
— Экспертные знания Kubernetes в production-средах.
— Опыт работы с Terraform, Ansible и инструментами CI/CD (GitLab / GitHub).
— Уверенное владение стеком мониторинга: Prometheus, Grafana, Alertmanager.
— Глубокое знание Linux (Debian / Ubuntu) на системном уровне.
БУДЕТ ПРЕИМУЩЕСТВОМ
— Опыт работы с высоконагруженными RPC-сервисами.
— Понимание архитектур Proof-of-Stake (PoS) и механизмов консенсуса.
— Навыки построения отказоустойчивых кластеров в распределенной среде.
УСЛОВИЯ РАБОТЫ
— Полностью удаленный формат и отсутствие бюрократии.
— Выплаты в USDT согласно рыночной вилке.
— Возможность прямого влияния на архитектуру и масштабирование платформы.
— Работа в сильной инженерной команде с фокусом на результат.
Location: Auckland
Workplace: OnSite
ABOUT HALTER
At Halter, we’re on a mission to enable farmers and graziers to run the most productive and sustainable operations. Our customers are using Halter to break free from the time-intensive constraints of conventional practices. Imagine watching 500 cattle stand up and walk calmly towards their next break? No quad bikes, no dogs, no fences. Just a group of cattle walking at their own pace. People say it looks like magic. Our customers are revolutionizing grazing with Halter. It's changing lives and transforming an industry. People join Halter to do meaningful work. By joining us you’ll be solving challenging problems within a talented team and a culture built for high performance. Our team out-think, out-work and out-care. We’re committed to delivering real change in the world - this isn’t easy, and in truth, we love that it’s hard.
We’re backed to deliver on a mission that matters by Tier 1 investors including Founders Fund https://foundersfund.com, Bessemer Venture Partners https://www.bvp.com/, BOND, https://www.bondcap.com/ DCVC https://www.dcvc.com/, Blackbird https://www.blackbird.vc/, Promus Ventures https://www.promusventures.com/, Rocket Lab’s Peter Beck and Icehouse ventures https://www.icehouseventures.co.nz/?utm_term=icehouse%20ventures&utm_campaign=Brand+Keywords&utm_source=adwords&utm_medium=ppc&hsa_acc=4064636360&hsa_cam=16902737884&hsa_grp=134004309485&hsa_ad=592971340272&hsa_src=g&hsa_tgt=kwd-1082530126230&hsa_kw=icehouse%20ventures&hsa_mt=b&hsa_net=adwords&hsa_ver=3&gclid=Cj0KCQjw2v-gBhC1ARIsAOQdKY0J0DepRVFDmjQlAkJPbZuQnLSA5UVzUzOXYiPxkjX-SeVa513_BhkaAr-MEALw_wcB.
To find out more, visit our LinkedIn https://www.linkedin.com/company/halter-limited & Instagram https://www.instagram.com/lifeathalter/.
ABOUT THE ROLE
Hardware at Halter is truly unique. We design and build devices that are fitted to an animal, and must remain operational 24/7 for 6-10 years out in the field. To achieve this, we iterate and improve our products continuously, so a mechanical role at Halter can be quite diverse. We own our designs right the way through, from sketching how a device might fit on an animal, to testing in the lab to see how it might break, to spending time on the production line finding ways to improve the product. We like to do things quickly, no matter which phase of the design we're in, which makes the role fast-paced and adaptive. We're endlessly challenged by our farmers, our animals, and our lofty production targets; so there's never a dull day.
For the next stage, we need talented, disciplined mechanical engineers who know how to develop hardware. With plenty of new markets and revenue streams to unlock, there will be no shortage of exciting mechanical projects, all of which require problem solving, critical thinking, and the ability to execute to a high standard. These projects will offer ample opportunity for up-skilling, leadership, mentorship and career development. At Halter, our teams are small and agile, which means you get to work on the most important projects, and contribute to the company's success, whatever your role may be.
2027 will be Halter's biggest year yet, and this is your chance to be a part of it.
WHAT WOULD BE VALUABLE:
- Highly reliable device design.
- Experience developing robust products. E.g. automotive, agricultural or military.
- Exposure to the full product life cycle.
- Understand the challenges of outdoor hardware.
- Verification and validation.
- Designing, conducting and documenting high quality tests.
- Injection Molding:
- Experience designing complex injection molded parts, specifically overmolding.
- Experience in setting up contract manufacturers to produce high quality injection molded parts.
- Experience with tool commissioning at contract manufacturers.
