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Distributed Systems EngineerSan Francisco, CA (Onsite)About the CompanyA fast-moving AI research group is building the core video data infrastructure used by leading AI labs and major tech companies. The team is small at around fifteen people, nearly all engineers, and recently pivoted to focus exclusively on high-quality video data at massive scale. The shift has driven significant revenue growth, and they are now planning to expand the team steadily over the next few months.The culture is straightforward: engineering led, product focused, low ego, and built around people who enjoy ownership. They work in person five days a week in their San Francisco office, moving quickly, solving hard problems, and avoiding micromanagement.The RoleThis position focuses on designing and scaling distributed systems that support huge ML and ETL workloads across petabytes of video. You will own core infrastructure: compute scheduling, orchestration, throughput, reliability, cost efficiency, and the internal tooling that keeps the entire engineering group moving at pace.The company is beginning to scale its infrastructure footprint aggressively, and this role will become central to that growth. It is a hands-on IC position suited to someone who has operated critical systems before and wants to shape the foundation of a rapidly expanding platform.What You’ll Work On• Architect and scale distributed systems for large-scale ML and ETL workloads• Build compute orchestration and scheduling across thousands of GPUs• Improve uptime, resilience, and execution speed of high-volume data pipelines• Design pipelines capable of handling petabyte-level video datasets• Lead the development of CI/CD and internal tooling for fast iteration• Partner closely with research engineers delivering new video models and algorithms• Operate in a high-trust environment with strong autonomy and clear ownershipRequirements• 3+ years building foundational distributed systems or data infrastructure• Experience running critical systems at significant scale• Proficient across cloud architectures• Strong coding experience with Go (preferred) and Python• Background building or maintaining large-scale pipelines• Experience with ML-focused CI/CD and automation• Video domain experience is not required• Operates as a strong IC who leads through action• Fully onsite in San Francisco, Monday to FridayCulture Fit• Enjoys ambiguity, problem discovery, and self-direction• Communicates clearly and concisely• Shows strong intellectual curiosity• Low ego, collaborative mindset• Motivated by building core systems in a small, high-caliber teamRed flags include weak communication, low curiosity, or unclear motivation for the domain.Interview ProcessIntro call focused on culture, curiosity, and communicationTechnical discussion on background and complexity of past workProblem-solving session with a research engineerOnsite research problem and collaboration exercise

Senior Computational Materials ScientistAbout the CompanyA global energy-technology organization developing next-generation Li-Metal batteries for electric mobility across automotive, aviation, and advanced energy applications. This team integrates modern machine learning directly into materials R&D, cell design, manufacturing workflows and safety analytics, operating across major hubs in North America and Asia.About the Advanced Computation DivisionThis group serves as the company’s core AI and computational science unit. It brings together computational materials scientists, software engineers and machine learning researchers working hand-in-hand with experimental chemists and product engineers. The team builds intelligent scientific tooling, accelerates materials discovery and supports fast iterative R&D.About the Molecular Discovery PlatformThe company’s flagship platform for AI-accelerated materials discovery analyzes more than 10^8 small molecules across quantum-level, ML-derived and experimentally curated properties. Leveraging GPU-accelerated simulation, large-scale automation and advanced visualization, it enables rapid navigation across vast chemical space.About the RoleThe team is seeking a Senior Computational Materials Scientist to contribute to the development of this platform while advancing simulation capabilities for electrolyte systems, solid electrolyte interphase (SEI) modeling, reaction network methods, force field development and large-scale molecular dynamics acceleration on modern HPC infrastructure.You will collaborate across computation, software, AI and experimental groups to develop tools that connect quantum chemistry, statistical mechanics and machine learning for practical molecular design.Key ResponsibilitiesDesign and execute large-scale quantum chemistry and molecular dynamics simulations using industry-standard tools (e.g., GPU4PySCF, GROMACS, LAMMPS, Gaussian).Develop and refine force fields and interatomic potentials for electrolyte-relevant chemistries.Build and improve simulation workflows for SEI formation, including reaction network analysis and atomistic modeling.Contribute to property-calculation workflows covering key quantum descriptors (HOMO, LUMO, ESP), thermodynamics and kinetics.Automate high-throughput simulation pipelines using Python, HPC schedulers (e.g., SLURM) and distributed compute environments.Integrate new simulation capabilities into the broader molecular discovery platform through APIs or modular Python packages.QualificationsRequiredPhD in Materials Science, Chemistry, Chemical Engineering, Physics or a closely related discipline5+ years of post-PhD experience in computational chemistry or computational materials scienceHands-on experience with major molecular simulation packages (GROMACS, LAMMPS, Gaussian, VASP, Quantum Espresso, ADF, GPU4PySCF or similar)Strong Python skills, including scientific libraries (NumPy, ASE, PySCF etc.) and experience writing reproducible research-grade codeExperience with high-throughput computation and large-scale data workflows on HPC or GPU clustersStrong communication skills and comfort working across experimental, computational and AI teamsPreferredExperience with battery materials, electrolyte systems or solid/liquid interface modelingBackground in force-field development, reactive MD (Polarizable FF, ReaxFF, MLFF) or coarse-grained simulationFamiliarity with cheminformatics concepts (molecular representations, fingerprints, exploration of chemical space)Contributions to open-source simulation frameworks or published methodology papersExperience with unsupervised learning methods (dimensionality reduction, clustering beyond k-means)Exposure to CUDA or GPU-accelerated codingWho Thrives HereYou enjoy working at the intersection of chemistry, physics, ML and large-scale computationYou’re comfortable challenging the limits of standard computational toolsYou have a natural curiosity for molecular behavior, electrolyte chemistry and computational designYou prototype quickly, iterate thoughtfully and value reproducible scientific workflowsYou like building tools that turn raw simulation output into interactive, research-ready platforms

