Summary An innovative quantum technology company is looking for a Quantum Success Engineer to support customers using advanced quantum control hardware and software. This role combines technical troubleshooting, customer onboarding and training, and relationship management. You will help researchers integrate quantum control systems into their experiments, resolve technical challenges and ensure they get the most from the technology, while sharing customer feedback with internal engineering and product teams. Responsibilities Customer onboarding and training: Support hardware installation, setup and integration, delivering technical training both onsite and remotely. Technical support: Troubleshoot customer issues involving quantum control systems, helping experimental research teams overcome technical challenges. Customer relationships: Build strong relationships with customers, respond to concerns and support customer satisfaction and long-term retention. Customer advocacy: Gather customer feedback and communicate insights to product and engineering teams to inform improvements and future development. Cross-functional collaboration: Work with internal technical and commercial teams to resolve issues and improve the overall customer experience. Requirements A PhD in experimental physics involving microwave or radio-frequency experiments, or a Master's degree in experimental physics with 1–2 years of relevant industry experience. Familiarity with Python programming. An understanding of electronics and experimental physics; experience with quantum computing is highly advantageous. Experience with embedded systems through academic projects or professional work is desirable. Strong problem-solving skills and a proactive, customer-focused approach. Excellent communication skills, with the ability to explain technical concepts clearly and professionally. Previous industry experience and/or experience in a customer-facing technical role is advantageous. Professional fluency in English. Benefits and opportunity Hybrid working: Three days in the office and two days working remotely. Generous annual leave: 30 days of paid holiday, in addition to national holidays. Competitive compensation: Attractive base salary and a 14% employer pension contribution. Company equity: Opportunity to participate in the company's long-term success through Stock Appreciation Rights. Relocation support: Relocation package and visa sponsorship for international hires and their families. Cutting-edge technology: Work at the forefront of quantum computing, supporting researchers and experimental teams worldwide. Career development: Collaborate with physicists, engineers and developers in a growing quantum technology business.

Summary An innovative deep-tech company developing next-generation quantum computing systems is seeking a Software Manager / Senior Software Manager to lead the team responsible for the software that controls and operates its hardware. With systems already deployed with customers, the company is focused on building a reliable, production-grade software platform that integrates quantum technology with existing HPC, GPU and data-centre infrastructure. This role combines software architecture, technical leadership and people management, with ownership of the platform, roadmap and customer-facing reliability. Responsibilities Technical leadership: Own the architecture and evolution of the low-level software stack, ensuring reliable integration with compute, networking, security and data-centre infrastructure. SDK and APIs: Lead the development of developer tools and APIs for hybrid quantum-classical applications. Team management: Lead, mentor and develop software engineers, setting priorities, standards and resource plans. Roadmap and delivery: Prioritise features and upgrades in collaboration with commercial, customer-facing and engineering teams. Performance and reliability: Improve latency, throughput, uptime and recovery in collaboration with hardware and optical engineering teams. Engineering quality: Establish best practices across testing, CI/CD, code reviews, release management, observability and incident response. Customer support: Lead technical escalations and root-cause analysis, ensuring issues are resolved effectively. Cross-functional collaboration: Promote documentation and shared ownership, and communicate technical progress to senior leadership. Requirements 10+ years of experience building and shipping production software, including leading engineering teams. Experience with HPC systems and/or large-scale data-centre infrastructure. Strong Python and C++ and/or Rust skills, with solid Linux systems knowledge. Experience with hardware-integrated software, such as real-time systems, instrument control, embedded software or FPGA integration. Strong engineering practices across testing, CI/CD, releases, monitoring and root-cause analysis. Experience supporting deployed customer systems and communicating calmly under pressure. Strong problem-solving, decision-making and prioritisation skills. A degree in Computer Science, Electrical Engineering, Physics or a related quantitative discipline, or equivalent experience. Desirable: Quantum computing, quantum control systems or scientific instrumentation. Digital signal processing, data acquisition, timing or synchronisation. Experience in high-reliability sectors such as semiconductors, telecommunications, medical devices, defence or aerospace. Experience scaling deep-tech products from R&D into commercial deployment. Benefits and opportunity Work on advanced quantum computing technology with real-world customer deployments. Shape the architecture, roadmap and reliability of a growing software platform. Combine technical decision-making with team leadership and development. Collaborate across software, hardware and optical engineering. Help bring next-generation computing technology into modern AI and HPC environments. Competitive salary and the opportunity to make a meaningful impact in an ambitious deep-tech business.

