Senior/Staff Robotics Engineer
About the job
- A Ph.D. in Robotics, Mechanical Engineering, Electrical Engineering, Computer Science, or a related field, with a strong emphasis on robotics.
- A minimum of 1-2 years of experience in robotics research or development.
- Proven experience in modeling, planning, and controlling hybrid dynamical systems for robotic manipulation.
- Hands-on experience with machine learning techniques applied to robotic manipulation tasks.
- Experience with robotic perception technologies and deep learning frameworks as applied to manipulation.
- Strong programming skills in C++ and Python, with familiarity with ROS (Robot Operating System).
- Experience with simulation tools such as Nvidia Isaac Sim, Gazebo, V-REP, and CUDA for robotic manipulation.
- Proficiency with machine learning libraries such as TensorFlow or PyTorch.
- Fluency in English is mandatory.
- Lead R&D efforts to prototype a new robotic manipulator, conducting rigorous testing to validate design specifications and performance criteria.
- Work with industry-standard hardware platforms, including ROS-compatible robots and specific sensor suites, to develop and deploy robotic manipulators for real-world testing.
- Develop and implement models for hybrid dynamical systems exhibiting both continuous and discrete dynamic behaviors in robotic manipulators.
- Design advanced planning algorithms to optimize manipulation tasks such as pick-and-place operations.
- Apply supervised learning, unsupervised learning, and reinforcement learning techniques to improve manipulation performance in robots.
- Train reinforcement learning models in simulated and real-world environments with continuous action and state spaces.
- Design and develop middleware and software solutions tailored for robotic manipulation applications.
- Optimize software architecture for efficient communication between sensors, processors, and actuators in robotic manipulators.
- Develop perception algorithms for object pose estimation, matching, and instance segmentation to support manipulation tasks.
- Use deep learning techniques for end-to-end and self-supervised grasping to enhance autonomous robotic manipulation capabilities.
- Integrate hardware components, including tactile sensors, force sensors, vision systems such as RGB-D cameras, and depth sensors, to optimize communication protocols and data flow for robotic operations.
About the company
Almetra mounts AI cameras on production lines to turn shop-floor video into real-time operational data such as cycle times, output, utilization, and micro-stoppages, with edge processing and privacy-by-design anonymisation. It runs computer-vision analytics on-device and combines those insights with MES/PLC/ERP context and input from continuous-improvement engineers to produce actionable metrics, not just dashboards. The company differentiates itself through its focus on edge processing, privacy, and close collaboration with engineering teams to drive ongoing productivity improvements. Its goal is to help manufacturers diagnose root causes of inefficiency and raise output, supported by expansion plans in the US and growth funding.
Company Size
51-200
Company Stage
Series A
Total Funding
$22.4M
Headquarters
Berlin, Germany
Founded
2022
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Simplify's Take
What believers are saying
- June 25, 2026 Series A raised €16.3 million from blisce/ and NAP.
- Almetra plans U.S. expansion and robotics features, broadening revenue beyond analytics.
- Simplify lists 13 open roles in August 2026, signaling aggressive hiring.
What critics are saying
- If Bosch or Siemens bundles similar tooling, Almetra loses standalone necessity.
- US factory rollouts require long enterprise pilots, delaying payback and burn reduction.
- If privacy scrutiny tightens, shop-floor cameras become a liability before scale.
What makes Almetra unique
- Almetra's edge is edge-processed shop-floor video, anonymized locally, preserving worker privacy.
- It converts camera feeds into cycle times, stoppages, and utilization without MES integrations.
- Bosch, Siemens Energy, and Google DeepMind Accelerator validate manufacturing and robotics relevance.
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Benefits
Stock Options
Flexible Work Hours
Hybrid Work Options
Growth & Insights and Company News
6 month growth
3%1 year growth
-3%2 year growth
1%Berlin startup Almetra, formerly Deltia, has raised $19 million in a Series A round led by blisce/. NAP, Merantix Capital, Robin Capital, Underline Ventures, and Critical Ventures also joined, along with undisclosed individual investors. Almetra mounts cameras over factory floors and uses algorithms to track cycle times, output rates, and brief stoppages in real time. Customers include Bosch, Siemens Energy, ABB, Grundfos, and Continental's Aumovio division. At a Bosch e-bike battery line in Hungary, shift output rose 19% over four months. Viessmann's plant in Poland reported a 20% productivity gain. The company will use the funds to expand in the US and build tools that help factories respond to problems, not just detect them. It raised a €4.5 million seed round in early 2024 and has more than 40 employees.
Berlin-based Almetra, formerly known as Deltia, has raised €16.3 million in a Series A round led by blisce/, with participation from NAP, Merantix Capital, Robin Capital, Underline, Critical Ventures and business angels. The manufacturing intelligence company addresses factory inefficiencies through a platform combining video, machine data, IT systems and operator knowledge. AI-powered cameras installed above production lines process video locally, converting it into structured production data including cycle times, output rates and equipment utilisation, without requiring IT integration. The platform anonymises video footage and retains most data on-site to protect worker privacy. Almetra claims factories can identify optimisation opportunities within weeks. The funding will support product development, US expansion and development of automation capabilities, including robotics applications for production environments.
Romanian-founded firm Almetra raises $19M Series A led by blisce. Berlin-based Almetra, formerly known as Deltia, has raised a $19 million in a Series A round led by Blisce, with participation from NAP, Merantix, Robin Capital, Underline Ventures, and Critical Ventures, as Vestbee was told. * Founded in 2022 by Maximilian Fischer and Silviu Homoceanu, the company builds an AI-powered computer vision platform that helps factories monitor and improve production in real time. * Its system uses privacy-preserving cameras on shopfloors to convert raw video into structured operational data such as cycle times, machine stoppages, throughput, and utilization, reducing reliance on manual time studies and fragmented systems like MES or ERP. * The data is processed locally, anonymized, and used to create a live model of factory operations that AI analyzes to detect inefficiencies, identify root causes, and prioritize improvement actions for engineering teams. * Customers include Bosch, Siemens Energy, and ABB, with reported productivity gains of roughly 15 to 20% and faster cycle times in deployed environments. Details of the deal. * The new funding will support expansion into the US, faster product development, and the evolution of Almetra into a broader intelligence and automation layer for factory operations, integrating video, machine, and operational data into a unified system that delivers continuous, real-time insights for manufacturers.
Germany-based Deltia.ai, a startup enhancing warehouse picking processes with AI and computer vision, has secured $4.8M in seed funding. Cavalry Ventures led the round, with participation from Merantix. The funds will support operational and growth initiatives. Deltia.ai's platform uses AI to analyze and improve manual shop floor operations, converting processes into digital formats to identify inefficiencies. Notable investors include Nico Peters, Willi Tscheschner, and Max Viessmann.
Deltia.ai has expanded its seed funding by €4.5 million. The company plans to use the funds to accelerate customer onboarding, enhance AI capabilities for processing, and integrate customer IT system data. Additionally, they aim to expand their product reach to more factories over the next 18-24 months by increasing their Go-to-Market team.