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As part of the Audiences team, youll work on highly scalable systems, tackle real-time challenges, and contribute to a platform that directly impacts the success of our customers campaigns.

Our team mixes disciplines from back-end, data, AI and front-end engineers and were looking for a great back-end data oriented developer that is passionate about what they do, who want to dive into the worlds of big data, microservices and production management at our scale, to help us reach our vision and goals

What youll do:
Solve diverse, complex problems at a large scale.
Collaborate with Product Managers, data scientists and Software Engineers to deliver innovative, user-facing products.
Independent - cradle to grave, own a feature from scratch to production.
Analyze and improve performance, scalability and stability of our products, environments and tools.
Continuously learn and evaluate new technologies in the everlasting effort to perfect our products and adapt to the ever-growing scale.

As part of the Audiences team, youll work on highly scalable systems, tackle real-time challenges, and contribute to a platform that directly impacts the success of our customers campaigns.

Our team mixes disciplines from back-end, data, AI and front-end engineers and were looking for a great back-end data oriented developer that is passionate about what they do, who want to dive into the worlds of big data, microservices and production management at our scale, to help us reach our vision and goals.

What youll do:
Solve diverse, complex problems at a large scale.
Collaborate with Product Managers, data scientists and Software Engineers to deliver innovative, user-facing products.
Independent - cradle to grave, own a feature from scratch to production.
Analyze and improve performance, scalability and stability of our products, environments and tools.
Continuously learn and evaluate new technologies in the everlasting effort to perfect our products and adapt to the ever-growing scale.

Were looking for a Big Data Engineer who loves turning massive, messy datasets into scalable, reliable systems. Youll design and maintain data pipelines, ensure data quality, and collaborate with data scientists and product managers to bring new insights to life.

What youll do:
Design, build, and optimize scalable data pipelines and ETL processes
Own data products from design to production.
Ensure data accuracy, integrity, and performance across large datasets.
Collaborate with data scientists and engineers to deliver production-grade experiment.

Were looking for a Senior Data Engineer to join our Data team - someone whos passionate about building reliable, scalable data infrastructure and thrives on solving complex technical challenges.
In this role, youll own the design and development of end-to-end data pipelines that power analytics and data-driven decision-making.
Youll collaborate closely with both business and technical stakeholders to ensure data flows smoothly, accurately, and efficiently across the company.
What You Will Do:
Design, implement, and maintain large-scale ETL and ELT pipelines using modern data frameworks and cloud technologies.
Work with Redshift data warehouses to design efficient schemas and optimize performance.
Build and manage data ingestion processes from multiple sources - APIs, SaaS platforms, internal systems, and databases.
Collaborate with stakeholders to deliver clean, well-modeled, and high-quality data.
Build and evolve a modern, efficient, and scalable data warehouse architecture.
Ensure observability, monitoring, and testing across all data processes.
Apply best practices in CI/CD, version control (Git), and data quality validation.

Were hiring a ML Engineer to accelerate AI-driven innovation across B2B SaaS platform.
Youll be at the forefront of building intelligent systems that power core product experiences and automate internal operations, driving efficiency, speed, and scale across the organization. This is a high-impact, hands-on role in a fast-growing, AI-first company where machine learning is a foundational pillar, not a bolt-on feature. You'll partner with product, engineering, and operations teams to design and implement powerful ML and LLM-based solutions that make a measurable difference.
What You Will Do.:
Build Intelligent Systems: Design and develop ML/LLM-powered solutions that solve real-world challenges across product and internal workflows.
Own Full Lifecycles: Take projects from concept all the way to production, including model training, evaluation, integration, and monitoring.
Leverage State-of-the-Art Tools: Work with leading frameworks like LangChain, Hugging Face, TensorFlow, and PyTorch to deliver cutting-edge functionality.
Collaborate Cross-Functionally: Partner with product managers, engineers, and stakeholders to embed AI capabilities into user-facing features and backend services.
Ship at Scale: Build and maintain scalable APIs and services, integrating best practices in CI/CD, observability, and cloud infrastructure.
Report with Impact: Share progress, challenges, and results clearly with technical and executive stakeholders.