- Design for Manufacture (DFM) and Design for Assembly (DFA):
- Designing and iterating parts and assemblies to make them easy to manufacture and easy to assemble.
- Designing for and selecting processes for high volume manufacturing.
WHAT YOUR DAY COULD LOOK LIKE
- High ownership and high accountability. You have to be committed to the mission and drive success for yourself, for the team, and for the organization.
- Rapid hands-on development delivering robust electro-mechanical products through to production.
- Time spent on the farm with our farmers, ranchers and animals. If you like cows, you'll love working in the mechanical team as we have a strong focus on ergonomic design.
- Collaborating with external suppliers to optimise designs and streamline manufacturing processes. We spend a lot of time at our suppliers in China and Thailand and we encourage our engineers to problem solve at the factory.
- Be part of, and contribute to, a high performance team. We want you to add to the culture and push growth within the team. We want drivers not passengers.
- We'll never lose our start-up culture, so you'll be rolling your sleeves up and helping with whatever is required to make our customers and cows happy.
OTHER REQUIREMENTS
- A Bachelor's Degree in Mechanical Engineering or a similar field is highly desired.
- 3+ years of professional experience ideally working on robust hardware.
- Capable with 3D CAD and 2D drafting, preferably using Solidworks or Onshape.
- Interested and available to travel for 10-20% of the year (negotiable).
OUR OFFICE FIRST APPROACH
There’s a reason you visit your friends in person, live with your family and don’t do dinners over Zoom. Humans are wired for connection. We believe a world-class, in-person office culture is the best way for high-performing teams.
We’re office first, not office only. This means working from the office everyday is our default setting, but we flex when we need to. We have a high-trust culture, so everyone is trusted to do what’s best for Halter.
JOIN OUR TEAM
Halter is committed to promoting a diverse and inclusive workplace — a place where we can each be ourselves and do the best work of our lives. Research shows that while men apply to jobs when they meet an average of 60% of the requirements, women and under-represented groups of candidates tend to only apply when they meet every requirement. If you think you have what it takes but don’t necessarily tick every requirement on this job description, please still get in touch and apply to Halter. We’d love to chat to see if you’ll be an epic fit!
If this opportunity sounds like you, please apply below by sending through your cover letter explaining why you’re excited about this role and working at Halter, along with your CV, and we’ll be in touch!
Location: London
Perplexity is looking for a Search Machine Learning Engineer Intern to help build the next generation of advanced search technologies, with a focus on retrieval and ranking. You will work closely with experienced engineers to improve search quality, experiment with new models, and ship features that directly impact how users search and discover information.
Internship program: 12 - 24 weeks, full-time, in-person in the London office.
Responsibilities:
- Contribute to experiments that improve search quality through better models, data usage, and evaluation tools, under the guidance of senior engineers.
- Design and implement components of the search platform and model stack, including retrieval, ranking, and classification models.
- Train evaluating models (including LLM-based approaches) for retrieval, ranking, and classification tasks.
- Support deployment and monitoring of search and ranking models in a scalable and performant way.
- Help build and iterate on RAG pipelines for grounding and answer generation.
- Collaborate with Data, AI, Infrastructure and Product teams to deliver improvements quickly and learn best practices in production ML.
Qualifications:
- Strong foundation in machine learning and statistics, with coursework or projects related to information retrieval, ranking, or recommender systems.
- Experience with Python and common ML frameworks (e.g. PyTorch, TensorFlow, JAX) through academic, open source, or personal projects.
- Familiarity with evaluating model quality using offline metrics and/or A/B testing is a plus, but not required.
- Previous experience (internships, research, or significant projects) working on search, recommendation, or NLP is a plus, but not required.
- Self-driven and curious, with a strong sense of ownership, willingness to learn, and comfort working in a fast-paced environment
- Experience with Rust will be a plus
СтажёрLondon
ГибридLondon
ГибридLondon
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.
seniorDenver, CO; Seattle, WA; Chicago, IL (Remote); United States (Remote);; We are happy to provide reasonable accommodations to candidates in need of individualized support during the
УдалённоColombia; Mexico; Argentina; Brazil; Costa Rica; Manage distributed teams across time zones with clear communication and structure
Jeddah, Saudi Arabia; Lusail, Qatar; Dubai, United Arab Emirates; Cairo, Egypt; Lahore, Pakistan; New Delhi, India
УдалённоСША; candidates interested in being located out of any Olsson office location, hybrid, or fully remote in various locations of the US
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