Machine Learning

We are supporting a large-scale digital and AI transformation initiative and are looking for a mid-level Data Engineer with strong Azure and Databricks expertise, combined with real-world experience delivering GenAI and agentic AI solutions into production environments.This role is ideal for someone who is hands-on, engineering-focused, and already using modern AI-assisted development workflows as part of their day-to-day work.What You’ll Be Doing:Build, optimize, and maintain production-grade data pipelines on AzureDevelop and support GenAI and agentic AI solutions that are actively used in live environmentsWork with Azure Databricks, Spark, and Delta Lake on scalable, business-critical workloadsBuild backend services and APIs in PythonIntegrate Azure AI capabilities including Azure OpenAI, Azure AI Search, and Azure AI FoundryCollaborate with cross-functional engineering and AI teams to deliver reliable, scalable solutionsUse AI-assisted and agentic development tools as part of daily engineering workflowsWhat We’re Looking For:Around 5 years of experience building and operating production data platforms and pipelinesProven experience delivering GenAI or agentic systems on Azure beyond proof-of-concept stageStrong hands-on experience with:Azure OpenAIAzure AI SearchAzure AI FoundryAzure DatabricksSparkData LakeStrong Python engineering skills, including APIs and backend servicesPractical, day-to-day usage of AI coding assistants and agentic development tools such as:GitHub CopilotClaude CodeCursoror similar platformsFluent English communication skillsNice to HaveExperience working in enterprise-scale cloud environmentsExposure to MLOps or AI platform engineeringFamiliarity with modern software engineering and CI/CD practicesThis profile has to be based in Europe.

We’re working with a well-funded deep-tech company building next-generation AI sensing systems for deployment in complex real-world environments. They’re looking for a Machine Learning Engineer / Applied ML Scientist to help develop and deploy advanced ML models for real-time inference on edge devices. The company operates at the intersection of AI, sensing, embedded systems, and intelligent autonomy, with applications spanning industrial, robotics, environmental, and next-generation sensor platforms. This is a highly technical role suited to someone who enjoys taking ideas from research through to deployment in production systems. The Role You’ll work across the full ML lifecycle - from data processing and model development through to optimisation and deployment on constrained hardware. Typical projects may include:Developing deep learning models for real-world sensor dataBuilding low-latency inference pipelines for edge devicesOptimising models for deployment (quantisation, pruning, compression, distillation)Designing ML systems for noisy or dynamic environmentsWorking closely with hardware, embedded, and systems engineersPrototyping and evaluating new ML architectures and approachesContributing to production ML infrastructure and deployment workflowsWhat They’re Looking ForStrong experience with Python and modern ML frameworks (PyTorch and/or TensorFlow)Experience developing and deploying ML models in production environmentsBackground in one or more of:Edge AIEmbedded MLReal-time inferenceAudio / signal processingSensor fusionComputer visionTime-series modellingUnderstanding of performance optimisation for constrained systemsFamiliarity with Docker, Linux, cloud infrastructure, or MLOps toolingStrong mathematical and problem-solving skillsNice to HaveExperience with on-device AI or ultra-low-power inferenceBackground in robotics, autonomous systems, defence, healthcare, or industrial AIKnowledge of quantisation / pruning / TinyML techniquesExposure to C , embedded systems, or hardware-aware ML optimisationResearch background (PhD/MSc) in ML, signal processing, robotics, physics, or related fieldsWhy Join?Work on genuinely cutting-edge AI systems with real-world deploymentSmall, highly technical engineering teamSignificant ownership and influence over technical directionStrong funding and long-term product visionOpportunity to work closely with leadership on next-generation AI productsLocation: Munich - Onsite Compensation: Highly competitive equity potential depending on experience

