Careers

The role

Turn technical conviction into recurring revenue. You will own complex opportunities with robotics, autonomy and industrial teams, from first conversation through pilot conversion, negotiation and expansion. Working directly with the founders, you will build the enterprise sales playbook rather than inherit one. This is a hands-on closing role, with success measured in qualified pipeline, paid conversions and durable customer relationships.

What you'll do

• Own the full sales cycle: develop target accounts, qualify opportunities, map decision-makers and close new business.
• Build relationships with CTOs, engineering and data leaders; uncover the operational and financial cost of their current infrastructure.
• Agree pilot success criteria and a commercial decision process upfront, partnering with forward-deployed engineers on technical validation.
• Translate measured improvements in data availability, infrastructure cost and engineering effort into a defensible business case.
• Lead pricing, procurement and contract negotiations with the founders and counsel; manage renewals and account expansion.
• Maintain an accurate CRM and evidence-based forecasts; turn wins, losses and customer feedback into a repeatable sales process.

What you bring

• Typically, 5+ years selling complex B2B software, with evidence of closing multi-stakeholder enterprise deals and achieving revenue targets.
• Experience in infrastructure, data platforms, developer tools or AI; you can sell credibly to technical buyers without overstating capabilities.
• A record of converting pilots or proofs of concept into recurring contracts, including navigating security reviews and procurement.
• Early-stage ownership, disciplined qualification, strong negotiation skills and excellent English; comfortable working on site with customers.

Nice to have

An active network of robotics, autonomy or AI infrastructure buyers; a technical background; experience building a sales motion as an early commercial hire.

Why join

Own foundational customer relationships and shape how we sell. Work directly with the founders and engineers, with base salary, performance-based commission and equity.

The role

Build pipeline and close business with growing robotics and autonomy teams. You will own a defined portfolio from outbound and inbound discovery to demos, pilots, contracts and expansion. The senior Account Executive and founders will support complex opportunities, but this is a revenue-owning role, not a meeting-booking position. Your job is to keep good opportunities moving and help customers reach a clear buying decision.

What you'll do

• Research target accounts, identify engineering and data stakeholders, and run personalised outreach that speaks to their actual workflows.
• Qualify inbound interest from the website, developer community and events against customer needs, timing and buying readiness.
• Lead discovery and initial product demonstrations; bring in engineers when deeper technical validation is needed.
• Coordinate trials and pilots, maintain mutual action plans, and turn agreed success criteria into a clear proposal and close.
• Manage your pipeline, follow-ups, contracts and forecasts; own revenue targets for your accounts and identify expansion opportunities.
• Partner with community and communications on campaigns and events; share objections and use cases that improve our positioning.

What you bring

• Typically, 1-3 years in technical B2B sales, including direct closing responsibility and evidence of creating your own pipeline.
• A record of progressing opportunities through discovery, evaluation and negotiation, rather than handing them off after qualification.
• Curiosity about robotics, AI and data infrastructure; you can explain a technical product clearly and learn from engineers.

Nice to have

Experience with developer-led or open-source adoption, infrastructure software or robotics customers; familiarity with Attio or a comparable CRM.

Why join

Own deals end to end while learning directly from senior sellers, founders and engineers. Base salary, performance-based commission and equity, with room to grow into larger accounts.

The role

Build an engaged community around LatentWorlds and own our external communications. You will bring robotics engineers and researchers together while making our work understandable to journalists, partners and future hires. This is more than a social-media role: you own recurring programmes, public relations and launches, working directly with founders and technical teams to turn attention into meaningful participation and adoption.

What you'll do

• Build recurring community programmes: workshops, hackathons, meetups, office hours and collaborations with labs and open-source contributors.
• Own public relations: media outreach, press materials, interview preparation and enquiries; coordinate agencies and freelance specialists when needed.
• Run the editorial calendar across our website, newsletter and social channels; turn engineering and research work into accurate, accessible stories.
• Coordinate announcements and launches with the founders, securing technical validation and customer approval before publishing claims or stories.
• Deliver events end to end, including partners, budgets, speakers and follow-up; work with sales on relevant introductions without treating community as a mailing list.
• Measure participation, repeat engagement, developer activation and relevant coverage; manage sensitive communications and escalation with the founders.

What you bring

• Typically 3+ years in community, communications or technical marketing, with hands-on ownership of both community programmes and public relations.
• Strong English writing and editorial judgement; you can adapt a message for engineers, the press and a broader audience without losing accuracy.
• Evidence of running recurring events or communities and securing relevant media coverage, not only coordinating agencies.
• An organised, independent approach to budgets, vendors and deadlines; confidence working with founders and engineers, and availability for events and travel.