AI Project Lead – Berlin (Hybrid)Salary: €70,000–€90,000 + BonusHybrid: 3 days per week in our Berlin office, travel to client site 2-3 times a monthWe are looking for a Client-Facing AI Project Lead to join a fast-growing, highly profitable consultancy at the forefront of applied artificial intelligence. Join a team of 30 friendly nerds who work with corporates, NGOs, Mittelstand companies, and scale-ups to create meaningful AI breakthroughs - from fast-paced MVPs to large-scale transformations.Please Note: This is NOT an engineering role. This is a Project Management and Leadership role focused on client delivery, stakeholder management, and driving exponential value. You will be supported by an expert technical team.What You’ll DoBe obsessed with achieving an actual AI breakthrough with the client and delivering exponential value.Lead fast-paced AI projects from inception to complete integration, ensuring alignment with defined goals and scope.Act as the core point of contact for our clients, driving efficient collaboration across functions and organizational borders.Build trust and maintain strong relationships with stakeholders at all levels (The "charm" factor!).Contribute to a growing, high-impact company and help shape its culture and direction.What We’re Looking ForProject Management Expertise: At least 2 years of experience successfully managing projects from start to finish, with a focus on delivering tangible value (ideally in consulting or a related field).High Processor Speed: Incredibly fast in anticipating, analyzing, and solving problems; able to understand technical basics and use tools effectively.Strong Communication: Excellent verbal and written communication skills; ability to lead workshops and confidently handle numbers.Language Skills: Ability to communicate effectively in German (speaking, writing) is required.Academic Foundation: A technical background (Bachelor’s or Master’s) is highly valued.Soft Skills: Demonstrable ability to deal with ambiguity ("See it. Say it. Sort it!") and build lasting trust.Ideally, You Also BringUnderstanding of and experience in AI projects and Machine Learning.Familiarity with project management methodologies such as Agile.High proficiency in both German and English (C1 level or higher).Willingness to travel to client sites 2–3 times per month across Europe.What We OfferAscension: Opportunity to do the best work of your career with significant autonomy and real impact in a key leadership role.Captivating AI Projects: Engage with high-impact projects that offer ample room for experimentation, continuous learning, and growth.Top-Tier Compensation: We offer top-of-market pay for this AI Project Lead role.Professional Environment: Flexible work environment based on trust, collaboration, and our innovative “No rules rules” philosophy.Supportive Culture: Family-friendly policies, flexible hours, and an active commitment to diversity, inclusion, and Female Empowerment (mentorship and leadership support).

