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🔥 Data Scientist (Applied Machine Learning)
Posted about 1 hour ago

📍 Europe

🧭 Full-Time

🔍 Hospitality

🏢 Company: Nory

  • A scientific approach to problem solving based on crafting and testing hypotheses
  • The ability to write clean and maintainable python code
  • Real world experience deploying algorithms into production
  • Strong fundamentals in ML theory
  • Familiarity with cloud infrastructure
  • Design, build and deploy production new machine learning algorithms
  • Monitor, maintain and iterate on existing algorithms
  • Work closely with product and engineering on collaborative feature releases
  • Contribute to the wider data and tech community at Nory

PythonCloud ComputingMachine LearningMLFlowNumpyAlgorithmsData scienceData StructuresPandasRESTful APIs

Posted about 1 hour ago
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🔥 Machine Learning Ops Engineer
Posted about 2 hours ago

📍 US

🧭 Full-Time

🔍 Software Development

🏢 Company: Weave👥 501-1000💰 $70,000,000 Series D over 5 years agoMedicalSaaSVoIPUnified CommunicationsSmall and Medium BusinessesSoftware

  • 5+ years of experience in any structured back-end language, i.e. Go, Java or Python (Go and Python experience is a plus).
  • Experience moving and storing TBs of data or 100M’s to 10B’s of records.
  • Demonstrated experience with common MLOps technologies such as Python, Jupyter, Workflow Engines (Dagster, MLFlow, KubeFlow, etc), DVC, Triton Server, LLMs, Postgres, and others.
  • Experience with data labelling or annotation for audio or NLP use cases.
  • Understanding of distributed systems and building scalable, redundant, and observable services.
  • Expertise in designing and architecting systems for distributed data sets and services
  • Experience building solutions to run on one or more of the public clouds (e.g., AWS, GCP, etc.).
  • Experience providing stable well designed libraries and SDKs for internal use.
  • Demonstrated track record of delivering complex projects on time and have experience working in enterprise-grade production environments.
  • Design and Develop machine learning infrastructure, tooling, and models to help teams deliver world class experiences.
  • Help product and development teams understand the data lifecycle and the inherent experimental nature of machine learning.
  • Build internal products and platforms to enable teams to incorporate AI into their features and customer facing products.
  • Consult with teams to help them understand common patterns, anti-patterns, and tradeoffs of machine learning. Guide them through creating excellent customer experiences end to end.
  • Build scalable, resilient services to support data integration, event processing, and platform extensions.
  • Contribute to the continued evolution of product functionality that services large amounts of data and traffic.
  • Write code that is high-quality, performant, sustainable, and testable while holding yourself accountable for the quality of the code you produce.
  • Coach and collaborate inside and outside the team. You enjoy working closely with others - helping them grow by sharing expertise and encouraging best practices.
  • Work in a cloud environment, considering the implementation of functionality through several distributed components and services.
  • Work with our stakeholders to translate product goals into actionable engineering plans.

AWSBackend DevelopmentDockerPostgreSQLPythonSQLCloud ComputingData AnalysisGCPGitKubernetesMachine LearningMLFlowAPI testingData engineeringData scienceGoREST APICI/CDDevOpsMicroservicesData visualizationData modeling

Posted about 2 hours ago
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🔥 Machine Learning Engineer
Posted about 13 hours ago

📍 United States

🧭 Full-Time

💸 130000.0 - 200000.0 USD per year

🔍 Software Development

🏢 Company: Sadaora

  • 5+ years of experience developing, deploying, and maintaining ML models in production environments.
  • Proficiency in Python and common ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch, XGBoost).
  • Strong foundation in statistics, linear algebra, probability, and optimization.
  • Deep understanding of a range of ML techniques (regression, classification, clustering, NLP, deep learning).
  • Experience with cloud platforms such as AWS, GCP, or Azure.
  • Familiarity with containerization and orchestration tools (Docker, Kubernetes).
  • Solid understanding of software engineering principles, version control (Git), and CI/CD workflows.
  • Design, train, and evaluate machine learning models using best-in-class frameworks.
  • Architect scalable ML solutions and pipelines, from feature engineering to deployment.
  • Implement rigorous testing, validation, and monitoring processes to ensure model reliability in production.
  • Work closely with data engineers to shape the data architecture required for robust ML workflows.
  • Build efficient ETL pipelines to clean, preprocess, and transform large-scale datasets.
  • Partner with product managers, engineers, and business stakeholders to define ML use cases.
  • Collaborate with software engineers to integrate ML models into production-grade APIs and applications.
  • Translate complex ML concepts into business-relevant insights and recommendations.
  • Stay current with advancements in machine learning, AI, and related fields.
  • Experiment with new algorithms, architectures, and tools to continuously enhance our capabilities.
  • Contribute to a culture of experimentation, technical excellence, and intellectual curiosity.

