AI Engineer

• Build customer-facing and internal product features end to end.
• Develop web flows, backend APIs, admin tools, dashboards and operational systems.
• Support products across insurance, payments, savings, investing, travel and financial services.
• Work with product, design, mobile and operations teams to launch fast.
• Integrate APIs, handle data flows and improve production reliability.
• Use analytics, feedback and production issues to improve features after launch.
• Help build tools that reduce manual work and improve speed across the business.

Full Stack Software Engineer – AI Neobank App

• Build AI agents, workflows, tools and automations that solve real customer, product and operations problems.
• Apply LLMs, retrieval, tool calling, evaluations, guardrails and automation to practical financial workflows.
• Create AI-assisted experiences for onboarding, support, KYC, risk review, CRM, operations, document handling and product intelligence.
• Work with product and engineering teams to identify what is worth building, then build it quickly and improve it in production.
• Design around real constraints: accuracy, hallucination risk, latency, cost, security, compliance and user trust.
• Turn manual processes into reliable AI-enabled systems that can scale.

Applied AI Engineer

• Build AI-powered workflows, assistants, agents and automation systems.
• Apply AI across customer support, CRM, onboarding, claims, renewals, payments, operations and internal tools.
• Work with product and engineering teams to turn manual processes into scalable AI-native systems.
• Build integrations with LLMs, internal data, APIs, documents, knowledge bases and business systems.
• Design evaluation, monitoring and fallback flows so AI outputs are useful, safe and reliable.
• Prototype quickly, test with users or operators, then productionize what works.
• Improve speed, quality and consistency across workflows using AI where it creates real business value.

Applied AI Engineer – AI Neobank App

• Build and ship Android features using Kotlin.
• Create clean mobile flows for insurance, payments, claims, renewals and financial services.
• Work with product and design to simplify complex user journeys.
• Integrate backend APIs and ensure mobile flows are stable, secure and reliable.
• Improve app performance, crash rate, loading states, responsiveness and memory usage.
• Use analytics, user behaviour and production issues to improve the product.
• Build AI-assisted mobile experiences only where they genuinely improve the user journey.

Mobile Developer – AI Neobank App

Machine Learning Engineer

• Token Factory is a part of Nebius Cloud, one of the world's largest GPU clouds, running tens of thousands of GPUs.
• We are building a high-performance inference and fine-tuning platform designed to push foundation models to their hardware limits.
• Our mission is to maximize throughput, minimise latency, and optimise cost-per-token across tens of thousands of GPUs.
• Inference Optimization: Identifying LLM inference bottlenecks to drive production speedups.
• Squeezing the maximum performance for a wide range of LLM architectures at scale (e.g., GPT-OSS, Kimi K2.5, DeepSeek V3.1/V3.2, GLM-5).
• Inference engines support: Implement novel speculative decoding architectures, optimise components of various LLM designs (dense/MoE, autoregressive/parallel), and contribute to open-source inference engines.
• Low Precision Training & Inference: Design and productionise low-precision (FP8, NVFP4/MXFP4) training and inference pipelines with measurable gains in throughput and cost-efficiency.

Senior ML Engineer – Token Factory

AI Research Scientist

• Design and implement downstream AI models that operationalize clinical endpoints using outputs from foundation models.
• Translate clinical study designs and outcome definitions into clear modeling tasks and evaluation frameworks in collaboration with Clinical Scientists.
• Define and apply consistent modeling and evaluation approaches across multiple biomarkers and imaging modalities.
• Collaborate closely with the AI Algorithm Lead to ensure robust integration between foundation models, MLOps infrastructure, and downstream biomarker models.
• Guide and review modeling approaches developed by AI Research Scientists, providing technical feedback and mentorship.
• Perform in-depth model analysis, including calibration, subgroup performance, and failure-mode assessment.

AI Research Engineer

• Design, develop, and maintain generative AI services and reusable components using mostly Python and a little bit of Java.
• Define and promote best practices in engineering, including scalability, observability, testing, and CI/CD.
• Contribute to system designs spanning multiple services and modules, aligning with architectural best practices.
• Collaborate with product, platform, and research teams to translate AI prototypes into production-ready capabilities.
• Work within a Kubernetes (EKS) environment to deploy scalable, containerized applications.
• Contribute to the resolution of complex technical challenges across distributed systems.
• Mentor less-senior developers on engineering principles, GenAI patterns, and platform development.
• Participate in code reviews, architecture sessions, and cross-team initiatives to ensure quality and maintainability.
• Stay informed of the latest developments in generative AI and advocate for responsible integration into product ecosystems.

Senior Software Engineer – AI Engineering

• Take up a tech lead role on a per-project basis
• Design and build robust software systems for end-to-end (Gen)AI solutions
• Ensure the scalability of deployed systems
• Lead teams of engineers and translate business challenges into technical solutions

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