SumerSports

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👥 501-1000💰 $166,262,336 Series F over 3 years ago🫂 Last layoff about 2 years agoFinancial Services SaaS FinTech Software

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🔥 Software Engineer - Football Analytics

Posted 3 days ago

📍 United States, Canada

🧭 Full-Time

🔍 Sports Analytics

🔧 Requirements

8+ years of commercial software development experience or 6 years with an advanced degree
Strong proficiency in React/Typescript, Java, and Python
Experience in web application development and distributed systems
Familiarity with AWS/GCP/Azure, Kubernetes, Terraform, Helm, Airflow, and Docker

💡 Responsibilities

Lead the design and development of complex product features from conception to deployment
Manage project priorities, deadlines, and deliverables with autonomy
Collaborate with cross-functional teams
Contribute to the continuous improvement of data quality standards

AWSDockerPythonGCPJavaKubernetesTypeScriptAirflowAzureReactCI/CDTerraform

Posted 3 days ago

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🔥 Sr. Software Engineer (Full Stack) - Fantasy Football

Posted 11 days ago

📍 United States, Canada

🧭 Full-Time

💸 100000.0 - 120000.0 USD per year

🔍 Software Development

🔧 Requirements

8+ years of commercial software development experience or 6 years with an advanced degree
Strong proficiency in React/Typescript, Java, C#, or Python
Proven experience in web application development and distributed systems
Familiarity with AWS/GCP/Azure, Kubernetes, Terraform, Docker, and CI/CD practices
Background in designing high-throughput, low-latency distributed systems

💡 Responsibilities

Lead design and development of complex product features from conception to deployment
Manage project priorities, deadlines, and deliverables
Collaborate with cross-functional teams
Contribute to improving data quality standards

AWSDockerPythonSoftware DevelopmentGCPJavaKubernetesTypeScriptC#AirflowAzureReactCI/CDTerraform

Posted 11 days ago

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🔥 Senior Platform Engineer

Posted 25 days ago

🔍 Software Development

🔧 Requirements

Strong expertise in Python and libraries for machine learning and data processing
Extensive experience with Kubernetes, including deployments, scaling, and management of containerized applications
In-depth knowledge of AWS services related to computing, storage, and machine learning
Hands-on experience with building and deploying generative AI and statistical models
Solid understanding of feature engineering, data preprocessing, and data integration techniques
Familiarity with MLOps tools and best practices, including automation, monitoring, and orchestration

💡 Responsibilities

Develop and maintain scalable and efficient machine learning pipelines capable of processing large volumes of data in real time
Work independently to deploy, manage, and monitor machine learning models, ensuring high performance and reliability
Collaborate with product engineering, data science, and ML teams to integrate advanced machine learning features into our products
Deploy and manage ML models using Kubernetes on AWS, ensuring high availability and low latency for real-time inference
Implement continuous integration and delivery (CI/CD) processes for machine learning systems, ensuring rapid and safe deployment of features
Optimize data and feature engineering processes to enhance model performance and reliability
Monitor and evaluate model performance, making adjustments and improvements as needed
Ensure compliance with data privacy and security protocols throughout the model lifecycle
Contribute to the strategic planning and development of ML projects, ensuring alignment with business objectives and technological advancement

Posted 25 days ago

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🔥 Data Engineer

Posted 4 months ago

🧭 Full-Time

🔍 Software Development

🔧 Requirements

Proven experience as a data engineer, preferably with at least 3 or more years of relevant experience.
Some exposure designing cloud native solutions and implementations with Kubernetes
Experience with Airflow or similar pipeline orchestration tools.
Strong background in Python programming.
Demonstrated experience in collaborating with Data Science and Engineering teams in a production environment.
Firm grasp on SQL and knowledge of relational data modeling schemas.
Preference for experience with Databricks or Spark
Familiarity with modern data stack design and strong opinions on data lifecycle management, testing, and governance.
Effective communicator with the ability to advocate best data practices across the organization.
Passion for coaching and working in a team-oriented environment.
Commitment to improving developer experience and productivity.
Experience with distributed systems, microservices architecture, and cloud platforms (e.g., AWS, Azure, Google Cloud).
Excellent problem-solving skills and the ability to analyze and debug complex issues.
Strong communication and interpersonal skills, with the ability to collaborate effectively with cross-functional teams.

💡 Responsibilities

Develop and maintain data pipelines using Databricks, Airflow, or similar orchestration systems.
Write robust, maintainable code in Python, following best practices and coding standards.
Design and implement solutions using Kubernetes, ensuring high availability and scalability.
Gather product data requirements and implement solutions to ingest, process, and serve that data to applications at scale
Collaborate closely with Data Science and Engineering teams to build production-ready applications, optimizing for performance and scale.
Cultivate data from a wide range of sources for use by our data scientists and maintain documentation for data.
Design a modern data stack, with a keen focus on providing a platform for data scientists and ML engineers to develop production ready models and pipelines.
Work across Data Science and Engineering teams to ensure effective collaboration and communication.
Actively participate in code reviews, coaching, and mentoring within cross-functional teams.
Enhance the developer experience through improved tooling and reduced toil.
Stay informed of industry advancements and advocate for the adoption of new technologies and best practices.

Posted 4 months ago

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