Nice to have

Experience with robotics, AI infrastructure or open-source communities; relationships with relevant journalists, technical creators, research labs or conference organisers.

Why join

Shape how LatentWorlds shows up in the world and build a community with genuine technical substance. Direct founder collaboration, competitive salary and equity.

The role

Make LatentWorlds work in customers' real environments. You will lead technical discovery, integration and deployment, staying hands-on from the first architecture discussion to a reliable production handover. This is a player-coach engineering role, not demo-only presales or project coordination. You own technical delivery and feed recurring customer needs back into the platform rather than accumulating one-off solutions.

What you'll do

• Map customer data flows, deployment constraints and integration points; turn them into a scoped architecture and acceptance plan.
• Write production-quality integrations, connectors and tooling across edge devices, ingestion, storage, retrieval and downstream workflows.
• Deploy and troubleshoot in cloud, customer-controlled and on-premise environments, including identity, networking, observability and upgrades.
• Lead pilots against agreed reliability, performance and cost baselines; give sales evidence for the commercial decision without owning the close.
• Coordinate technical delivery, mentor engineers and manage risks; document runbooks, rollback plans and operational ownership.
• Turn repeated deployment work into reusable platform capabilities, examples and automation, with disciplined feedback to core engineering.

What you bring

• Typically 3+ years building production software, including technical leadership and direct work with external customers or demanding internal users.
• Strong coding in Python and at least one systems language, ideally Rust; sound judgement across APIs, distributed systems and data pipelines.
• Hands-on Linux, containers, cloud networking and infrastructure automation; ability to diagnose failures across software and infrastructure boundaries.
• Clear communication with engineers and executives, pragmatic scope management and willingness to travel for integrations and critical deployments.

Nice to have

ROS 2, MCAP or multimodal sensor data; experience delivering enterprise data or ML platforms.

Why join

Own deployments that directly shape the product, not a separate services backlog. Work closely with customers and the founding team, with competitive salary and equity.

The role

Work on a focused research problem at the intersection of physical data and intelligent behaviour. Depending on your strengths, your project will centre on world modeling, hand motion tracking, video captioning or data annotation pipelines. You are not expected to be expert in all four. You will work with a research mentor, build reproducible experiments and connect your findings to real data and practical workflows.

What you'll do

• With your mentor, define a research question, reproduce relevant baselines and choose evaluation criteria before scaling experiments.
• Explore world models that learn temporal structure and action-conditioned dynamics from multimodal trajectories.
• Develop or evaluate hand motion tracking and reconstruction, including temporal consistency, occlusion and interactions with objects.
• Improve grounded video captioning, temporal segmentation or annotation pipelines, including uncertainty-aware quality checks and human review.
• Build clean datasets and evaluation splits; run ablations and analyse failure cases rather than relying on aggregate scores alone.
• Contribute tested research code, experiment records and technical reports; support publications or open-source releases where appropriate.

What you bring

• Current MSc or PhD study in machine learning, robotics, computer vision or a related field, or equivalent research experience.
• Strong Python and practical experience with a deep-learning framework such as PyTorch; comfortable training and evaluating models.
• Depth in at least one relevant area: generative or world models, 3D vision and tracking, vision-language models, or data-centric ML.
• Careful experimental reasoning, clear technical English and evidence of sustained research or engineering work through projects, code or papers.

Nice to have

Experience with egocentric video, geometry, multimodal temporal data, scalable annotation or robotic manipulation. Publications are welcome, not required.

Why join

Own a substantive project with close mentorship and a direct path from research to infrastructure or model improvements. Paid placement; scope, dates and duration agreed with you.

The role

Turn data requirements into predictable, quality-controlled delivery. You will coordinate people, partners, equipment, logistics and data handoffs, keeping programmes on schedule without letting quality slip. Research defines what data is useful; engineering defines how it is captured and processed; you make the operation run. Your measure of success is accepted, usable data delivered safely and efficiently, not simply recording volume.

What you'll do

• Translate collection briefs into staffing, capacity, schedules, budgets and acceptance criteria; track dependencies and delivery risks.
• Recruit, onboard and coordinate collection partners and operators; establish training, operating procedures, supervision and escalation paths.
• Coordinate equipment procurement, inventory, shipping, repairs and returns, working with specialist providers on cross-border logistics where needed.
• Align daily collection plans with technical readiness, maintenance and research priorities; work with technical leads to resolve downtime and recurring failures.
• Coordinate secure transfer, ingestion checks, metadata, review and rework; maintain traceability, consent and usage-rights records with relevant specialists.
• Track usable-data yield, rejection and rework, on-time delivery and cost per accepted unit; improve workflows while protecting safety and confidentiality.