Research Scientist / Engineer, Inference San Francisco | Permanent DeepRec has partnered with a frontier AI research lab that designs its own model architectures from the ground up. Serving cost is treated as a research question here, so inference sits at the centre of the work rather than the end of it. The Opportunity You'll own latency and throughput across two serving stacks. One handles production traffic for customers. The other powers test-time compute and RL rollouts for the research team, so every gain you make speeds up the research itself.   What You'll Do Cut latency and raise throughput for model serving at very high concurrency Speed up RL rollout generation and scale test-time compute for research Tune batching, caching, load balancing and parallelism across the serving stack Write and profile GPU kernels in CUDA and Triton Apply quantization, distillation, speculative decoding and low-precision numerics Shape model and hardware co-design with serving cost in view from day one Own benchmarking, testing and reliability for every inference service What You'll Bring Essential Production experience with vLLM, TensorRT-LLM or similar at high concurrency Hands-on continuous batching and KV cache management Quantization for inference in production Profiling and performance analysis with CUDA and Triton Desirable Speculative decoding or multi-node serving Performance tuning on H100 or B200 hardware Kubernetes and production infrastructure We encourage you to apply even if you don't meet every requirement. The right mindset matters as much as the right CV.     Apply Now If you've spent your career making models fast, this is a place where that work shapes the research agenda. Send your CV and we'll share the full brief in a confidential conversation

Research Scientist / Engineer, Pre-training San Francisco | Permanent DeepRec has partnered with a frontier AI research lab building new model architectures, not fine-tuning someone else's. Pre-training is the foundation every product and post-training effort builds on, and the team concentrates on a handful of large training efforts rather than spreading thin. The Opportunity You'll run controlled experiments on large models and let the data settle the arguments. You'll have the compute to test real hypotheses at scale, plus room to lead your own projects alongside the flagship runs. What You'll Do Research model architecture, training algorithms, optimisers and data pipelines Lead small projects independently while contributing to flagship training runs Design scaling-law experiments that set data, architecture and hyperparameter choices Scale training across thousands of accelerators with sound fault tolerance Build the dev tooling that keeps the research team moving quickly Work across the stack, from kernel throughput to high-level model design Design for downstream serving cost as well as model quality What You'll Bring Essential MS or PhD in CS, ML or a related field PyTorch distributed training, including FSDP and Megatron-style tensor or pipeline parallelism Debugging loss spikes, divergence and throughput regressions at scale Building and balancing data mixtures and tokenization pipelines Desirable Publications at NeurIPS, ICML, ICLR or similar venues FP8 or other low-precision training Custom CUDA or Triton kernels, or SSM-style and other non-standard architectures We encourage you to apply even if you don't meet every requirement. The right mindset matters as much as the right CV.   Apply Now If you want your experiments to shape the models themselves, we'd like to hear from you. Send your CV and we'll share the full brief in a confidential conversation.

