• Set long-term technical direction for Kraken’s AI/ML strategy, influencing multiple teams and initiatives. • Own the architecture and evolution of core AI/ML systems, including training, feature management, serving, experimentation, and monitoring. • Lead cross-team efforts to standardize ML development and operational practices across the company. • Drive the design and delivery of complex, high-impact ML systems for use cases such as fraud, risk, personalization, and recommendations. • Partner with senior engineering, product, and data leaders to identify where ML can unlock step-change improvements in scalability and efficiency. • Balance hands-on technical contributions with architectural leadership and design review responsibilities. • Evaluate emerging ML and GenAI technologies and lead their adoption when they provide durable platform-level value. • Mentor Staff and Senior engineers, shaping technical culture and raising the overall quality of ML engineering at Kraken.

• Guide the technical direction of Bondora’s ML engineering stack by selecting, evaluating, and implementing technologies, tools, and processes that improve scalability and reliability. • Lead complex, high risk, or cross departmental projects that directly influence Data Science delivery, risk model performance, and production stability. • Act as the bridge between Data Science, Data Engineering, and Development to identify and solve systemic technical challenges. • Design and build advanced, production grade ML infrastructure and set the engineering standard for the team. • Ensure all ML solutions are secure, observable, resilient, and scalable, following governance, compliance, and operational best practices. • Mentor ML Engineers through code reviews, design sessions, and hands on technical leadership. • Identify weaknesses or inefficiencies in model or data infrastructure and drive company wide improvements. • Represent the ML Engineering team in technical discussions and communicate architectural decisions clearly to stakeholders.

• Design, build, and optimize algorithm in Vertex ai. • Develop scalable data models, Algorithm supporting user 360 views, churn prediction, and recommendation engine inputs. • Lead integration across data sources: MySQL, BigQuery, Redis, Kafka, GCP Storage, and API Gateway. • Implement CI/CD for data pipelines using Git, dbt, and automated testing. • Define data quality checks and auditing pipelines for ingestion and transformation layers. • Mentor and guide junior AI/ML engineers on data modeling, algorithm performance tuning. • Partner with Data Science, ML, and Backend teams to productionize machine learning features in Snowflake. • Work closely with Legal, Security, and Infrastructure teams to ensure compliance, privacy, and governance of user data (PII). • Collaborate with the Director of Data Platforms and product stakeholders to translate business requirements into technical specifications. • Tune algorithm performance. • Establish data partitioning, clustering, and materialized views for fast query execution. • Build dashboards and monitors for pipeline health, job success, and data latency metrics (e.g., via Looker, Tableau, or Snowsight). • Establish and enforce naming conventions, data lineage, and metadata standards across schemas. • Lead code reviews, enforce documentation standards, and manage schema versioning. • Contribute to the company’s evolving data mesh and streaming architecture vision.

• Build the team vision: Partner with cross-functional leaders to define key business challenges and design AI-first solutions that unlock substantial value for customers and stakeholders. • Drive hands-on execution: Lead the development of personalized content and recommendation systems by leveraging a mix of generative and traditional machine learning architectures to drive core business outcomes. • Deploy AI systems at scale: Drive end-to-end software development, including building ML services, agentic workflows, managing experiment lifecycles, and deploying production-ready AI solutions at scale. • Innovate: Stay at the cutting edge of AI innovation by conducting literature reviews and exploring novel paradigms in recommendation systems (RecSys). Identify opportunities for customization and apply these advancements to meet Instacart’s unique needs. • Elevate the team: Mentor and guide junior team members, fostering learning, engagement, and technical growth within the team.