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Job Role:- AI Research Engineer Job Location:- Bengaluru, India Experience:- 3-5+ Years Role Summary:-We are seeking an AI Research Engineer to design, develop, and deploy scalable machine learning systems and AI-powered features. The role focuses on building LLM, computer vision, and multimodal machine learning pipelines, deploying models into production, and improving system reliability, performance, and cost efficiency. Key Responsibilities:- Design and develop AI features from data ingestion through real-time model inference.Build scalable, cost-efficient, and observable machine learning systems and services.Develop training and inference pipelines for LLM, computer vision, and multimodal AI models.Create model evaluation frameworks, including offline evaluation, online experiments, and user feedback integration.Collaborate with software engineering, data, and product teams to deliver AI-powered features.Deploy, monitor, and maintain machine learning models using containerised and cloud-based infrastructure.Investigate production incidents, improve system reliability, and optimise operational performance.Optimise training and inference costs through batching, quantisation, mixed precision, and GPU resource management.Required Skills:-Strong proficiency in Python and machine learning frameworks such as PyTorch or TensorFlow.Experience building end-to-end machine learning pipelines, including data preparation, training, evaluation, deployment, and monitoring.Knowledge of MLOps tools such as MLflow, Weights & Biases, DVC, Airflow, or Prefect.Experience with Docker, Kubernetes, containerised deployments, and CI/CD practices.Understanding of GPU optimisation, ONNX, TensorRT, batching, and mixed precision techniques.Familiarity with vector databases, retrieval-augmented generation (RAG), and LLM fine-tuning approaches.Knowledge of observability and monitoring tools such as Prometheus, Grafana, or OpenTelemetry.Strong analytical, problem-solving, and collaboration skills.Qualifications & Experience:-Bachelors or Masters degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.35+ years of experience in applied machine learning, AI engineering, or software engineering.Experience developing and deploying production-grade machine learning applications.Understanding of statistics, experimentation, model evaluation, and real-world performance analysis.Preferred Attributes:_Hands-on experience with LLMs, computer vision, or multimodal AI systems.Ability to balance research innovation with production engineering requirements.Strong ownership mindset and experience working in cross-functional teams.Excellent communication and technical documentation skills .
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.