https://www.gorovex.com/ Rovex Technologies Corporation Senior Autonomy Engineer - Robotics On-siteFull time Gainesville, Florida, United States OverviewApplication   Description About Rovex Rovex is building autonomous robots that help hospitals operate more efficiently so healthcare professionals can focus on what matters most: patient care. Our robots automate routine tasks such as patient transportation, logistics, and environmental monitoring, enabling healthcare systems to improve efficiency while enhancing the patient experience. We're a fast-growing robotics startup bringing together experts in robotics, AI, and healthcare to solve real-world problems. Our team works hands-on across hardware and software, rapidly iterating from prototype to deployment in close collaboration with hospital partners. If you're excited about building complex robotic systems, taking ownership, and seeing your work deployed in the real world, we'd love to hear from you. About the Role We are looking for a hands-on Senior Autonomous Robotics Engineer to help productionize and scale Rovex's autonomy stack as we deploy robotic fleets into dynamic, high-stakes hospital environments. This is a senior individual contributor and mentorship role. You'll work closely with our existing autonomy team to make key technical decisions, improve system architecture, and help build reliable, production-ready autonomy systems. Your work will bridge the gap between core software algorithms and physical execution, accelerating Rovex's path from early deployments to commercial scale. We are specifically looking for someone who has successfully deployed autonomous mobile robots in commercial environments at meaningful scale. The ideal candidate has helped bring 25+ autonomous robots into commercial operation and has firsthand experience solving the reliability, navigation, and operational challenges that emerge after robots leave the lab. Key Responsibilities Technical Leadership & Vision Help shape Rovex's autonomy roadmap, make key architectural decisions, mentor existing autonomy engineers, and guide the team toward reliable, production-ready systems. Production Autonomy Architecture Architect and deploy robust autonomy software that maximizes hardware performance while emphasizing reliability, maintainability, and observability in dynamic hospital environments. Complex Navigation & Edge Cases Solve challenging autonomy problems beyond basic point-to-point navigation, including crowded hallways, elevators, doorways, temporary obstacles, localization degradation, and other real-world deployment scenarios. Fleet Reliability & Diagnostics Develop logging, telemetry, health monitoring, and diagnostic tools that enable rapid failure analysis, remote support, and reliable fleet operations. Safety & Hardware Integration Design fault-tolerant autonomous systems and collaborate closely with software, electrical, mechanical, and systems engineers to ensure safe, dependable operation around patients and healthcare staff. Requirements Desired Education & Experience Bachelor's, Master's, or PhD in Robotics, Computer Science, Electrical Engineering, Computer Engineering, Mechatronics Engineering, or a related technical field (or equivalent industry experience). Typically 5+ years of professional experience developing autonomous robotic systems in industry. Experience deploying autonomous mobile robots in commercial environments, ideally including responsibility for fleets of 25+ robots operating successfully in the field. Demonstrated experience solving real-world autonomy challenges involving navigation, localization, reliability, and field debugging after deployment. Strong technical leadership skills with experience making architectural decisions while remaining a hands-on engineer. Passion for solving real-world robotics problems and building technology that directly improves hospital operations and patient care. Comfortable working in a fast-paced startup environment with a strong sense of ownership.   Technical Skills Production Robotics Proven experience building reliable autonomy systems and debugging complex field failures in commercial deployments. Autonomy Expertise Deep technical strength in one or more core autonomy disciplines such as localization, navigation, perception, planning, or safety, with practical experience deploying systems in real-world environments. Platforms & Tooling Strong proficiency in C++, Python, Linux, and ROS/ROS2, along with simulation and hardware-in-the-loop testing platforms. Reliability & Diagnostics Experience using logging, telemetry, and diagnostic tools to identify, reproduce, and resolve complex issues across deployed robotic fleets.   What We're Looking For Has successfully brought autonomous robots from development into commercial operation. Prioritizes shipping reliable, production-ready systems over impressive demonstrations. Builds maintainable, observable systems and avoids one-off fixes whenever possible. Comfortable working across software, sensors, controls, electrical, and mechanical systems to solve complex robotics challenges. Excellent communicator who enjoys mentoring teammates and collaborating across engineering disciplines. Excited by the opportunity to own difficult technical problems and help accelerate the commercialization of healthcare robotics. Benefits Base Salary: $140,000–$200,000, commensurate with experience. Equity: Eligible for stock options. Paid time off and company holidays. Opportunity to take technical ownership of mission-critical autonomy systems. Work alongside a world-class robotics team solving meaningful real-world healthcare challenges. Help shape the future of autonomous robotics in healthcare from an early-stage company.

Senior Data Mesh & Governance Consultant Contract | Fully Remote | Europe | Up to €850/day We are looking for a Senior Data Mesh & Governance Consultant to support a global data and AI transformation programme within a highly regulated environment. The project involves adapting an existing global data governance framework and data foundation to meet the needs of a specific business domain. Key requirements: 7+ years’ experience in data mesh, data governance or data architecture. Experience working across federated, global data environments. Strong understanding of enterprise data governance frameworks and data foundations. Familiarity with Databricks, Snowflake, AWS and Azure. Comfortable working with senior stakeholders and translating strategy into practical solutions. Previous experience in a technology consultancy or regulated environment is advantageous. Contract details: Fully remote across Europe, with Eastern Europe preferred. Full-time freelance contract through to the end of September. Up to €850/day, depending on location and experience. Immediate start, with availability before the 2 November kickoff preferred.

