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WHO WE ARE: Zinnia is the leading technology platform for accelerating life and annuities growth. With innovative enterprise solutions and data insights, Zinnia simplifies the experience of buying, selling, and administering insurance products. All of which enables more people to protect their financial futures. Our success is driven by a commitment to three core values: be bold, team up, deliver value and that we do. Zinnia has over $180 billion in assets under administration, serves 100+ carrier clients, 2500 distributors and partners, and over 2 million policyholders. WHO YOU ARE You are a passionate Python and AI/ML Engineer minimum 5 years of hands-on experience building intelligent systems. You thrive in fast-paced environments, love solving complex problems with data and algorithms, and take pride in delivering AI solutions that create real business impact. You have experience with cutting-edge Generative AI, scalable ML pipelines, and production-grade systems and you're energized by working at the frontier of what AI can do. WHAT YOU'LL DO - Design, develop, and deploy machine learning models and Generative AI solutions including classification, clustering, summarization, search & ranking, and information extraction. - Own end-to-end ML pipelines from data ingestion and preprocessing through model training, deployment, and production monitoring. - Collaborate with cross-functional teams to translate business requirements into AI-driven features applying NLP, outlier detection, and deep learning techniques where applicable. - Build robust, scalable, and well-documented Python-based RESTful APIs to expose ML models and AI services in production environments. - Optimize database interactions and ensure efficient data storage and retrieval for AI applications across SQL and NoSQL systems. - Stay current with the latest advances in AI/ML integrating emerging approaches such as RAG pipelines, LLM fine-tuning, and vector search into live products. WHAT YOU'LL NEED Python Robust hands-on proficiency for building, scripting, and deploying AI/ML systems. NumPy Pandas FastAPI Scikit-learn Machine Learning Applied expertise across supervised, unsupervised, and deep learning classification, clustering, outlier detection. PyTorch TensorFlow XGBoost DBSCAN Generative AI (2+ yrs) Hands-on experience building with LLMs prompt engineering, RAG pipelines, summarization, and AI-powered features. LLMs RAG Prompt Eng. Fine-tuning NLP & Search / Ranking Processes language and builds relevance engines NER, embeddings, semantic search, and ranking models. spaCy BERT FAISS Elasticsearch API Development Designs and ships secure, well-documented RESTful APIs exposing ML models as production-ready services. REST FastAPI OAuth2 Swagger Databases Proficient in SQL and NoSQL stores for structured and unstructured data pipelines supporting AI workloads. PostgreSQL MongoDB Vector DBs GOOD TO HAVE Cloud Platforms Deploys and scales AI workloads on AWS, Azure, or GCP. AWS Azure TypeScript / JavaScript Frontend or full-stack exposure for building ML-powered product interfaces. TypeScript React Node.js MLOps Manages the ML lifecycle tracking, versioning, and pipeline automation. MLflow Kubeflow CI/CD Containerization & Orchestration Packages and scales AI services using containers and cluster management. Docker Kubernetes .
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.