Product Engineer – AI-Driven Materials & Battery Simulation Platform About the CompanyA leading energy-technology firm advancing next-generation battery materials and intelligent energy systems. The team is at the forefront of applying modern machine learning to materials discovery, molecular simulation, and high-performance battery development. Their AI-enhanced Li-Metal and Li-ion platforms are among the first to incorporate electrolyte materials discovered through data-driven scientific methods, enabling progress across mobility, energy storage, robotics and aerospace. What You Can ExpectStrong compensation and benefits, including meaningful equity in a fast-scaling public company.The chance to contribute to an ambitious scientific mission focused on accelerating the transition to cleaner global energy systems.A collaborative workplace where AI, computational science and advanced battery R&D converge.Significant career growth opportunities working alongside top researchers, engineers and domain experts.Role OverviewThe company is seeking a Product Engineer to design and lead an AI-driven molecular simulation and materials informatics platform supporting the development of next-generation battery materials.You will connect advanced AI model architectures with computational chemistry, molecular dynamics (MD) and phase-field simulation. This role centers on building and scaling the scientific computing stack that powers materials discovery and battery R&D across the organization.You will take early-stage AI4Science capabilities — from ML force fields and surrogate models to automated MD pipelines — and turn them into reliable, developer-friendly APIs and internal platforms. Key ResponsibilitiesPlatform and ArchitectureLead the full architecture and delivery of a scientific computing platform that unifies AI models, simulation tools and experimental data.Build and optimize high-performance simulation services in C++ for large-scale MD, phase-field and related materials models.Define and evolve platform interfaces and APIs that expose simulation, data and ML services to internal users.AI-Driven Simulation and AutomationDevelop and operationalize AI/ML models for materials informatics, including ML force fields, surrogate modeling and uncertainty-aware pipelines.Build scalable MD automation systems that manage large batches of simulations, including scheduling, monitoring and data capture.Convert cutting-edge research prototypes into production-grade simulation and AI services.Battery R&D IntegrationCollaborate closely with scientists and experimental teams to translate R&D requirements into practical platform features.Develop simulation tools supporting analysis of dendrite behavior, degradation pathways and electrolyte/material performance.Ensure seamless integration between simulations, experimental workflows and analytics systems.Core CompetenciesExpertise in C++ and scientific/high-performance computingExperience with HPC environments and parallel computing (MPI, CUDA, GPU acceleration, or similar)Strong knowledge of MD simulations and associated toolingAPI engineering and scalable software/platform architectureUnderstanding of battery materials informatics and AI4Science workflowsExperience building automated MD workflows and simulation pipelinesHybrid background across scientific computing and modern software engineeringMinimum QualificationsPhD in Materials Science, Computational Physics, Computational Chemistry or a similar field.At least 1 year of post-graduate experience in computational materials science, including MD or phase-field simulation.Proven ability to build production-grade scientific software in C++ or related systems languages, ideally in HPC environments.Hands-on exposure to AI/ML for materials modeling (ML force fields, surrogate models, automated ML workflows).Experience developing APIs, services and platforms for use by engineering or scientific teams.Strong grounding in algorithms related to materials behaviour (dendrite formation, transport, microstructure evolution).Demonstrated ability to work directly with experimentalists and domain scientists.Preferred QualificationsExperience developing or scaling AI4Science platforms unifying simulation, ML and laboratory/experimental data.Background with cloud-native scientific computing (Kubernetes, containers, workflow engines).Prior exposure to battery R&D (Li-metal, Li-ion, electrolytes, interfaces) and multiscale modeling.Experience leading product or platform engineering initiatives within deep-tech or research-heavy environments.Familiarity with modern data/ML stacks such as Python, PyTorch/JAX/TensorFlow, model registries and workflow orchestration tooling.

Agentic AI Architect / ML Scientist Location: Boston Massachusetts Type: Full time I am representing a deep tech organisation building an AI powered materials discovery platform. Their system integrates advanced model architecture with computational chemistry and large scale simulation. The company has strong financial backing, over 200 million USD in liquidity, and partnerships with leading automotive and energy companies, giving real-world impact to its technology.About the platform At the heart of the company’s work is a high-dimensional system that maps and predicts molecular behaviour at scale. It combines physics-informed models, learned representations, and automated simulations to accelerate discovery of next-generation battery and electrolyte materials. This system also supports agentic reasoning, interpretable predictions, and causal insights, allowing the platform to guide scientific exploration autonomously.What you will work onDesign and develop foundation models and agentic AI systems for scientific applicationsApply multimodal reasoning and causal inference to molecular and materials datasetsBuild interpretable models with next-generation explainability tools for scientific MLDevelop representation engineering approaches to improve model generalisation and accuracyWork closely with chemists, physicists, and engineers to translate scientific challenges into ML solutionsContribute to experiments that validate and benchmark AI predictions in real-world materials discoveryMentor and collaborate with team members across levels to share best practices in AI researchWhat you bringStrong background in ML, foundation model design, or AI research applied to scientific domainsExperience in molecular simulation, materials science, or physics-informed MLKnowledge of agentic AI, causal reasoning, multimodal reasoning, or interpretable ML techniquesFamiliarity with large datasets in chemistry, materials, or battery sciencesAbility to communicate complex AI concepts to scientific and technical teamsResearch mindset with curiosity for building models that can reason and act autonomously