Senior AI Engineer – AI Agents & Automation ? Greater Boston, MA – On-site Monday - Thursday, Friday is work from home day ? Full-time ? Reporting to: Managing Partner   About the Firm Our client is a leading private equity firm with a strong track record of building and scaling high-quality businesses. The firm combines investment expertise with hands-on operational experience, and is now looking at how AI can transform the way its own teams operate and create value across the business.   The Opportunity   We're looking for a highly hands-on AI Engineer to take ownership of building and deploying internal AI capability. This is not a strategy, advisory, or people-management role — it's a builder role. You'll work directly with senior leadership and employees across the firm to understand how work is currently performed, identify opportunities for automation, and build AI agents and applications that remove repetitive work. An example: understanding how an investment associate monitors portfolio companies, then building an AI-powered system to automate the research, data collection, analysis and reporting involved. Initially your focus will be the firm's management company and a small, close-knit team. Longer term, there's significant potential to expand AI capabilities across the firm's portfolio companies — for someone who delivers, there's no predefined ceiling on this role.   What You'll Do   Work directly with senior leadership on bottlenecks and repetitive processes Translate business problems into clearly defined technical solutions Design, build and deploy production-grade AI agents and applications Build agentic workflows involving reasoning, retrieval, data processing and interaction with internal systems Integrate LLMs with existing applications, documents, databases and third-party platforms Build retrieval/knowledge systems (RAG) for internal company information Implement evaluation, monitoring and observability for AI systems in production Design human-in-the-loop processes where full automation isn't appropriate Establish controls around data access, permissions and sensitive information Measure impact — time saved, adoption, productivity gains   The initial focus will be automating management company finance, including:   Accounts receivable, payment matching, collections and exception handling. Management fee calculations, invoicing and reconciliations. Expense management and transaction coding. Month-end close and management reporting. Cash forecasting, budgeting and financial analysis. Controls, approvals, monitoring and audit trails around automated workflows.   You’ll work with existing systems including QuickBooks, Ramp, Allvue and Chronograph, taking solutions from initial business requirement through to production.   What We're Looking For   Strong software engineering skills, ideally with significant Python experience Experience building production applications using LLMs (OpenAI, Anthropic, or similar) Experience building AI agents and multi-step agentic workflows RAG, embeddings, semantic search, vector databases API development, backend/service architecture Cloud infrastructure (AWS/Azure/GCP) and containerization (Docker) Comfort designing reliable systems around non-deterministic AI models A builder mentality: you'd rather ship a working prototype than write a deck about what could be built Comfort operating with significant autonomy and ambiguity Strong communication — able to explain technical concepts to non-technical senior stakeholders   Experience with LangGraph, LangChain, LlamaIndex or similar is useful, but we care more about your ability to design robust systems than any specific framework.   Why This Role   This is a rare opportunity to build an AI function from the ground up, with direct access to senior leadership and no legacy platform to inherit. The initial mandate is focused — deliver measurable value for the management company — but the trajectory is open-ended, with real potential to extend into the firm's wider portfolio!   A couple of important requirements: this is an on-site role in Waltham, MA, and the firm is unable to provide visa sponsorship. Candidates must therefore already have unrestricted US work authorization as either a US Citizen or Green Card holder and be able to work on-site in Waltham   Please apply with your resume for more details   We look forward to hearing from you

Machine Learning Engineer – Reinforcement Learning & Simulation Location: San Francisco, CA Working Arrangement: Full-time, office-based Compensation: $120,000–$220,000 base salary + equity About the Opportunity We’re partnering with an ambitious, well-funded AI startup working at the intersection of machine learning, reinforcement learning, simulation, and robotics. The company is building infrastructure to train, evaluate, and improve next-generation AI models, combining advanced simulation environments with substantial real-world robotics infrastructure. Having established a significant operational foundation, the team is now focused on scaling the engineering systems that enable reinforcement learning environments to be developed, tested, and deployed at pace. This is an opportunity to join a small, exceptionally driven technical team at an early stage, with significant ownership over core systems and the chance to help shape engineering standards as the company grows. The Role We’re looking for a strong Machine Learning Engineer with excellent technical fundamentals and an interest in reinforcement learning, simulation, and AI systems. Your primary focus will be scaling the production of reinforcement learning environments, turning research requirements into robust, efficient, and maintainable software systems. You’ll work closely with researchers to build the infrastructure needed to run