As a Senior Artificial Intelligence/Machine Learning Engineer, become a part of a cross-functional development team engineering experiences of tomorrow.
Locations (3)
Wrocław, Poland
Gdańsk, Pomerania, Poland
Poland
Responsibilities
Own the ML lifecycle: take models from problem framing through training, deployment and monitoring
Frame problems: turn business goals into ML tasks and metrics. Use plain code where a model isn’t needed
Build models: classical ML, time series and NLP, plus LLM and RAG features where they fit
Evaluate rigorously: sound validation, the right metrics, and evals that gate every release
Ship and run models: deploy with Docker and CI/CD on cloud ML platforms, and monitor drift and cost
The Senior Developer, AI is responsible for designing, developing, deploying, and supporting enterprise AI solutions including scalable AI applications, AI agents, and RAG solutions using Databricks.
Responsibilities
Design, build, test, deploy, and support scalable enterprise AI applications, AI agents, and intelligent workflows using Databricks and cloud-native technologies.
Develop AI agents, multi-agent workflows, and RAG solutions by integrating enterprise data, APIs, tools, and business processes to enable automation and decision support.
Create APIs, backend services, integrations, and reusable frameworks while applying software engineering best practices such as CI/CD, automated testing, monitoring, and secure deployment.
Drive solution reliability, performance, Responsible AI compliance, data governance, operational readiness, and continuous improvement through testing, evaluation, and technical reviews.
Partner with business stakeholders, Product Owners, Architects, Data Scientists, Data Engineers, platform teams, and vendors while providing technical guidance, knowledge sharing, and mentoring across AI Delivery PODs.
Architecte Data / IA Services Financiers responsable de la définition, industrialisation et déploiement d’architectures Data & IA pour les services financiers, en assurant conformité réglementaire et performance.
Compensation
Rémunération : En fonction du profil
Responsibilities
Définir des architectures Data & IA : data mesh, feature stores, plateformes MLOps, scoring, pricing et IA générative
Industrialiser les solutions en garantissant passage à l’échelle, performance, résilience et maîtrise des coûts
Traduire les exigences de l’AI Act, DORA, ACPR, RGPD, Bâle et Solvency en choix de conception
Garantir l’explicabilité, la traçabilité, la robustesse et le contrôle des biais des modèles
Intégrer les contraintes des métiers : risques, conformité, anti-fraude, KYC/AML, marketing, relation client, actuariat et trading
Requirements
Master's degree (Bac+5) in Engineering or Business School with strong technical specialization
მოდელების რისკების მართვის გუნდში მუშაობა, სტატისტიკური, მანქანური სწავლების და GenAI მოდელების ვალიდაცია, რეპორტების მომზადება და მოდელების რეგისტრაცია.
Responsibilities
მოდელების რისკის დონის შეფასება არსებული პოლიტიკისა და სტანდარტების მიხედვით
ახალი და არსებული მოდელების ვალიდაცია
ვალიდაციის შედეგების დეტალური რეპორტების მომზადება
მოდელების რეგისტრაციისა და მართვის პროცესის უზრუნველყოფა
Lead technical vision and architecture for AI/ML solutions across AstraZeneca’s commercial landscape, guiding advanced AI from traditional ML to generative and agentic AI, while influencing multi-functional teams and ensuring production readiness.
Responsibilities
Define and drive technical vision, roadmap and architecture for AI capabilities
Provide hands‑on technical leadership to project teams
Lead design of multi‑agent systems and LLM applications
Establish evaluation standards and quality gates
Drive model optimization and cost/latency improvements
Requirements
Bachelor's degree in Computer Science or related quantitative field
Master's or PhD in machine learning, computer science or related field
A senior data science role focused on AI/LLM systems, agentic product performance, and scalable AI solutions, bridging the gap between technical metrics and business objectives.
Locations (2)
Tel Aviv, Tel Aviv, Israel
Herzliya, Central District, Israel
Responsibilities
Collaborates with relevant partners on defining metrics and frameworks for evaluating complex AI/large language model (LLM) systems and agentic product performance.
Diagnoses complex issues and identifies opportunities to drive improvements within AI/LLM systems.
Prototypes and deploys applications of AI models using containerized environments (e.g., AI Azure Foundry, LangChain).
Optimizes scalable systems that use optimal context engineering (e.g., retrieval-augmented generation) workflows.
Drives AI system roadmaps through continual assessment of model performance and refinement of LLM systems and models.
A highly technical, hands-on role at the intersection of Enterprise AI and client-facing architecture. The role involves writing production-grade solution blueprints alongside strategic customers and deivering repeatable, extensible, and open-sourced AI Quickstarts to solve complex operational bottlenecks in the APAC region.
Responsibilities
Design and build comprehensive, production-ready architecture blueprints and reference codebases.
Package repeatable, extensible technical architectures as open-sourced AI Quickstarts.
Collaborate with external engineering teams (semiconductor partners, regional AI programs, and software vendors) to validate joint-architecture blueprints.
Design and integrate automated testing, evaluation harnesses, and system-level telemetry into blueprints.
Proactively incorporate robust data privacy standards, secure network perimeters, and localized hosting considerations into solution blueprints.
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