MLFlow Jobs

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πŸ“ Brazil

🧭 Full-Time

πŸ” Logistics Tech

  • Experience with machine learning models
  • Knowledge of deep learning architectures
  • Design machine learning models
  • Implement scalable ML solutions
  • Collaborate with cross-functional teams

AWSDockerPythonKubernetesMachine LearningMLFlowPyTorchTensorflow

Posted about 4 hours ago
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πŸ“ United States

πŸ” SaaS

🏒 Company: Canibuild Au Pty Ltd

  • 4+ years in MLOps, AI infrastructure, or DevOps
  • Strong expertise in CI/CD tools for ML (e.g., MLflow, Kubeflow, Airflow)
  • Experience with cloud ML services (AWS SageMaker, Google Vertex AI, Azure ML)
  • Proficiency in container orchestration (Docker, Kubernetes)
  • Understanding of AI model monitoring, logging, and explainability frameworks
  • Implement CI/CD pipelines for model training, testing, and deployment.
  • Develop scalable ML infrastructure to ensure reliable AI model performance.
  • Automate model retraining, versioning, and monitoring using MLflow, Kubeflow, or Airflow.
  • Deploy ML models on cloud platforms (AWS, Azure, GCP) and manage Kubernetes/Docker environments.
  • Assist in optimizing data pipelines and integrating AI models with production systems.
  • Ensure AI deployments adhere to security, governance, and compliance standards.

AWSDockerPythonGCPKubeflowKubernetesMachine LearningMLFlowAirflowAzureData engineeringCI/CDDevOps

Posted 1 day ago
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πŸ“ UK, Europe, Africa

🧭 Full-Time

πŸ” Fintech

🏒 Company: M-KOPA

  • Experience managing machine learning infrastructure in production
  • Working with infrastructure-as-code tools such as Azure Bicep, Terraform, ARM, CloudFormation or similar
  • Good practical experience in data engineering, for machine learning or general analytics use case.
  • Experience with Kubernetes or other platforms for containerized applications
  • Working with orchestration systems such as Apache Airflow
  • Proficiency in programming languages (Python, C#, Java, etc.)
  • Certification in Azure Solutions Architect Expert or similar
  • Designing, deploying and managing data and machine learning infrastructure to make it easy for data scientists to experiment, train, serve and monitor batch and online machine learning models in production.
  • Designing and implementing architectures to streamline exploration, training, deployment and monitoring of machine learning models.
  • Building and maintain CI/CD pipelines to deploy machine learning models into production, ensuring scalability, reliability, and continuous performance monitoring with automated retraining workflows.
  • Implementing version control for models and feature sets to ensure reproducibility, traceability, and compliance with best practices.
  • Using Azure and infrastructure-as-code tools (e.g., Azure Bicep, Terraform) you will automate and manage infrastructure for data pipelines, machine learning model training, and serving.
  • Establishing infrastructure and engineering patterns to feature engineering and reuse across suite of models.
  • Developing workflows for model validation, testing, and deployment, fully integrated with CI/CD systems, while enhancing resource utilization, to enable distributed processing, and optimize workflows for scalability, including GPU/TPU acceleration.

PythonApache AirflowKubernetesMachine LearningMLFlowAzureData engineeringCI/CDTerraformData analytics

Posted 1 day ago
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πŸ“ United States

πŸ’Έ 152000.0 - 213000.0 USD per year

πŸ” Financial Services

🏒 Company: GeminiπŸ‘₯ 501-1000πŸ’° $1,000,000 Secondary Market over 2 years agoπŸ«‚ Last layoff about 2 years agoCryptocurrencyWeb3Financial ServicesFinanceFinTech