Were hiring a Machine Learning Engineering Manager to guide and grow a high-impact ML team driving AI-powered innovation across B2B SaaS platform. Youll lead the design and delivery of AI solutions while mentoring engineers and setting the technical direction for AI-first development at scale.
This is a leadership role with a balance of hands-on engineering and team management, perfect for someone who thrives on solving technical challenges, inspiring a team, and shaping the future of AI in fintech automation.
What You Will Do:
Lead & Mentor: Manage, mentor, and grow a team of ML engineers, fostering technical excellence and career development.
Set Technical Direction: Define the ML strategy, ensuring best practices in architecture, frameworks, and operationalization.
Build and deploy AI-based solutions: Oversee the development and deployment of GenAI/LLM-powered solutions that address real-world challenges across products.
Scale & Operationalize: Establish scalable ML infrastructure, CI/CD, observability, and data pipelines for high-availability production systems.
Collaborate Cross-Functionally: Partner with product managers, engineers, and business stakeholders, clearly communicate progress, challenges, and outcomes.

we are seeking a Senior Data Scientist to drive the development and implementation of AI-based solutions that solve complex business challenges across our innovative SaaS platform. In this key role, youll work cross-functionally to lead end-to-end AI projectsfrom data exploration to deploymenthelping shape the future of our intelligent products and user experiences.
If youre passionate about machine learning, LLMs, and real-world impact, and thrive in a collaborative, high-velocity environment, wed love to connect
What You Will Do:
Identify AI opportunities to enhance product experiences and operational efficiency.
Collect, analyze, and model diverse financial datasets to develop actionable AI Products.
Own the full AI solution lifecyclefrom problem definition to research, modeling, and hands-on implementation.
Break down complex problems into well-defined, structured work plans.
Collaborate closely with developers, product managers, and other stakeholders to integrate AI solutions seamlessly into products.
Stay up to date with AI, ML, and LLM trends, translating them into practical applications.
Provide technical leadership and mentorship to junior data scientists while balancing immediate delivery with long-term innovation.

We are looking for a Data Engineer.
What You'll Do:
Design, build, and maintain data pipelines and infrastructure
Develop and implement data quality checks and monitoring processes
Work with engineers to integrate data into our systems and applications
Collaborate with scientists and analysts to understand their data needs

As a Senior Data Engineer, youll collaborate with top-notch engineers and data scientists to elevate our platform to the next level and deliver exceptional user experiences. Your primary focus will be on the data engineering aspectsensuring the seamless flow of high-quality, relevant data to train and optimize content models, including GenAI foundation models, supervised fine-tuning, and more.
Youll work closely with teams across the company to ensure the availability of high-quality data from ML platforms, powering decisions across all departments. With access to petabytes of data through MySQL, Snowflake, Cassandra, S3, and other platforms, your challenge will be to ensure that this data is applied even more effectively to support business decisions, train and monitor ML models and improve our products.
Key Job Responsibilities and Duties:
Rapidly developing next-generation scalable, flexible, and high-performance data pipelines.
Dealing with massive textual sources to train GenAI foundation models.
Solving issues with data and data pipelines, prioritizing based on customer impact.
End-to-end ownership of data quality in our core datasets and data pipelines.
Experimenting with new tools and technologies to meet business requirements regarding performance, scaling, and data quality.
Providing tools that improve Data Quality company-wide, specifically for ML scientists.
Providing self-organizing tools that help the analytics community discover data, assess quality, explore usage, and find peers with relevant expertise.
Acting as an intermediary for problems, with both technical and non-technical audiences.
Promote and drive impactful and innovative engineering solutions
Technical, behavioral and interpersonal competence advancement via on-the-job opportunities, experimental projects, hackathons, conferences, and active community participation
Collaborate with multidisciplinary teams: Collaborate with product managers, data scientists, and analysts to understand business requirements and translate them into machine learning solutions. Provide technical guidance and mentorship to junior team members.