AWSDockerPythonETLGCPGitKubernetesMachine LearningMLFlowPyTorchAzureData engineeringTensorflowCI/CD

Posted about 13 hours ago
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🔥 Machine Learning Manager, China (Remote)
Posted about 15 hours ago

📍 China

🏢 Company: Bjak👥 101-250Price ComparisonInsurTechInformation Technology

  • Bachelor's, Master's, or Ph.D. in Computer Science, Artificial Intelligence, or a related field.
  • Proven experience as an AI engineer or data scientist, with a track record of leading successful AI projects.
  • Proficiency in AI and machine learning frameworks and programming languages (e.g., Python).
  • Strong expertise in data preprocessing, feature engineering, and model evaluation.
  • Excellent problem-solving and critical-thinking skills.
  • Effective leadership, communication, and team management abilities.
  • A passion for staying at the forefront of AI and machine learning advancements.
  • Lead and mentor a team of AI engineers, providing technical guidance, coaching, and fostering their growth.
  • Collaborate with product managers and stakeholders to define AI project objectives, requirements, and timelines.
  • Design, develop, and implement AI models, algorithms, and applications to solve complex business challenges.
  • Oversee the end-to-end AI model lifecycle, including data collection, preprocessing, model training, evaluation, and deployment.
  • Stay updated with the latest advancements in AI and machine learning, incorporating best practices into projects.
  • Drive data-driven decision-making through advanced analytics and visualization techniques.
  • Ensure the security, scalability, and efficiency of AI solutions.
  • Lead research efforts to explore and integrate cutting-edge AI techniques.

DockerPythonArtificial IntelligenceData AnalysisKerasMachine LearningMLFlowNumpyAlgorithmsApache KafkaAPI testingData scienceREST APIPandasSparkTensorflowCI/CDMicroservicesData visualizationData modeling

Posted about 15 hours ago
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🔥 Senior Machine Learning Engineer, LS Embedding
Posted 1 day ago

📍 United States

🧭 Full-Time

💸 216700.0 - 303400.0 USD per year

🔍 Software Development

🏢 Company: Reddit👥 1001-5000💰 $410,000,000 Series F over 3 years ago🫂 Last layoff almost 2 years agoNewsContentSocial NetworkSocial Media

  • 5+ years of experience in machine learning engineering, with a strong focus on recommendation systems, representation learning, and deep learning.
  • Hands-on experience with Graph Neural Networks (GNNs), collaborative filtering, and large-scale embeddings.
  • Proficiency in Python and experience with ML frameworks such as PyTorch Geometric (PyG), Deep Graph Library (DGL), TensorFlow, or JAX.
  • Strong understanding of graph theory, network science, and representation learning techniques.
  • Experience building distributed training and inference systems using ML infrastructure components (data parallelism, model pruning, inference optimization, etc.).
  • Ability to work in a fast-paced environment, balancing innovation with high-quality production deployment.
  • Strong communication skills and the ability to collaborate cross-functionally with engineers, researchers, and product teams.
  • Design and implement scalable, high-performance machine learning models using Graph Neural Networks (GNNs), transformers, and knowledge graph approaches.
  • Develop and optimize large-scale embedding generation pipelines for Reddit’s recommendation systems.
  • Collaborate with ML infrastructure teams to enable efficient distributed training (multi-GPU, model/data parallelism) and low-latency serving.
  • Work closely with cross-functional teams (Ads, Feed Ranking, Content Understanding) to integrate embeddings into various personalization and ranking systems.
  • Drive feature engineering efforts, identifying and curating expressive raw data to enhance model effectiveness.
  • Monitor, evaluate, and improve model performance using A/B testing, offline metrics, and real-time feedback loops.
  • Stay up-to-date with the latest research in GNNs, transformers, and representation learning, bringing new ideas into production.
  • Participate in code reviews, mentor junior engineers, and contribute to technical decision-making.