Staff Agentic AI Engineer / AI Engineer $200,000 - $250,000 San Francisco, CA Onsite, 5x per week in office Full time / Permanent Most "agentic AI" roles are still research projects dressed up as products.This one isn't. The agent is live, in production, handling real workflows for Tesla, BMW, Meta, and Amazon. You’ll be in the codebase from day one, improving an agent that's already shipping, not starting from a blank page.This company builds AI-powered automation for mechanical engineers. Think Claude Code, but for CAD, CAE, and PLM workflows. $32M raised, backed by Eric Schmidt and early investors in Anthropic and OpenAI. Over 1,000 customers running production workflows on the platform.They're hiring a Staff Engineer to own the agent intelligence layer, the system that takes an engineer's intent and executes it reliably across complex desktop software. What you'd own:Evals infrastructure and agent benchmarking - defining what "good" looks like for a domain with no established benchmarkAgent harness build-out and ongoing performance improvement (task success rate, token efficiency, workflow coverage)Architecture decisions: tool-calling strategy, state management, context handling, model routing, error recoveryTechnical leadership of a small team of AI engineers - player-coach, not pure manager The profile they're looking for:Proven expertise building agentic systems into production. Systems that take real actions - tool-calling, multi-step state, failure handling, cost constraints. Ideally 2 yearsStrong on evals: task completion, failure mode analysis, regression detectionProduction-first mindset - you'd rather ship 70% coverage reliably than demo a clever system you can't measureBuilders over researchers. Too much academic background is a flag here Desktop automation experience is nice-to-have. Mechanical engineering background is nice-to-have. Experience taking agentic systems into production is the bar.

Machine Learning Engineer – Speech Model Training $250,000 - $300,000 San Francisco, CA Hybrid, 3x per week in office Full time / Permanent In this role you won’t be wrapping APIs or fine-tuning existing models. You’ll be building models across raw acoustic signal processing all the way through to production inference on edge devices. At a company that actually ships to 1.5M live users. A profitable, fast-growing AI company ($250M ARR in under three years, no VC dependency) is standing up a SpeechLLM lab from scratch. This is a founding seat on that team. They build a hardware-software AI companion used daily by over 1.5 million professionals worldwide. The next chapter is a world-class speech intelligence core and they need the engineers to architect it. What you'd own:Design and train large-scale speech models end-to-end. Unified SpeechLLMs, ASR, expressive TTS, generative audioOwn the full stack from acoustic feature engineering to GPU cluster optimisationRun and optimise distributed training at scale via PyTorch or JAX, FSDP, DeepSpeed, etcDrive real-time inference performance with vLLM, TensorRT-LLM, or SGLangApply RL alignment techniques to improve conversational qualityDebug the hard problems in distributed infrastructure and ship solutions You likely have:Proven experience training large-scale audio or speech models from the ground upDeep PyTorch or JAX expertise with real distributed training experienceGenuine comfort traversing the entire ML stack from signal processing to productionA bias toward shipping: you take ownership, you iterate fastStrong bonus: neural audio codecs, diffusion/flow-matching architectures, or LLM pretraining experience. Why joinProfitable company at ~$250M run rate - you'll see the impact of your work immediately in a product used daily by professionals worldwideDirect ownership of the live speech quality stack, not a supporting role in a large orgHybrid San Francisco team with real access to large, diverse, multilingual audio datasetsShort feedback loops - improvements ship fast and metrics are visibleClear path toward senior technical leadership as the audio team grows

AI Knowledge Graph Lead Remote (USA) up to $220,000 baseWe’re partnering with an AI-driven technology company looking to hire an AI Knowledge Graph/ Ontology Lead to build and scale the knowledge graph layer underpinning a new generation of intelligent enterprise products. This is a senior, hands-on leadership role for someone who has real experience designing and shipping production knowledge graphs, not just conceptual ontology work. You’ll be responsible for shaping a graph and ontology platform that powers: • AI retrieval and RAG workflows • Entity linkage and reasoning systems • Cross-domain and temporal knowledge modeling • Regulatory and compliance intelligence products • Agentic AI applications The role combines architecture, hands-on engineering, and team leadership. You’ll work closely with AI/ML engineers to turn complex, unstructured information into structured, queryable intelligence that directly feeds live AI systems. Key experience includes: • Strong Neo4j and Cypher expertise in production environments • Deep ontology / taxonomy modeling experience • Python engineering skills • Knowledge graph integration with LLMs, RAG, or vector search systems • Experience balancing formal semantics with pragmatic implementation • Ability to lead technically while remaining hands-on Additional experience in areas such as RDF/OWL, inference engines, entity resolution, legal/regulatory data, ESG, healthcare, or pharmaceutical domains would be highly valuable. The company offers: • A highly technical AI environment • Significant ownership and architectural influence • Fast decision-making and direct access to leadership • Strong adoption of AI-assisted development tooling • Flexible working arrangements and competitive compensation Ideal for someone excited by the challenge of building the intelligence layer behind complex AI products at scale. Please apply for more details

