Jobs at Almetra

Design and adapt vision-language and video models for scene understanding, temporal reasoning, and action recognition. Build GPU-based training and evaluation pipelines, curate video-text datasets, develop benchmarks, optimize models through compression and distillation, and deploy production-ready inference systems. Collaborate with computer vision, platform, robotics, product, and customer teams to translate research into usable AI products.

Deploys and supports AI edge systems at industrial customer sites. Responsibilities include installing cameras, compute nodes, networking equipment, and hardware cabinets; configuring devices; validating connectivity and edge-to-cloud data flow; automating installation and diagnostics with scripts; troubleshooting hardware, network, and software issues; coordinating logistics; and ensuring reliable, safe, high-performance installations.

Own customer AI onboarding from initial execution through go-live and continuous improvement. Validate camera and input data quality, identify edge cases, maintain datasets and SOPs, track success metrics, communicate blockers, and coordinate installation teams to ensure reliable, consistent deployments. Improve onboarding workflows through documentation, checklists, templates, and tool enhancement recommendations. The role requires structured execution, strong communication, process discipline, technical systems comfort, and preferably manufacturing or process experience.

Support AI software onboarding by executing onboarding cycles, checking camera and input-data quality, documenting edge cases, tracking success metrics, communicating blockers, improving SOPs and tools, and coordinating with installation teams to ensure reliable, consistent deployments.

Analyze manufacturing and production data to identify performance drivers, bottlenecks, anomalies, and optimization opportunities. Build dashboards, reports, data pipelines, features, and quality metrics while collaborating with customers, AI and backend engineers, Product, and Customer Success. Translate operational insights into improvements for customer outcomes and the company’s AI analytics platform. Occasional travel to manufacturing plants is required.

Own provisioning and operations for a distributed fleet of Linux-based edge devices, cameras, and sensors. Build PXE-based deployment and configuration automation, manage monitoring, patching, diagnostics, networking, VPNs, and firewalls, and define fleet reliability standards. Support installation engineers through deployment-ready equipment, documentation, and troubleshooting. The role is based in Berlin, involves up to 50% travel to customer sites, and may require lifting equipment weighing over 30 kg.

Lead R&D for industrial robotic manipulators, including modeling, planning, control, perception, machine learning, simulation, and hardware integration. Develop and test robotic prototypes, planning algorithms, middleware, software architectures, pose estimation, segmentation, and autonomous grasping systems. Deploy and validate solutions using ROS-compatible hardware, sensors, robot arms, and real-world environments.

Develop and maintain backend features, APIs, data pipelines, and infrastructure for a scalable platform. Improve database performance, reliability, and real-time processing; debug and optimize systems for low latency. Collaborate with AI, frontend, and product teams, contribute to architecture decisions, and take ownership of backend problems. The role also involves cloud environments, Linux performance tuning, orchestration, and hybrid edge/cloud architectures.

Support AI software onboarding for manufacturing customers by executing onboarding cycles, validating camera and input data quality, documenting edge cases, tracking success metrics, coordinating with installation teams, and improving processes, documentation, checklists, and internal tools. The role requires structured execution, clear communication, attention to detail, ownership, and comfort working with technical systems. Manufacturing or process experience is advantageous, while prior machine learning experience is not required.

Develop and deploy computer vision models for video and sensor applications, building scalable training, evaluation, inference, and MLOps pipelines. Manage GPU clusters, Docker/Kubernetes environments, cloud workloads, CI/CD, and model orchestration. Collaborate with research, robotics, and platform teams to productionize reliable computer vision systems for cloud and edge deployment, including real-time inference optimization and industrial automation applications.

Own the day-to-day finance function for a Series A AI company, including investor reporting, controlling, month-end close, forecasting, budgeting, cash runway planning, dashboards, AP/AR, and vendor payments. Coordinate with external accountants, maintain German GAAP compliance, support junior staff and interns, and improve finance processes while partnering closely with founders and investors.

Partners with Sales, Product, Engineering, and Improvement teams to win and expand manufacturing customers. Leads discovery, maps factory workflows, identifies bottlenecks, translates operational challenges into AI use cases, supports pilots and deployments, quantifies ROI, and develops repeatable value-selling playbooks. The role requires expertise in continuous improvement, Lean, operational excellence, or industrial engineering, along with manufacturing operations experience and the ability to communicate effectively with shop-floor and executive stakeholders.

Support AI software onboarding by executing onboarding cycles, monitoring success metrics, checking camera and input-data quality, documenting edge cases, maintaining datasets and process documentation, communicating blockers, and coordinating with installation teams. The role focuses on reliable process execution, continuous improvement, and cross-station consistency in a manufacturing environment.

Design and maintain AWS infrastructure with Terraform, manage Kubernetes clusters, and own CI/CD pipelines. Improve developer experience, observability, monitoring, logging, alerting, and CDN performance. The role requires strong Linux, networking, storage, database, and configuration-management skills, with opportunities to support ML infrastructure, GPU workloads, model deployment, and MLOps.

Lead full-cycle, six-figure enterprise sales across Europe and North America. The Account Executive will build relationships with manufacturing leaders, manage complex multi-stakeholder deals, conduct discovery, negotiate legal and security reviews, drive account expansion, maintain CRM hygiene, forecast accurately, and consistently meet quota. The role partners with SDRs, Growth, Product, Customer Success, Engineering, and company founders while helping develop a repeatable enterprise go-to-market playbook.

Own customer onboarding from initial execution through post-launch iteration. Validate camera and input data quality, identify edge cases, maintain datasets, document process variance, track success metrics, and communicate progress and blockers. Improve onboarding workflows through checklists, documentation, templates, and tool feedback. Coordinate with installation teams to ensure camera setups support reliable, consistent AI onboarding across stations.

Build Almetra’s marketing function from the ground up, owning positioning, messaging, go-to-market strategy, demand generation, ABM, content, events, partnerships, metrics, and reporting. The role partners closely with founders and sales leadership, establishes repeatable revenue-generating marketing motions, and gradually builds and leads the marketing team as the company scales.

Drive continuous improvement initiatives for manufacturing customers using AI-powered computer vision insights. Analyze production data and assembly processes, identify inefficiencies, recommend measurable improvements, train customer teams, guide implementation, track outcomes, and collaborate with engineering, data science, product, and sales teams. Apply Lean and CI best practices while helping develop scalable AI-enabled improvement methods.

Own customer onboarding outcomes by executing and improving onboarding cycles, validating data quality, documenting edge cases, tracking success metrics, and communicating progress and blockers. The role coordinates with installation teams to ensure reliable camera setups and consistent results, while improving checklists, documentation, templates, processes, and tools. Candidates should be detail-oriented, metrics-minded, technically comfortable, and experienced in structured execution roles such as implementation, QA, solutions engineering, operations, or data operations.

Identify and contact manufacturing prospects across Europe, engage operations, production, and quality leaders, qualify leads, and book meetings for Account Executives. Partner with AEs on pipeline, messaging, and market feedback while helping develop the company's go-to-market playbook. The role requires B2B sales experience, strong communication, organization, initiative, and interest in AI, robotics, or manufacturing technology.