  • 4+ years of work experience in analytics and data science domain focusing on financial services-related business problems.
  • 3+ years of experience deploying statistical and machine learning models in production.
  • 2+ years of experience in integrating data science models into applications.
  • Proven experience in developing and deploying ML models at scale, with a deep understanding of model lifecycle management.
  • Knowledge and experience of crypto exchange trading, financial markets, or banking.
  • Extensive knowledge of ML frameworks (Sagemaker or ML Flow) , libraries, data structures, data modeling, and software architecture.
  • Advanced skills with SQL are a must.
  • Proficient in Python.
  • Experience with one or more big data tools and technologies like Snowflake, Databricks, S3, Hadoop, Spark.
  • Experienced in working collaboratively across different teams and departments.
  • Strong technical and business communication.
  • Design and develop Trust & Safety machine learning and AI models to optimize across fraud, crypto exchange trading, and anti money laundering.
  • Distill complex models and analysis into compelling insights for our stakeholders and executives.
  • Analyze large and complex datasets to identify patterns for feature engineering, trends, and anomalies and develop predictive models that can be used for decision-making.
  • Collaborate with software developers to design and implement machine learning systems that can improve the speed and accuracy of the machine learning models.
  • Monitor and analyze the performance of our machine learning models and systems and make necessary improvements to ensure their effectiveness.
  • Stay up-to-date with data science tools and methodologies in technology and financial domain.
  • Perform root cause analysis and resolve production and data issues.

AWSPythonSQLData AnalysisGitMachine LearningMLFlowSnowflakeSoftware ArchitectureAlgorithmsData scienceData StructuresSparkCommunication SkillsAnalytical SkillsProblem SolvingRESTful APIsData modeling

Posted 1 day ago
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πŸ“ Australia, New Zealand, Canada, United States

πŸ” SaaS

🏒 Company: Canibuild Au Pty Ltd

  • Bachelor’s or Master’s in Computer Science, AI, or related field.
  • 7+ years in project management, with 3+ years in AI/ML projects.
  • PMP or Agile certification preferred.
  • Experience with MLOps tools (e.g., MLflow, Airflow, Weights & Biases).
  • Understanding of AI governance and ethical AI principles.
  • Strong leadership, problem-solving, and communication skills.
  • Define project scope, develop AI roadmaps, and manage resources.
  • Align AI solutions with business objectives and oversee end-to-end implementation.
  • Collaborate with cross-functional teams, including AI engineers and business leaders, to ensure transparency and goal alignment.
  • Monitor AI bias, compliance with AI governance frameworks (e.g., GDPR, CCPA), and ethical AI considerations.
  • Oversee AI/ML model lifecycle, ensuring models meet performance, security, and compliance standards.
  • Assess project success, identify areas for improvement, and drive AI innovation.

AWSLeadershipProject ManagementPythonAgileApache AirflowArtificial IntelligenceCloud ComputingData AnalysisMachine LearningMLFlowCommunication SkillsProblem SolvingRisk ManagementStrategic thinking

Posted 2 days ago
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πŸ“ United States

🧭 Full-Time

πŸ’Έ 170000.0 - 225000.0 USD per year

πŸ” Healthcare

🏒 Company: Red Cell PartnersπŸ‘₯ 11-50Financial ServicesVenture CapitalFinance

  • 10+ years of experience in computer science or an equivalent field
  • Proven experience in a leadership role driving ML system development and optimization, preferably in healthcare or related fields.
  • Demonstrated expertise in training ML models and building robust training pipelines for real-world applications.
  • Strong understanding of machine learning frameworks such as TensorFlow, PyTorch, or similar.
  • Proficient in programming languages like Python or Go, with the ability to write efficient, clean, and maintainable code.
  • Excellent written and verbal communication skills, with the ability to convey technical concepts to both technical and non-technical audiences.
  • A track record of delivering impactful machine learning solutions that have been successfully deployed in production environments.
  • Lead the team in architecting, building, and optimizing ML systems to deliver high-quality, real-world results in healthcare settings.
  • Design and implement robust training pipelines for machine learning models, ensuring efficiency and scalability for healthcare data.
  • Fine-tune ML models to meet specific healthcare needs and optimize their performance for various medical applications.
  • Develop and implement feedback mechanisms to continuously improve the accuracy and effectiveness of ML in healthcare contexts.
  • Collaborate with cross-functional teams to understand healthcare business requirements and translate them into actionable ML solutions.
  • Stay up-to-date with the latest advancements in machine learning and healthcare technology, implementing best practices to enhance our ML infrastructure.
  • Coach and mentor junior data engineers, fostering a culture of continuous learning and growth within the Lightbox Health team.
  • Communicate complex technical concepts and findings to non-technical stakeholders in a clear and concise manner, particularly in healthcare contexts.