Senior Machine Learning Engineer (m/f/d)Join a mission-driven tech team applying cutting-edge AI to the recycling and waste management sector. They’re developing intelligent systems to optimize material detection, sorting, and process efficiency. Making industrial operations smarter and more sustainable. We're looking for a Senior Machine Learning Engineer with strong experience in Machine Learning to help design and deploy advanced models in production environments.What You’ll DoDevelop and deploy ML solutions for image and time-series data (e.g. object detection, anomaly detection, forecasting)Design scalable algorithms and integrate them into real-world systemsStay on top of the latest AI research and apply new technologies (e.g. Deep Learning, LLMs)Lead code reviews, mentor junior engineers, and promote development best practicesMonitor and continuously optimize models in productionWhat We’re Looking For4+ years of experience in CV (e.g. CNNs, YOLO) and time series (e.g. LSTM, Transformers)Strong Python/C++ skills and experience with ML frameworks (e.g. PyTorch, TensorFlow, OpenCV) and Robotics frameworks (ROS1/ROS2)Experience working with Sensors for real-world applications.Proven record of building and deploying real-world ML applicationsSolid math and data analysis skillsFluent in English and German; strong communication and leadership abilitiesWhat We OfferA key role in shaping AI products in an innovative fieldFlat hierarchies, creative freedom, and an agile environmentA diverse, interdisciplinary team and flexible working optionsModern office space and participation in company success (e.g. VSOP)Salary Budget: €80 - 95k (Dependant on Experience)

MLOps Engineer – Munich (Hybrid) Salary: €100,000 Hybrid: 3 days per week in our Munich office We are seeking an MLOps Engineer to join a pioneering company building technology that makes AI models more efficient, accessible, and sustainable. Our mission is to democratize AI - reducing its environmental impact while empowering people to do more with less. You’ll join a collaborative, research-driven environment where engineers, scientists, and product experts work together to push the boundaries of efficient machine learning. What You’ll DoDevelop and maintain a scalable SaaS cloud platform for model compression and benchmarking.Build and optimize backend services and responsive, user-friendly interfaces.Manage and improve our R&D cluster, including AWS-based compute infrastructure for ML experiments and development.Collaborate closely with ML researchers, engineers, and product teams to ensure seamless workflows and robust system performance.Support the go-to-market team by experimenting with new tools and solutions for the ML community.What We’re Looking ForStrong understanding of machine learning algorithms and MLOps principles.Proficiency in Python, C++, or Java.Experience with infrastructure-as-code tools (Terraform, CloudFormation, etc.).Expertise in cloud platforms and containerization technologies (e.g., Docker, Kubernetes).Experience designing and managing CI/CD pipelines and automated deployments.Strong communication skills and ability to collaborate across teams.A proactive mindset with ownership over projects and results.Bonus PointsExperience with deep learning frameworks (e.g., PyTorch, TensorFlow).Contributions to open-source MLOps or ML infrastructure projects.What We OfferMeaningful work at the intersection of AI and sustainability.Comprehensive benefits, including meal vouchers, wellness programs, mobility support, and a remote work stipend.Collaborative culture built on trust, inclusion, and continuous learning.Transparent and fair hiring process designed to be flexible and accessible to all candidates.Our ValuesDecide Wisely: Data-driven, customer-focused decision-making.Trust by Default: Open communication and mutual respect.Foster Inclusion: A diverse, supportive workplace where everyone belongs.Grow Together: Continuous feedback and shared learning.Learn Relentlessly: Adaptability and curiosity in a fast-moving field.Apply now to help shape a more efficient, sustainable future for AI.

AI/ML Engineer – Berlin (Hybrid) Salary: €70,000–€90,000 + Bonus Hybrid: 3 days per week in our Berlin office We are looking for an AI/ML Engineers to join a fast-growing consultancy at the forefront of applied artificial intelligence. Join a team of 30 engineers and innovators works with NGOs, Mittelstand companies, and scale-ups to create meaningful AI breakthroughs - from fast-paced MVPs to large-scale transformations. What You’ll DoShape and deliver fast-paced AI projects that move from proof-of-concept to production-ready MVPs.Build data pipelines, design and run ML workflows, and develop and deploy scalable web services.Collaborate with clients to integrate solutions into their systems and drive real business impact.Work across diverse sectors — from corporates and scale-ups to NGOs and the public sector.Contribute to a growing, high-impact company and help shape its culture and direction.What We’re Looking ForStrong experience building scalable software systems in a professional setting.Hands-on experience implementing AI/ML solutions in production environments.Solid technical foundation in Python and modern software engineering practices.Ability to deal with ambiguity, find practical solutions, and deliver high-quality results.Strong communication skills and ability to interact with clients in German (B1 level or higher).Ideally, You Also BringExperience with data science tools (e.g. pandas, matplotlib, scikit-learn).Experience working with large language models (OpenAI, Claude, etc.).Knowledge of front-end development and/or Docker.Experience integrating web services with SAP.Willingness to travel to client sites 2–3 times per month.What We OfferOpportunity to do the best work of your career with autonomy and real impact.Challenging and meaningful AI projects with room for growth and experimentation.Professional yet flexible environment built on trust, collaboration, and curiosity.Family-friendly policies, flexible hours, and commitment to diversity and inclusion.Equal opportunities and active support for women in tech through mentorship and leadership programs.