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Tech Stack
Tools & technologiesCloud
About the role
Key responsibilities & impact- Own end-to-end delivery of AI features across model, backend, APIs, UI integration, deployment, monitoring, and iteration in production
- Solve complex challenges with AI/ML: Design, develop new AI-powered products that deliver the product roadmap, including agentic AI solutions that orchestrate LLMs, tools, and workflows to solve multi-step problems autonomously.
- Implement ML lifecycle - from data engineering and model development to cloud-based deployment, integrations and operationalisation. Incl. MLOps
- Productionise full-stack AI/ML solutions: Translate emerging techs like GenAI& agenticAI architectures into innovative, practical solutions that transform customer experiences.
- Align with Product Strategy: Create proof of concepts at high cadence to demonstrate/validate potential solutions as per our product strategy.
- Optimise Model and system performance: Fine-tune, optimise training and inference performances, including latency, cost, and reliability trade-offs in agent-based and LLM-driven systems.
- Wider collaboration: Partner with cross-functional teams to demonstrate and validate the impact of ML innovations before introducing them into the product ecosystem.
- Research Savvy: Staying up-to-date with SOTA and industry trends in AI/ML, with a strong awareness of advances in agentic systems, autonomous workflows, and multi-agent architectures.
Requirements
What you’ll need- Master’s or PhD in AI/ML or a related field
- At least 6+ years of experience building software or AI systems, including 1–3 years working with LLMs, generative AI, or AI agent architectures.
Benefits
Comp & perks- An excellent workplace culture
- Competitive salary
- Company performance-related bonus
- Medical insurance
- Flexible working hours
- Educational assistance
- In-house soft skills training
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
AI features deliveryAI/ML product developmentMLOpsdata engineeringmodel developmentcloud-based deploymentfull-stack AI/ML solutionsmodel optimisationinference performance tuningagent-based systems
Soft Skills
problem-solvingcollaborationcommunicationresearchinnovationstrategic alignmentvalidationadaptabilitycreativitycross-functional teamwork
Certifications
Master’s in AI/MLPhD in AI/ML