AI Data Engineer-  HealthTech AI  Up to $180,000 | U.S (Remote) | Full-Time Deeprec.ai is partnering up with an AI focused HealthTech company centred around early-stage cancer detection.This is a remote Data Engineering role focused on building and maintaining scalable pipelines that ingest, clean, and structure large, complex healthcare datasets. What You’ll DoWork with Data Scientists and ML Engineers to define data needs for LLM and ML models.Build and maintain scalable data pipelines for large healthcare datasets.Ensure data quality through cleaning, validation, and monitoring.Design efficient data structures and schemas for model training and use.Source new data while ensuring compliance with healthcare regulations (e.g., HIPAA) RequirementsBachelor’s degree in Computer Science, Engineering, or a related field.Experience as a Data Engineer working with large-scale or big data systems such as Apache SparkStrong programming skills in Python, Scala, or Java.Experience with ETL pipelines, data warehousing, and data modelling.Familiarity with cloud platforms (AWS, GCP, or Azure) and tools like Apache Spark.Strong problem-solving skills Nice to HaveMaster’s degree in Computer Science, Engineering, Data Science, or a related field.Experience working with healthcare data and standards such as FHIR or HL7.Familiarity with machine learning concepts and LLM fine-tuning workflows.Experience using data orchestration tools such as Apache Airflow. Why Join?Help shape the future of healthcare by building AI that improves early cancer detection and saves lives.Work on high-impact, real-world AI used directly in clinical settings at scale.Competitive salary, benefits, and flexible remote/hybrid working options.Join a mission-driven, fast-growing team focused on innovation and health equity.Continuous learning with exposure to cutting-edge AI, ML, and healthcare technologies.

A fast-growing deep-tech company operating in the advanced sensing, AI, and real-time analytics space is seeking a skilled Data Engineer to help build the next generation of data and ML infrastructure powering mission-critical intelligent systems. This role sits at the intersection of high-frequency sensor data, machine learning infrastructure, cloud platforms, and real-world edge deployments. You will work closely with engineering and ML teams to build scalable data systems that transform complex telemetry into actionable intelligence. The Role As a Data Engineer, you will design and maintain robust data pipelines and infrastructure supporting large-scale sensor ingestion, analytics, and machine learning workflows. You’ll contribute across the full data lifecycle — from edge-to-cloud ingestion through training data preparation and operational analytics — within a highly collaborative, engineering-led environment. Key ResponsibilitiesDesign and implement scalable data pipelines for ingesting, processing, and delivering high-frequency sensor and telemetry dataBuild architectures supporting both real-time stream processing and large-scale batch analyticsOwn core data platform infrastructure including time-series databases and object storage systemsDevelop ML data pipelines including:dataset preparationlabeling workflowsfeature storesversion-controlled training datasetsDefine and enforce data schemas, contracts, and quality standards across distributed data sourcesDesign cloud-side data systems optimized for bandwidth-constrained edge environmentsBuild internal dashboards, APIs, and analytics tooling to support engineering and product teamsSupport field data collection activities including deployment and management of sensor datasetsCollaborate cross-functionally with Embedded, RF, Signal Processing, and ML Engineering teamsMonitor and optimize pipeline performance to ensure reliable low-latency data deliveryRequired ExperienceBachelor’s or Master’s degree in Computer Science, Data Engineering, or related discipline3 years of experience in Data Engineering, ML Infrastructure, or backend data systemsHands-on experience with data processing technologies such as Kafka, Spark, Flink, or similar frameworksExperience working with time-series or event-driven data at scaleStrong understanding of data modeling, schema management, and production data quality practicesExperience with AWS (or similar cloud platforms) and infrastructure-as-code methodologiesFamiliarity with CI/CD pipelines and automated testing for data workflowsStrong English communication skillsPreferred ExperienceBackground working with IoT, embedded systems, or hardware-generated dataUnderstanding of edge computing and on-device data reduction strategiesExperience supporting ML feature engineering and training data infrastructureFamiliarity with event-driven architectures and real-time distributed systemsExposure to regulated, security-sensitive, or mission-critical environmentsStartup or high-growth company experienceWhy Join?Work on cutting-edge AI and sensing technologies with real-world impactSolve complex engineering challenges involving real-time data and intelligent systemsCollaborate with highly technical multidisciplinary teamsInfluence the architecture of next-generation ML and analytics platformsJoin a fast-moving, innovation-driven environment with significant growth potentialFor a confidential discussion regarding this opportunity, please apply directly.