LeadershipPythonSQLMachine LearningMLFlowPyTorchAlgorithmsData engineeringTensorflowCommunication SkillsCI/CDProblem SolvingRESTful APIsMentoringData modelingData analytics

Posted 2 days ago
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πŸ“ Argentina, Uruguay, Colombia, Mexico, Dominican Republic

🧭 Full-Time

πŸ” Machine Learning

🏒 Company: Halo MediaπŸ‘₯ 11-50InternetConsultingWeb DevelopmentAppsMarketingMobileWeb DesignSoftware

  • Python (Pandas, NumPy, Scikit-Learn, TensorFlow/PyTorch)
  • Strong knowledge of ML algorithms (supervised, unsupervised, reinforcement learning)
  • Experience with feature engineering and model evaluation
  • Familiarity with MLOps tools (Kubeflow, MLflow, Docker, CI/CD for ML)
  • Experience with cloud platforms (AWS, GCP, or Azure) for model deployment
  • Develop and optimize machine learning models for real-world applications
  • Work with datasets to preprocess, clean, and engineer features
  • Implement and fine-tune deep learning models (CNNs, RNNs, transformers)
  • Deploy ML models using APIs, microservices, or serverless architectures
  • Monitor and maintain deployed models, ensuring performance over time
  • Collaborate with software engineers and data teams to integrate ML solutions

AWSDockerPythonGCPKubeflowMachine LearningMLFlowMongoDBNumpyPyTorchAzurePandasTensorflowCI/CD

Posted 4 days ago
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πŸ“ US

🧭 Fulltime

πŸ’Έ 200000.0 - 270000.0 USD per year

πŸ” Game Development

🏒 Company: Second Dinner

  • Proven experience leading and growing cross-functional data science and engineering teams in fast-paced environments
  • Expertise in data engineering and infrastructure, including experience with AWS (Lambda, S3, Kinesis), Databricks, Apache Airflow, and Kafka
  • Strong background in data science and applied machine learning, with familiarity with frameworks and tools including Spark, PyTorch/TensorFlow, SageMaker, and MLFlow
  • Proficient in Python, with outstanding programming skills and experience following common software development workflows
  • Exceptional ability to collaborate with cross-functional teams to translate complex problems into data opportunities
  • Excellent communication skills, with ability to articulate technical concepts clearly and concisely to various audiences
  • Deep understanding of and enthusiasm for games, with a mindset for serving a diverse, global player base
  • Empower and grow top talent in data science and data engineering. Foster a high-performing, collaborative, and customer-focused team culture
  • Lead the design, development, and operation of scalable, reliable, and efficient data infrastructure to support Marvel SNAP and our future games
  • Lead the team to architect and build the machine learning serving and operations framework to enable data scientists to model, iterate and deploy fast
  • Enable and empower teams to build data products, tools, and features that deliver game outcomes
  • Collaborate with Analytics, Product, Design, and Marketing teams to identify business opportunities and shape the Data team’s priorities to align with them
  • Build organizational capabilities to enable data-driven decision-making at all levels, fostering a strong data culture across the company
  • Define and raise the bar for technical excellence in the data discipline. Advocate for best practices in data science, data engineering, and experimentation across the company.
  • Contribute to and execute Second Dinner’s overarching data strategy

AWSLeadershipPythonSQLApache AirflowKafkaMachine LearningMLFlowPyTorchCross-functional Team LeadershipData engineeringData scienceSparkTensorflowCommunication SkillsAnalytical SkillsCollaborationProblem SolvingRESTful APIsOrganizational skillsExcellent communication skillsData visualizationTeam managementStrategic thinkingData modelingData analytics

Posted 6 days ago
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πŸ“ South Africa

🧭 Full-Time

πŸ” E-commerce

🏒 Company: The Global Talent Co.

