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Technology is our how. And people are our why. For over two decades, we have been harnessing technology to drive meaningful change.
By combining world-class engineering, industry expertise and a people-centric mindset, we consult and partner with leading brands from various industries to create dynamic platforms and intelligent digital experiences that drive innovation and transform businesses.
From prototype to real-world impact - be part of a global shift by doing work that matters.
Job Description
Are you passionate about translating complex business challenges into cutting-edge AI solutions? We're seeking a hands-on AI/ML Engineer / Senior Engineer to join our team.
This role is at the cutting edge of applied AI - it's an opportunity to be a core builder. You will be responsible for designing, developing and deploying AI agents leveraging Google’s Vertex AI ecosystem — and building solutions that around sophisticated machine learning models to cutting-edge Agentic AI for our clients.
The ideal candidate should have hands-on experience with machine learning algorithms, deep learning frameworks, and cloud-based ML solutions (preferably on Google Cloud stack).
What You'll Design & Own
- Design End-to-End AI Solutions:
Translate complex business problems into scalable, secure, and robust technical architectures. You will be the primary designer for solutions leveraging Agentic AI, LLMs, and advanced RAG. - Build and fine-tune agentic logic using Google's Gemini models and the Vertex AI platform. Develop sophisticated prompting strategies (e.g., ReAct, CoT) and evaluation frameworks.
- Get your hands dirty. Write high-quality, efficient code to build and train machine learning models and complex AI systems.
- Be a key player in developing innovative Agentic AI solutions, creating systems that can reason, plan, and act on complex tasks.
- Own the full model lifecycle. You will be responsible for deploying models into production environment, monitoring their performance, and iterating (MLOps).
- We are looking for a blend of technical depth, engineering rigor, and creative problem-solving.
- Hands-on experience in building and deploying machine learning models.
- Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, Data Science, AI, or a related quantitative field.
- Programming:
Expert-level proficiency in Python. - ML Frameworks:
Deep, practical experience with ML libraries like Scikit-learn, TensorFlow, and/or PyTorch and ML algorithms like classification, regression, clustering, reinforcement learning. - GenAI & Agentic AI:
Demonstrable experience with Large Language Models (LLMs), prompt engineering, and frameworks like LangChain, LlamaIndex, or similar. - Data Stack:
Strong skills in data manipulation and analysis using SQL, Pandas, and NumPy. - Deployment & MLOps:
understanding of MLOps principles. Hands-on experience with containerization (Docker, Kubernetes) and deploying models as scalable APIs (e.g., FastAPI, Flask). - Cloud Experience:
experience building and deploying solutions on at least one major cloud platform (GCP (Preferred), AWS, or Azure).
- Experience designing multi-agent systems or autonomous workflows.
- Hands-on experience with Google Cloud Platform.
- Publications, conference speaking, or open-source contributions in the AI/agent space.
Discover some of the global benefits that empower our people to become the best version of themselves:
- Finance:
Competitive salary package, share plan, company performance bonuses, value-based recognition awards, referral bonus; - Career Development:
Career coaching, global career opportunities, non-linear career paths, internal development programmes for management and technical leadership; - Learning Opportunities:
Complex projects, rotations, internal tech communities, training, certifications, coaching, online learning platforms subscriptions, pass-it-on sessions, workshops, conferences; - Work-Life Balance:
Hybrid work and flexible working hours, employee assistance programme; - Health:
Global internal wellbeing programme, access to wellbeing apps; - Community:
Global internal tech communities, hobby clubs and interest groups, inclusion and diversity programmes, events and celebrations.
Key Skills
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