simulations at scale and support the training and evaluation of advanced AI models. This is a highly engineering-focused role. You won’t necessarily need to develop novel reinforcement learning algorithms or have an extensive robotics background. Instead, we’re looking for someone who can build excellent software, solve difficult technical problems, and learn new concepts quickly. For more experienced candidates, there is also scope to take on greater technical ownership, mentor other engineers, and help establish the engineering practices that will support the team's next phase of growth. What You’ll Be Doing Build, scale, and productionise reinforcement learning environments used to train and evaluate advanced AI models. Translate research ideas and experimental requirements into reliable, high-performance engineering systems. Develop infrastructure to run simulation environments efficiently and at scale. Improve software quality, maintainability, testing, and engineering standards across the team. Collaborate with research colleagues to identify which environments and approaches deliver measurable improvements in model performance. Support model post-training, evaluation, and benchmarking where appropriate. Help validate simulation results through real-world model evaluation and testing on robotic systems. Identify opportunities to improve performance, scalability, and the efficiency of development workflows. Take ownership of technical challenges in a fast-moving environment where priorities can evolve quickly. What We’re Looking For The team places significant emphasis on technical ability, problem-solving, learning velocity, and ownership rather than a rigid checklist of previous experience. You’ll ideally bring: Strong software engineering fundamentals and the ability to build clean, reliable, production-quality systems. A strong general technical background, with an interest in machine learning, AI, or related disciplines. Excellent analytical and problem-solving skills. The ability to learn unfamiliar technologies and technical concepts quickly. A practical, hands-on approach to engineering, with the initiative to take projects from concept through implementation. High levels of ownership, adaptability, and intellectual curiosity. The motivation to work closely with a small, ambitious team tackling technically challenging problems. Experience in one or more of the following would be advantageous: Machine learning engineering or research engineering. Reinforcement learning and simulation environments. Production ML systems or large-scale software infrastructure. GPU-accelerated computing and simulation. Model training, post-training, or evaluation. Robotics and embodied AI. A background in robotics is not essential. The priority is strong software and AI capability rather than a purely mechanical, electrical, or controls-focused background. Candidates with a bachelor's or master's degree, a PhD, or equivalent practical experience are all welcome to apply. Exceptional early-career engineers will be considered alongside more experienced candidates. The Technical Environment The team is working with modern AI training and simulation technologies, including GPU-accelerated simulation and model post-training frameworks. Technologies discussed include: Python and modern software engineering tools. Reinforcement learning and simulation workflows. GPU-accelerated simulation, including Newton and MuJoCo Warp. Model post-training tools, including Tinker. Model evaluation, benchmarking, and performance optimisation. The precise stack is flexible. Strong underlying engineering ability and the capacity to pick up new tools quickly are more important than prior experience with every technology listed. Why Join? Work at the frontier of AI. Contribute to the environments and infrastructure used to train and evaluate increasingly capable AI models. Build at meaningful scale. Work with a company that combines simulation-based development with substantial real-world robotics infrastructure, allowing models and environments to be evaluated beyond purely theoretical settings. Take ownership early. Join a small technical team where your work will have a direct impact on the product, engineering standards, and future direction of the business. Work closely with research talent. Collaborate with highly technical colleagues to turn research ideas into scalable, production-ready systems. Help shape the engineering culture. Play a meaningful role in raising software quality and establishing practices that support the next stage of growth. Grow with an ambitious business. Join at an early stage, with competitive compensation, equity participation, and the opportunity to take on increasing technical responsibility. Working Environment This is a full-time, office-based role in San Francisco. The team values close collaboration, fast iteration, high ownership, and a strong commitment to delivering results. The environment is intense and best suited to people who enjoy working hard, tackling difficult problems, and learning rapidly alongside ambitious engineers and researchers. Candidates should be comfortable with a demanding startup environment and a high level of commitment to the work. Compensation The salary range for this position is $120,000–$220,000 base salary, plus equity, depending on technical ability, experience, and the scope of the role. Interested? If you’re a strong ML engineer who wants to build the infrastructure behind next-generation AI systems, we’d love to hear from you. Whether you come from a traditional software engineering background, ML engineering, research engineering, or a related technical discipline, we’re interested in people who combine excellent fundamentals with the ability to learn quickly and deliver high-quality work.