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Required Data Team Lead
What Youll Do:
As the Team Lead of the Account Management squad, you will guide a multidisciplinary team of backend and data engineers responsible for some of our most critical financial operations. Your mission is to build and scale the systems that keep our loan and card processes accurate, transparent, and resilient while fostering a culture of collaboration, ownership, and technical excellence within the squad.
In this role, youll not only manage talented engineers but also work closely with finance, risk, product, and compliance stakeholders to ensure our technology delivers real business impact. Your teams scope includes payment allocation, disbursement management, and the delivery of loan and card performance data products that support both internal decision-making and external reporting across regulators, partners, and investors.
Key Responsibilities
Lead, mentor, and inspire a high-performing squad of backend and data engineers.
Own and evolve our loan account management systems and data products.
Ensure accuracy and automation in payment allocation and manage disbursement flows.
Deliver high-quality Loan Performance and Card Performance data products used across internal operations, executive dashboards, and external reporting.
Build scalable, reliable systems that support high transaction volumes with full financial integrity.
Partner with finance, risk, product, and compliance to align technology with business goals.

Required Data Infrastructure Engineer
What Youll Do:
Design, implement, and enhance robust and scalable infrastructure that enables efficient deployment, monitoring, and management of machine learning models in production. In this role, you will bridge the gap between research and production environments, streamline data and feature pipelines, optimize model serving, and ensure governance and reproducibility across our ML lifecycle.
Responsibilities:
Decouple data prep from model training to accelerate experimentation and deployment
Build efficient data workflows with versioning, lineage, and optimized resource use (e.g., Snowflake, Dask, Airflow)
Develop reproducible training pipelines with MLflow, supporting GPU and distributed training
Automate and standardize model deployment with pre-deployment testing (E2E, dark mode)
Maintain a model repository with traceability, governance, and consistent metadata
Monitor model performance, detect drift, and trigger alerts across the ML lifecycle
Enable model comparison with A/B testing and continuous validation
Support infrastructure for deploying LLMs, embeddings, and advanced ML use cases
Manage a unified feature store with history, drift detection, and centralized feature/label tracking
Establish a single source of truth for features across research and production across research and production.

We are seeking an AI/ML Lead Engineer to join our R&D division and drive the adoption of advanced machine learning and AI solutions across our financial and operational domains. In this role, you will design and implement intelligent models that increase efficiency in collections and payments processing and build AI-driven tools that enhance call center performance and agent productivity.
We are looking for a hands-on, independent team player with strong foundations in data science, computer science, and backend engineering, combined with excellent analytical and algorithmic skills. This role is diverse and impactful, spanning machine learning development, data analysis, and backend engineering, with the opportunity to shape our AI/ML strategy for servicing and operations.
As part of the R&D group, you will work closely with engineers and product managers, leading and implementing AI/ML initiatives that directly align with our business goals and innovation vision.
Key Responsibilities
Lead the design, development, and deployment of ML models to optimize collections and payments processing.
Develop and integrate AI-driven tools to improve call center efficiency and agent productivity.
Collaborate cross-functionally with engineers, product managers, and stakeholders to translate business needs into technical solutions.
Drive data analysis and modeling efforts, leveraging advanced algorithms to uncover insights and improve decision-making.
Ensure scalability, quality, and compliance of all AI/ML solutions within the financial and servicing domains.
Stay up to date with emerging AI/ML technologies and assess their potential impact on the companys strategy.
Mentor and guide team members, fostering knowledge-sharing and technical excellence.

We are seeking a motivated and skilled Jr. Algorithm Engineer to join our R&D team. The engineer will be part of a team responsible for the core autonomy parts of the product responsible for developing the foundational algorithms that guide our autonomous vehicles. This role is a part of the group that oversees Motion Planning, Decision-Making, Localization, and Control, blending traditional robotics with state-of-the-art AI to solve the most challenging problems in autonomous driving. This is an opportunity to architect and deliver the core autonomy stack for a scalable, mapless L3-L4 system. You will work on cutting-edge algorithms, large-scale models, and see your innovations deployed on public roads in our global fleet of cars and buses. Responsibilities
* Be part of the development of four key domains: Motion Planning and Decision-Making: Oversee the trajectory planner and the decision-making module that sets the context for vehicle behavior. Localization: Guide the development of high-frequency, high-accuracy vehicle state estimation using advanced sensor fusion algorithms. Control: Supervise the design and implementation of the vehicle's lateral and longitudinal controllers.
* Drive innovation by integrating state-of-the-art (SOTA) methodologies, including Agentic AI, transformers, multi-agent prediction, trajectory optimization, uncertainty management, and safety-aware algorithms.
* Be part of a group involving multiple engineers, from initial research and prototyping to robust deployment and validation.
* Be part of a group in charge of complex data pipelines, from collection and annotation to model training and evaluation.