What you bring

• Typically 5+ years leading complex operations, technical programmes or data delivery, with direct responsibility for people, vendors, budgets and deadlines.
• A record of building processes from scratch and coordinating distributed teams with consistent training, accountability and quality standards.
• Confidence using spreadsheets, dashboards and operational data to forecast capacity, investigate bottlenecks and make trade-offs.
• Strong English, practical judgement and meticulous follow-through; comfortable coordinating across time zones and travelling when operations require it.

Nice to have

Experience with robotics or sensor-data collection, annotation operations, equipment logistics or other workflows combining a physical operation with digital quality control.

Why join

Build the operational discipline that makes valuable physical data repeatable. Work closely with engineering and research, with broad ownership, competitive salary and equity.

The role

Build a robotics experimentation environment from the ground up, connecting hardware, control software, data capture and evaluation. Your priority is rigorous, end-to-end evaluation of learned manipulation policies on real robots, not curated demonstrations. You own technical readiness, safe execution and reproducibility; the Data Operations Lead owns collection scheduling, staffing and delivery. Together, you make experiments reliable enough to guide the next model iteration.

What you'll do

• Design and commission robotic workstations: robot hardware, end effectors, fixtures, sensing, compute, networking and serviceable layouts.
• Own software bring-up, drivers, control interfaces, calibration and sensor synchronisation; version hardware configurations alongside code.
• Integrate learned policies from observations to executed actions, including inference, action interfaces, latency budgets and execution monitoring.
• Build evaluation suites with held-out tasks, repeated trials and consistent resets; measure success, cycle time, interventions, recovery and failure modes.
• Establish operating limits, interlocks, emergency-stop procedures and staged validation with appropriate safety specialists before policy deployment.
• Automate logging and regression tests; link results to model, dataset and configuration versions, and hand maintainable procedures to operations.

What you bring

• Typically 5+ years in hands-on robotics or equivalent depth, including setting up and maintaining real manipulation systems from hardware to software.
• Strong Python and C++ or comparable systems programming; experience with Linux, robot middleware such as ROS 2, controls and calibration.
• Practical experience deploying and evaluating learned manipulation policies; you can distinguish model limitations from sensing, control or integration failures.
• Evidence of building reproducible experiments, diagnosing hardware/software faults and leading technical work with a rigorous approach to robot safety.

Nice to have

Teleoperation, imitation learning, reinforcement learning, vision-language-action policies, automated reset design or simulation-to-real evaluation. You speak Italian.

Why join

Shape an experimental system from its foundations and make real-world policy evaluation dependable. Close collaboration with research and platform engineering, competitive salary and equity.

The role

Build the platform foundations that keep physical AI data usable under real-world constraints. You will own systems that must stay correct through intermittent networks, large payloads, uneven load and failures across edge and cloud. The work spans low-level reliability and product-facing primitives: services, APIs and execution workflows that other engineers and customers can depend on. Scope is broad; ownership is concrete.

What you'll do

• Build resilient ingestion with durable buffering, resumable transfer, backpressure, acknowledgements and end-to-end integrity checks.
• Develop storage, indexing and retrieval primitives for time-aligned sensor streams, with measurable performance and predictable resource use.
• Design stable APIs, metadata models and workflow foundations for dataset versions, provenance and execution.
• Implement access control, tenant isolation, auditability and lifecycle controls as part of the platform architecture.
• Use profiling, load tests and failure injection to understand system behaviour; improve observability, recovery and operational runbooks.
• Own work from design to rollout, collaborate with customer-facing and ML engineers, and turn deployment lessons into reusable platform improvements.

What you bring

• Production experience building distributed systems that other engineers relied on, with a clear account of your own design and operational decisions.
• Strong working knowledge of Rust, including async programming, with experience writing maintainable systems code.
• Sound reasoning about consistency, retries, concurrency, failure recovery and correctness; disciplined API and data-model design.
• An ownership mindset, strong programming fundamentals and clear communication; you enjoy making ambiguous problems precise and shipping maintainable solutions.

Nice to have

Storage engines, transport protocols, performance engineering, multi-tenant infrastructure, robotics data formats or sensor time synchronisation.

Why join

Work on infrastructure where reliability and efficiency have visible consequences. Own substantial technical decisions alongside a small team, with competitive salary and equity.

The role

Own the console where engineers inspect data and operate physical AI workflows. This is a professional engineering tool, not a conventional dashboard: it must make large, time-based and spatial datasets understandable without sacrificing responsiveness. You will set the architecture and quality bar, work directly with users, and help build the team. Product judgement matters as much as technical depth.