A high-growth European deep-tech company operating at the forefront of AI and next-generation infrastructure is seeking a senior Enterprise Account Executive to drive strategic enterprise growth across Germany. Backed by leading global investors and recognized internationally for breakthrough innovation in AI efficiency and model optimization, the company is scaling rapidly across Europe and global enterprise markets. Its proprietary technology enables dramatic reductions in LLM size and inference costs while maintaining production-grade performance helping enterprises deploy AI faster, greener, and more economically. The Opportunity You will lead strategic enterprise engagements with major German organizations, partnering with executive stakeholders to identify transformational AI opportunities and shape long-term commercial partnerships. The role combines:Strategic enterprise salesConsultative solution developmentExecutive relationship managementGo-to-market expansionComplex deal leadershipYou will work closely with technical and product teams to design tailored AI and infrastructure solutions aligned with customer business priorities. Key Responsibilities Enterprise Sales & Revenue GrowthOwn the full enterprise sales lifecycle from discovery through negotiation, close, and expansionBuild and close complex, high-value enterprise dealsDrive strategic revenue growth while developing long-term customer partnershipsManage multi-stakeholder engagements across business and technical teamsStrategic GTM & Market ExpansionDevelop regional go-to-market strategies across priority verticalsIdentify opportunities within AI, infrastructure, and advanced enterprise technology initiativesRepresent the organization at senior executive and technical levelsExpand presence within key German enterprise accountsConsultative Solution SellingLead value-led conversations focused on business transformation outcomesPartner with executives to uncover both explicit and latent AI opportunitiesCo-create enterprise AI roadmaps and tailored solution strategiesTranslate complex technical capabilities into clear commercial value propositionsCross-Functional LeadershipCollaborate closely with engineering, research, product, and solutions teamsLead commercial coordination across complex deal cyclesProvide market insight and customer feedback to support product directionRequired Experience10 years’ experience in enterprise sales, strategic accounts, or consultative technology salesProven success closing complex enterprise deals in the €500K–€5M rangeStrong executive presence with experience engaging C-level stakeholdersDeep understanding of German enterprise buying environments and stakeholder dynamicsNative German and fluent English requiredPreferred BackgroundExperience selling AI, infrastructure, cloud, or highly customized technology solutionsExisting relationships across enterprise sectors including finance, energy, manufacturing, telecom, or industrialsConsulting, systems integration, or complex solution-sales backgroundExperience helping scale new markets or high-growth technology businessesWhy This Role?Join one of Europe’s most exciting deep-tech growth storiesWork with cutting-edge AI and LLM optimization technologiesInfluence enterprise AI transformation at scaleHighly competitive compensation package including strong commission structure and signing bonusInternational, collaborative, innovation-led culture