As a Data Engineer, youll collaborate with top-notch engineers and data scientists to elevate our platform to the next level and deliver exceptional user experiences. Your primary focus will be on the data engineering aspectsensuring the seamless flow of high-quality, relevant data to train and optimize content models, including GenAI foundation models, supervised fine-tuning, and more.
Youll work closely with teams across the company to ensure the availability of high-quality data from ML platforms, powering decisions across all departments. With access to petabytes of data through MySQL, Snowflake, Cassandra, S3, and other platforms, your challenge will be to ensure that this data is applied even more effectively to support business decisions, train and monitor ML models and improve our products.
Key Job Responsibilities and Duties:
Rapidly developing next-generation scalable, flexible, and high-performance data pipelines.
Dealing with massive textual sources to train GenAI foundation models.
Solving issues with data and data pipelines, prioritizing based on customer impact.
End-to-end ownership of data quality in our core datasets and data pipelines.
Experimenting with new tools and technologies to meet business requirements regarding performance, scaling, and data quality.
Providing tools that improve Data Quality company-wide, specifically for ML scientists.
Providing self-organizing tools that help the analytics community discover data, assess quality, explore usage, and find peers with relevant expertise.
Acting as an intermediary for problems, with both technical and non-technical audiences.
Promote and drive impactful and innovative engineering solutions
Technical, behavioral and interpersonal competence advancement via on-the-job opportunities, experimental projects, hackathons, conferences, and active community participation
Collaborate with multidisciplinary teams: Collaborate with product managers, data scientists, and analysts to understand business requirements and translate them into machine learning solutions. Provide technical guidance and mentorship to junior team members.

Were looking for a Senior Data Analyst to help ensure the quality, completeness, and integrity of our foundational data. Youll work closely with data engineers, product managers, and operations teams to monitor pipelines, evaluate new data sources, design performance metrics, and derive insights that improve our entity models and customer outputs.
This role is ideal for a highly analytical and independent thinker who enjoys working with complex data ecosystems and translating messy real-world data into actionable insights.
RESPONSIBILITIES
Data Quality & Metrics
Define and maintain KPIs and quality metrics for POI and chain data accuracy, coverage, and freshness.
Monitor large-scale ingestion and enrichment pipelines, identifying anomalies, data drifts, or source inconsistencies.
Operational Analytics
Design dashboards and tools to track data health, system performance, and SLA compliance.
Provide visibility into the performance of automated systems and manual processes across the Foundation domain.
Cross-functional Collaboration
Work with engineers to validate and optimize merge, enrichment, and geocoding logic.
Partner with product and operations to assess the impact of data changes on downstream systems and customer-facing products.
Exploration & Research
Evaluate new data providers, test hypotheses about data behaviors, and contribute to decision-making for third-party integrations.
Develop data-driven recommendations to improve POI modeling and chain linkage accuracy.

Required Backend Data Engineer
As part of the role you will have the opportunity to:
Build end-to-end development of data infrastructure features, scalable data processing, database interaction and integration with CI/CD.
Take part in expanding our core data platform solutions, build new pipelines from scratch that ingest and process data at scale.
Work across a rich stack of technologies from Apache Kafka, Apache Storm, NoSQL, and relational databases.
Analyze and optimize performance, scalability, and stability of our product environments.
Work closely with the data-science team to implement production grade pipelines based on AI research.

Required Data Team Lead
As part of your role you will have the opportunity to:
Lead, mentor, and manage a team of experienced Data/Backend Engineers responsible for designing, building, and maintaining data infrastructure and data-driven applications
Oversee the planning and execution of the development cycle (e.g., sprints), ensuring timely and high-quality delivery
Define, build, and align the Data team roadmap with the company's product vision and overall R&D strategy
Analyze and optimize performance, scalability, and stability of Data team services
Collaborate effectively with other R&D teams on cross-functional projects and shared infrastructure
Take ownership of production incidents related to the Data domain, ensuring clear communication and effective coordination
Manage team performance and growth through regular 1:1 meetings, constructive feedback, periodic performance reviews, and comprehensive annual evaluations.