What you'll do

• Lead console architecture and implementation, creating foundations that remain coherent as data volume and product capability grow.
• Build responsive views for sensor streams, timelines, spatial information and comparisons, enabling precise inspection of complex recordings.
• Make performance measurable: profile rendering, memory, loading and interaction latency, and resolve bottlenecks across browser and backend boundaries.
• Design expert workflows with users, from finding and inspecting data to configuring operations and understanding failures.
• Establish reusable interaction patterns, testing, accessibility and release standards; partner with platform engineers on effective APIs.
• Hire and mentor engineers while remaining hands-on; connect technical decisions to a clear and consistent product experience.

What you bring

• Substantial experience, typically 10+ years, building complex interactive software, including shipping an editor-class or comparably demanding professional tool.
• Deep web-platform knowledge and hands-on performance work across rendering, scheduling, memory and large-data interfaces.
• Graphics experience on the GPU, in the browser or natively, and the ability to choose rendering and data-handling approaches pragmatically.
• Strong architecture and technical leadership, including mentoring or hiring; clear communication and excellent judgement about tools used by experts every day.

Nice to have

Rust or WebAssembly, 3D or media visualisation, robotics and sensor data, or experience with design tools, IDEs, CAD or game-engine editors.

Why join

Shape the product surface through which users experience the entire platform. Own both craft and architecture, work closely with the founders, and receive competitive salary and equity.

The role

Build the learning loop that turns robot recordings into measurable policy improvements. You will own applied research and engineering across dataset design, training and evaluation, working closely with platform engineers and robotics leads. This is not a paper-only role: the output is a reproducible loop that runs. The foundry lead owns the experimental hardware environment; you focus on learning methods, datasets and what the results mean.

What you'll do

• Define collection tasks, coverage and instrumentation requirements that produce useful training and evaluation data, including failures and recovery.
• Build dataset construction and quality-control pipelines with episode boundaries, metadata, provenance and reproducible versions.
• Implement and train baseline and improved models from multimodal trajectories; investigate data quality, representation and learning objectives.
• Design evaluations that expose generalisation limits and regressions, with controlled comparisons and clear links between data changes and outcomes.
• Work with robotics leads to deploy and test policies, separating model failures from sensing, control and integration issues.
• Improve platform retrieval, exports and processing through real training workloads; maintain tested code and communicate results, assumptions and next experiments.

What you bring

• Depth in robotics or machine learning, ideally PhD-level or equivalent practical research experience, with hands-on work on real robots.
• Experience training models on multimodal data and diagnosing failure modes through careful experiments rather than trial and error alone.
• Strong Python and modern deep-learning tooling; ability to write production-quality research and data-processing code.
• A rigorous approach to evaluation and reproducibility, clear English communication, and comfort working across research, hardware and platform engineering.

Nice to have

Manipulation learning, world models, imitation or reinforcement learning, ROS 2, sensor synchronisation, data-centric ML or automated robot evaluation.

Why join

Influence how physical data is collected, represented and used to improve robot behaviour. Work across the full learning loop with substantial ownership, competitive salary and equity.

The role

Build a finance function that gives the founders a clear view of cash, commitments and the choices ahead. You will own planning, reporting, controls and the coordination of external finance providers, while supporting fundraising and cross-border operations. This is a hands-on role: you will improve the model, establish a reliable close and decide what to automate, outsource or bring in-house as the company grows.

What you'll do

• Own cash forecasting, runway, budgeting and scenario planning, connecting headcount, infrastructure spend and commercial milestones.
• Establish a dependable monthly close and management pack; reconcile operating metrics with financial reporting and explain variances.
• Maintain the financial model, unit economics and customer cost-savings analysis for pricing and investment decisions.
• Coordinate bookkeepers, accountants, payroll providers and tax advisers; manage multi-entity reporting and corporate-structure work with counsel.
• Support fundraising, diligence and investor reporting; keep financial records, the data room and equity-administration processes organised.
• Build proportionate controls for expenses, procurement, invoicing, collections and contracts; strengthen finance operations without slowing the business.

What you bring

• Experience leading finance at a venture-backed technology company, including building processes during early growth and supporting equity fundraising.
• Hands-on financial modelling, cash management and reporting; you have personally built models and run a close, not only reviewed others' work.
• Experience with cross-border entities and external advisers; confidence coordinating accounting, tax, payroll and legal specialists.
• Clear communication with founders and investors, strong commercial judgement, and a relevant accounting qualification or equivalent practical experience.

Nice to have

Swiss, Italian, US and Dutch structures; infrastructure software or robotics economics; hardware procurement, pilot-based revenue or international expansion.

Why join

Shape the finance function directly with the founders. Work on consequential operating decisions through a fractional engagement, with scope, retainer and any equity participation agreed upfront.