  • Bachelor's degree in a quantitative field (e.g., Statistics, Mathematics, Economics, Computer Science). Master's degree preferred.
  • 7+ years of experience in product and/or marketing analytics.
  • Strong understanding of statistical concepts (e.g., hypothesis testing, regression analysis, time series analysis).
  • Proficiency in SQL and experience working with large datasets.
  • Experience with:
  • Version Control:
  • Git, GitHub, GitHub Actions
  • Infrastructure:
  • AWS (S3, ECR, EKS)
  • Data Science:
  • Databricks, MLflow
  • Development:
  • Python, Anaconda, Poetry/Pipenv (or piplock)
  • Reporting & Visualization:
  • Tableau, Streamlit
  • Workflow Orchestration:
  • GitHub Actions, Prefect (or Airflow)
  • MLOps:
  • SpiceRack (limited deep learning support)
  • Hyperparameter Optimization:
  • Ax, Optuna
  • Excellent communication and presentation skills to translate complex data insights for non-technical audiences.
  • Strong problem-solving and analytical skills.
  • Experience with e-commerce businesses.
  • Experience with subscription-based business models is a plus.
  • Analyze product usage, user behavior, and marketing campaign performance to identify trends and opportunities for improvement.
  • Develop and maintain dashboards and reports to track key performance indicators (KPIs) and provide actionable insights.
  • Collaborate with product managers and marketers to define metrics, design experiments, and interpret results.
  • Build and deploy data pipelines and models to automate reporting and analysis processes.
  • Identify and investigate data anomalies and discrepancies proactively.
  • Present findings and recommendations to stakeholders in a clear and concise manner.
  • Contribute to the development and enhancement of data infrastructure and analytical tools in collaboration with the product analytics team.

AWSPythonSQLData AnalysisGitMachine LearningMLFlowProduct ManagementTableauProduct AnalyticsData sciencePandasCommunication SkillsAnalytical SkillsRESTful APIsReportingData visualizationMarketingData modelingA/B testing

Posted 6 days ago
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πŸ“ LatAm

🧭 Full-Time

πŸ” Real Estate

🏒 Company: TruelogicπŸ‘₯ 101-250ConsultingWeb DevelopmentWeb DesignSoftware

  • 5+ years of experience in ML Ops, Data Engineering, or DevOps roles.
  • Proficiency with cloud platforms such as GCP, AWS, or Azure, and ML Ops tools like Kubeflow, MLflow, or SageMaker.
  • Expertise in containerization (Docker, Kubernetes) and CI/CD pipelines (GitLab CI, Jenkins, CircleCI).
  • Hands-on experience with data pipeline orchestration tools like Airflow.
  • Strong knowledge of data versioning, feature stores, and model lifecycle management.
  • Build and manage automated, reproducible ML pipelines for data ingestion, training, validation, deployment, and monitoring.
  • Develop scalable model-serving architectures, including containerized deployments, APIs, and real-time frameworks.
  • Automate infrastructure workflows, establishing CI/CD pipelines for ML models with robust versioning and rollback mechanisms.
  • Monitor model performance and data drift in production, ensuring accuracy and system health.
  • Collaborate with cross-functional teams to promote best practices for ML reproducibility, scalability, and maintenance.

AWSDockerPythonSQLApache AirflowGCPGitKubeflowKubernetesMachine LearningMLFlowAzureData engineeringCI/CDRESTful APIsDevOpsTerraform

Posted 6 days ago
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