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Company DescriptionABOUT IQ-EQ Were a leading Investor Services group offering end-to-end services in administration, accounting, reporting, regulatory and compliance needs of the investment sector worldwide. We employ a global workforce of 6,500+ people across 24 jurisdictions and have assets under administration (AUA) exceeding US$857 billion. We work with 13 of the worlds top-15 private equity firms. Our services are underpinned by a Group-wide commitment to ESG and best-in-class technology including a global data platform and innovative proprietary tools supported by in-house experts. Above all, what makes us different is our people.Operating as trusted partners to our clients,we deliver intelligent solutions through a combination of technical expertise and strong relationships based on deep client understanding. Were driven by our Group purpose, to power people and possibilities. Job DescriptionIntroduction We are seeking a passionate and results-driven AI/ML Engineer to design, develop, and deploy machine learning and Generative AI solutions that power next-generation products and services. In this role, you will collaborate with product, engineering, and data teams to build scalable AI systems, intelligent applications, and cloud-native solutions leveraging Machine Learning, Deep Learning, Generative AI, MLOps, and modern software engineering practices to drive innovation and business impact. What You'll Do You'll design, develop, train, optimize, and deploy machine learning and deep learning models, including predictive analytics, recommendation systems, classification models, NLP solutions, and model performance evaluation.You'll prepare and engineer structured and unstructured data, build scalable data pipelines, and collaborate with data engineering teams to ensure data quality, availability, and efficient training and inference workflows.You'll build and enhance Generative AI applications using LLMs, RAG architectures, prompt engineering, intelligent assistants, chatbots, and enterprise productivity solutions.You'll develop scalable backend services, APIs, and reusable AI components while integrating AI solutions with enterprise applications, external tools, and third-party platforms using software engineering best practices.You'll deploy, monitor, and maintain AI/ML solutions in cloud environments, implement CI/CD and MLOps practices, manage the model lifecycle, and partner with cross-functional stakeholders to design scalable, business-driven AI solutions.What We Offer Competitive Compensation: Annual package including base salary, allowances, and performance incentives.Health & Insurance Coverage: Medical insurance, group term life insurance, and accident coverage.Allowances & Support: Transportation allowance, internet allowance, and shift allowance.Paid Time Off: Generous leave policy supporting worklife balance.Career Growth: Exposure to cuttingedge AI/ML technologies and opportunities to work across Generative AI, MLOps, and cloudnative solutions.QualificationsAbout You You hold a bachelor's or master's degree in Computer Science, Artificial Intelligence, Data Science, Information Technology, or a related field, with 3-6 years of experience in AI/ML engineering, data science, or similar roles.You have strong hands-on experience with Python, SQL, machine learning and deep learning frameworks (Scikit-learn, TensorFlow, PyTorch), statistical analysis, feature engineering, and model training, evaluation, and deployment.You possess expertise in Generative AI technologies, including OpenAI/Azure OpenAI, LangChain or LangGraph, RAG architectures, prompt engineering, LLM evaluation, and data processing tools such as Pandas, NumPy, and ETL frameworks.You have experience with databases (PostgreSQL, MySQL, NoSQL), cloud platforms (Azure, AWS, or GCP), and modern DevOps practices using Git, Docker, CI/CD pipelines, and preferably Kubernetes, MLOps tools, and microservices architectures.You demonstrate strong problem-solving, communication, and collaboration skills, with knowledge of Agentic AI, vector databases, Responsible AI, observability tools, and a passion for AI innovation, continuous learning, ownership, and customer-focused delivery.Additional InformationOUR COMMITMENT TO YOU AND THE ENVIRONMENT Sustainability is integral to our strategy and operations. Our sustainability depends on us building and maintaining long-term relationships with all our stakeholders including our employees, clients, and local communities while also reducing our impact on our natural environment. There is always more we can, and should do, to improve whether in relation to our people, our clients, our planet, or our governance. Our ongoing success as a business depends on our sustainability and agility in a changing and challenging global landscape. Were committed to fostering an inclusive, equitable and diverse culture for our people, led by our Diversity, Equity, and Inclusion steering .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.