Jobgether
Overview
Bloomreach is building the world’s premier agentic platform for personalization. We’re revolutionizing how businesses connect with their customers, building and deploying AI agents to personalize the entire customer journey. We are enabling autonomous search, conversational shopping, and autonomous marketing to drive growth and loyalty for more than 1,400 global brands.
Join our Artificial Intelligence team as a Senior Software Engineer (with overlap into ML Engineer) and help us revolutionize marketing with ML-powered solutions. You’ll work on cutting-edge technologies, impact millions of users, and contribute to a product that truly makes a difference. We offer remote work in Central & Eastern Europe, with optional office space in Bratislava, Brno, or Prague on a full-time basis, and you’ll become a core part of the Engineering Team.
What you’ll work on
Design & Deliver new features
Ensure quality and performance of developed solution
Support and Maintain owned components
Your projects in detail a. Design & Deliver new features
Translate business requirements for ML-powered features into technical specifications and design documents.
Collaborate with data scientists to ensure new ML features’ technical feasibility and scalability.
Define and develop back-office API endpoints (to configure the features) as well as the high-performance serving endpoints.
Develop and implement ML models, algorithms, and data pipelines to support new features.
Deploy and monitor new features in production, ensuring seamless integration with existing systems.
b. Ensure quality and performance of developed solution
Perform rigorous testing and quality assurance of ML models and code, including unit tests, integration tests, and A/B testing.
Implement monitoring systems and dashboards to track the performance of ML models in production, identify potential issues, and optimize for accuracy and efficiency.
Contribute to developing and implementing DevOps and MLOps best practices within the team.
c. Support and Maintain owned components
Maintain end-to-end features, encompassing back-office APIs, models, definitions, and high-performance serving APIs.
Provide ongoing support and maintenance for existing ML-powered features, including troubleshooting issues, fixing bugs, and implementing enhancements.
Support client-facing colleagues in the investigation of possible issues (L3 support).
Document code, design decisions, and operational procedures to facilitate ongoing maintenance and knowledge sharing.
What technologies and tools does the AI team work with?
Programming languages - Python
Google Cloud Platform services - GKE, BigQuery, BigTable, GCS, Dataproc, VertexAI
Data Storage and Processing - MongoDB, Redis, Spark, TensorFlow
Software and Tools - Grafana, Sentry, Gitlab, Jira, Productboard, PagerDuty
The owned area encompasses various domains such as Recommendations, Predictions, Contextual bandits, MLOps. Experience in these areas is beneficial, as the team works with large data and ML pipelines.
Your success story
In 30 Days: Onboard and contribute to ongoing tasks, showing understanding of the codebase and team processes.
In 90 Days: Contribute to design discussions and independently deliver high-quality code for assigned features; participate in production issue investigation.
In 180 Days: Independently manage larger tasks, contribute to team improvements, and handle L3 support.
You have the following experience and qualities
Professional
— Proven experience in Python engineering, system design, and maintenance in AI/ML-powered features.
Personal
— Demonstrates initiative, teamwork, communication skills, and a commitment to continuous learning.
Professional experience
Proven experience in Python engineering, with a focus on AI/ML-powered features in production environments.
Experience with cloud platforms (GCP, AWS) and ML deployment services.
Strong understanding of software architecture for scalable APIs and microservices.
Experience with version control (Git) and CI/CD pipelines.
Familiarity with ML frameworks (TensorFlow, PyTorch, Scikit-learn) and ML pipelines/orchestration (Kubeflow, Airflow, Prefect).
Personal qualities
Strong initiative and proactive problem-solving.
Excellent communication and collaboration skills.
Passion for learning new technologies and AI/ML advancements.
Commitment to delivering high-quality work and continuous improvement.
Excited? Join us and transform the future of commerce experiences.
(Note: Some sections in the original description contained promotional or non-essential content. This refined version focuses on responsibilities, qualifications, and core team context while preserving the original role information.)
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Join our Artificial Intelligence team as a Senior Software Engineer (with overlap into ML Engineer) and help us revolutionize marketing with ML-powered solutions. You’ll work on cutting-edge technologies, impact millions of users, and contribute to a product that truly makes a difference. We offer remote work in Central & Eastern Europe, with optional office space in Bratislava, Brno, or Prague on a full-time basis, and you’ll become a core part of the Engineering Team.
What you’ll work on
Design & Deliver new features
Ensure quality and performance of developed solution
Support and Maintain owned components
Your projects in detail a. Design & Deliver new features
Translate business requirements for ML-powered features into technical specifications and design documents.
Collaborate with data scientists to ensure new ML features’ technical feasibility and scalability.
Define and develop back-office API endpoints (to configure the features) as well as the high-performance serving endpoints.
Develop and implement ML models, algorithms, and data pipelines to support new features.
Deploy and monitor new features in production, ensuring seamless integration with existing systems.
b. Ensure quality and performance of developed solution
Perform rigorous testing and quality assurance of ML models and code, including unit tests, integration tests, and A/B testing.
Implement monitoring systems and dashboards to track the performance of ML models in production, identify potential issues, and optimize for accuracy and efficiency.
Contribute to developing and implementing DevOps and MLOps best practices within the team.
c. Support and Maintain owned components
Maintain end-to-end features, encompassing back-office APIs, models, definitions, and high-performance serving APIs.
Provide ongoing support and maintenance for existing ML-powered features, including troubleshooting issues, fixing bugs, and implementing enhancements.
Support client-facing colleagues in the investigation of possible issues (L3 support).
Document code, design decisions, and operational procedures to facilitate ongoing maintenance and knowledge sharing.
What technologies and tools does the AI team work with?
Programming languages - Python
Google Cloud Platform services - GKE, BigQuery, BigTable, GCS, Dataproc, VertexAI
Data Storage and Processing - MongoDB, Redis, Spark, TensorFlow
Software and Tools - Grafana, Sentry, Gitlab, Jira, Productboard, PagerDuty
The owned area encompasses various domains such as Recommendations, Predictions, Contextual bandits, MLOps. Experience in these areas is beneficial, as the team works with large data and ML pipelines.
Your success story
In 30 Days: Onboard and contribute to ongoing tasks, showing understanding of the codebase and team processes.
In 90 Days: Contribute to design discussions and independently deliver high-quality code for assigned features; participate in production issue investigation.
In 180 Days: Independently manage larger tasks, contribute to team improvements, and handle L3 support.
You have the following experience and qualities
Professional
— Proven experience in Python engineering, system design, and maintenance in AI/ML-powered features.
Personal
— Demonstrates initiative, teamwork, communication skills, and a commitment to continuous learning.
Professional experience
Proven experience in Python engineering, with a focus on AI/ML-powered features in production environments.
Experience with cloud platforms (GCP, AWS) and ML deployment services.
Strong understanding of software architecture for scalable APIs and microservices.
Experience with version control (Git) and CI/CD pipelines.
Familiarity with ML frameworks (TensorFlow, PyTorch, Scikit-learn) and ML pipelines/orchestration (Kubeflow, Airflow, Prefect).
Personal qualities
Strong initiative and proactive problem-solving.
Excellent communication and collaboration skills.
Passion for learning new technologies and AI/ML advancements.
Commitment to delivering high-quality work and continuous improvement.
Excited? Join us and transform the future of commerce experiences.
(Note: Some sections in the original description contained promotional or non-essential content. This refined version focuses on responsibilities, qualifications, and core team context while preserving the original role information.)
#J-18808-Ljbffr