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We are looking for a Senior Associate AI/ML Engineer to build, deploy, and maintain AI/ML solutions using text, image, audio, and video data. The role involves developing ML models, RAG solutions, AI pipelines, APIs, and production-ready services. The candidate will also work on model optimization, MLOps, cloud deployment, and mentoring junior engineers. Key Responsibilities Develop and deploy ML models for NLP, Computer Vision, OCR, and Speech. Build AI pipelines for text, image, audio, video, and document processing. Develop LLM and RAG-based solutions. Work with vector databases and semantic search. Optimize models for performance, latency, scalability, and cost. Deploy AI solutions using Docker, Kubernetes/AKS, and FastAPI. Build and maintain ML CI/CD pipelines using GitHub Actions, Azure DevOps, or Jenkins. Use Azure Machine Learning for model training, tracking, registration, and deployment. Monitor AI/ML models using tools such as Prometheus and Grafana. Integrate AI services with enterprise applications such as search, recommendation, document, and content platforms. Develop and maintain AI inference and retrieval APIs. Collaborate with data, backend, platform, and product teams. Review code, document solutions, and mentor junior engineers. Required Skills Strong knowledge of Python. Experience with PyTorch and/or TensorFlow. Hands-on experience in NLP, Computer Vision, OCR, or Speech. Experience with LLMs and Generative AI. Knowledge of LangChain, LlamaIndex, or similar frameworks. Experience with RAG and vector search. Knowledge of FAISS, Pinecone, Weaviate, or Azure AI Search. Experience with Docker and Kubernetes. Understanding of CI/CD and MLOps. Experience with cloud-based AI/ML deployment. Preferred Skills Experience with Azure OpenAI and Azure Machine Learning. Knowledge of Azure Data Lake or similar data services. Experience with real-time inference or streaming data. Experience with distributed ML systems. Knowledge of model monitoring and drift detection. Education & Experience Bachelor's or Master's degree in Computer Science, AI/ML, Data Science, or a related field. Relevant experience in AI/ML Engineering or Generative AI. Good communication, problem-solving, and teamwork skills. Job Types: Full-time, Permanent Compensation: 500,000.00 - 2,500,000.00 per year Application Question(s): Are you available immediately Experience: RAG: 6 years (Preferred) MLOps: 6 years (Preferred) Azure: 6 years (Preferred) Python: 6 years (Preferred) Machine learning: 6 years (Preferred) Deep learning: 6 years (Preferred) PyTorch: 6 years (Preferred) Computer vision: 6 years (Preferred) Generative AI: 6 years (Preferred) Work Location: Remote .
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.