PythonData AnalysisKerasMachine LearningMLFlowPyTorchAlgorithmsData StructuresTensorflowA/B testing

Posted 1 day ago
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🔥 Senior Data Scientist
Posted 1 day ago

📍 Germany, Austria

🏢 Company: Storyblok👥 101-250💰 $80,089,317 Series C 10 months agoInternetCMSIaaSWeb HostingWeb DevelopmentPaaSInformation TechnologyWeb DesignSoftware

  • Proficiency in programming languages such as Python or R, and experience with SQL for data manipulation
  • Strong analytical and critical thinking skills with a keen attention to detail
  • Solid understanding of machine learning algorithms and experience applying them to real-world problems
  • Lead the development and implementation of advanced statistical and machine learning models to extract insights and drive business decisions
  • Collaborate with cross-functional teams to understand business challenges and develop data-driven solutions
  • Mentor and guide junior team members and Data Champions from other divisions, fostering a data-driven culture and enabling teams to leverage analytics effectively

AWSPythonSQLApache AirflowCloud ComputingData AnalysisData MiningETLGCPMachine LearningMLFlowNumpyTableauAlgorithmsAzureData engineeringData sciencePandasSparkTensorflowCommunication SkillsData visualizationData modelingData analyticsA/B testing

Posted 1 day ago
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🔥 Senior Data Scientist - (Remote - US)
Posted 1 day ago

📍 United States

🔍 Software Development

🏢 Company: Jobgether👥 11-50💰 $1,493,585 Seed about 2 years agoInternet

  • 5+ years of experience in AI, machine learning, and data science with practical deployment experience.
  • Strong proficiency in Python and machine learning frameworks such as PyTorch, TensorFlow, and Keras.
  • Extensive experience with Kubernetes and Docker for containerized AI deployments.
  • Familiarity with cloud environments (AWS preferred) for AI model deployment.
  • Expertise in SQL and standard data manipulation techniques.
  • Experience with anomaly detection, ideally related to financial crime patterns.
  • Knowledge of MLOps, including model monitoring, retraining strategies, and production pipelines.
  • Experience with AI testing platforms (e.g., MLflow) and C++ is a plus.
  • A full-stack mindset, with the ability to build, deploy, and refine AI solutions in production.
  • Strong customer interaction skills and the ability to translate customer needs into technical solutions.
  • A Ph.D. or Master’s in Computer Science, Mathematics, Statistics, or a related field is preferred but not required.
  • Develop and deploy machine learning models to detect financial crime, focusing on anomaly detection.
  • Enhance and optimize data pipelines, incorporating customer feedback to improve detection accuracy.
  • Lead AI model governance, ensuring models are interpretable, scalable, and reliable for real-world deployment.
  • Collaborate closely with customers and stakeholders to translate feedback into technical improvements and product enhancements.
  • Apply MLOps best practices to ensure smooth production-ready AI implementations.
  • Provide mentorship and technical guidance to junior team members while remaining hands-on with model development.
  • Stay updated on the latest AI trends and financial crime detection methodologies, continually evolving the platform's capabilities.

AWSDockerPythonSQLKerasKubernetesMachine LearningMLFlowPyTorchC++Data scienceTensorflow

Posted 1 day ago
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🔥 Team Lead Senior AI Engineer
Posted 2 days ago

📍 Poland, Romania, Ukraine

🔍 Cybersecurity

🏢 Company: Point Wild👥 101-250SecuritySoftware

  • Strong background in applied machine learning, inclusive of deep learning and natural language processing, with experience deploying AI in production.
  • Proficiency in Python, PyTorch/TensorFlow, and cloud-based ML deployment (AWS preferred).
  • Ability to translate AI capabilities into tangible product improvements that impact users.
  • Experience leading AI projects and mentoring engineers, with a track record of delivering AI-powered features in production.
  • Manage the execution of the AI roadmap, ensuring AI initiatives align with business objectives and drive measurable impact.
  • Partner with R&D teams across multiple product lines to scope, prioritize, and deliver AI-powered features and capabilities.
  • Serve as the single technical point of contact for AI initiatives, providing expert guidance on architecture, model selection, and deployment.
  • Write production-level code, submit PRs, and review team contributions—ensuring high-quality AI solutions with best practices in software engineering and MLOps.
  • Conduct PR reviews, uphold rigorous engineering standards, and mentor engineers to elevate AI development across the company.
  • Ensure AI solutions are deployable, maintainable, and optimized for real-world performance.

AWSLeadershipPythonSQLArtificial IntelligenceCloud ComputingMachine LearningMLFlowNumpyPyTorchAlgorithmsData StructuresREST APITensorflowCommunication SkillsAnalytical SkillsProblem SolvingMentoringTeam managementSoftware Engineering

Posted 2 days ago
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🔥 Senior ML Infra engineer
Posted 4 days ago

📍 France

🧭 Full-Time

🔍 Streaming Advertising

🏢 Company: Vibe👥 101-250💰 $22,500,000 Series A about 1 year agoInternetAdvertisingTVMarketing

  • 8+ years of experience in relevant technical roles (Software Engineering, Data Engineering, ML Ops, or Infrastructure), with a strong foundation to build and scale ML infrastructure
  • Strong coding skills in Python, CI/CD, and Infrastructure as Code (Terraform, Ansible)
  • Deep expertise in ML Infrastructure: training orchestration (Dagster, Airflow), feature stores, live model monitoring, and distributed/multi-GPU training (TensorFlow, PyTorch)
  • Extensive cloud & scalability experience: deploying ML models on AWS/GCP, optimizing real-time inference, handling large-scale data pipelines, and implementing cost-efficient FinOps strategies
  • Build and optimize automated ML training pipelines (MLflow, Dagster)
  • Improve scalability and performance (multi-GPU, caching, distributed architectures)
  • Deploy and optimize real-time inference systems to ensure sub-20ms latency at scale
  • Implement monitoring and observability for models (Prometheus, Grafana, Evidently AI)
  • Optimize cloud costs and resource management (AWS Spot Instances, auto-scaling Kubernetes, FinOps)

AWSPythonGCPKubernetesMLFlowPyTorchData engineeringGrafanaPrometheusTensorflowCI/CDTerraformAnsibleSoftware Engineering

Posted 4 days ago
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🔥 Principal Machine Learning Architect
Posted 4 days ago

📍 USA

🧭 Full-Time

🔍 Software Development

🏢 Company: Sift👥 251-500💰 Secondary Market about 3 years agoFraud DetectionBig DataPredictive AnalyticsAnalyticsNetwork Security

  • Proven experience building large-scale ML systems in production environments.
  • Familiarity with tools like Flink, Spark, PyTorch, TensorFlow, or similar frameworks.
  • Proficiency in not only Python, but also Java, C++, or similar languages.
  • Knowledge of industry best practices for deploying, maintaining, and scaling ML systems in production.
  • Experience in high-impact areas such as ad-tech, recommendation systems, personalization, search ranking, or gaming.
  • Strong understanding of modern ML engineering trends and challenges, including but not limited to model monitoring, drift detection, and retraining strategies.
  • Knowledge of GenAI, including LLMs, as well as the trends and challenges of building GenAI applications.
  • Ability to align and lead cross-functional teams on large-scale architectural initiatives.
  • Ability to provide guidance or mentor junior engineers
  • Architect scalable, reliable, and low-latency (150ms) ML systems for both online and offline use cases.
  • Evaluate and incorporate cutting-edge ML trends and technologies while aligning them with the company’s current architecture and goals.
  • Work closely with stakeholders across engineering, product, and data science teams to align technical designs with business priorities.
  • Establish and enforce best practices for maintaining consistent ML model performance in production.
  • Lead large-scale initiatives, such as transitioning to next-generation architectures, and ensure alignment across diverse engineering teams.
  • Provide mentorship and technical guidance to engineers to foster a culture of excellence.
  • Develop a deep understanding of business and customer KPIs.
  • Represent the innovation of our data science and ML in the industry.

AWSBackend DevelopmentLeadershipPythonSQLJavaKafkaKubeflowMachine LearningMLFlowPyTorchSoftware ArchitectureC++Cross-functional Team LeadershipAlgorithmsData scienceData StructuresSparkTensorflowCommunication SkillsAnalytical SkillsCollaborationProblem SolvingRESTful APIsMentoringStrategic thinkingData modeling

Posted 4 days ago
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