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Key Responsibilities: Machine Learning Model Development: Design, implement, and deploy machine learning models to address complex challenges in the insurance domain. Work on diverse projects, leveraging machine learning techniques to extract insights and drive business value. Machine Learning Pipelines: Design and implement ETL processes for Machine Learning to ensure accurate and timely data integration from multiple sources. Build and optimize end-to-end machine learning pipelines, ensuring scalability, efficiency, and maintainability. Collaborate with data engineers to integrate machine learning models into production systems. Artificial Intelligence: Apply knowledge and experience in working with Artificial Intelligence solutions, contributing to the development and deployment of AI-driven models in one or more of the industry like Insurance, Manufacturing, Retail, Telecom, etc Design and deploy AI algorithms, predictive analytics, and natural language processing solutions to enhance underwriting, claims processing, and customer service in the insurance sector, as we'll as optimize production processes and quality control in manufacturing. Data Analysis: Utilize advanced analytical techniques to extract actionable insights from complex datasets. Demonstrate expertise in SQL and Python for data manipulation, analysis, and visualization. Build interactive dashboards using Tableau or PowerBI to visualize data and communicate insights effectively to stakeholders. Innovation and Problem Solving: Thrive in a startup-like environment within the maturity of a big organization. Analyze business problems, design and implement effective solutions, and communicate findings to both technical and non-technical stakeholders. Bring innovative solutions to the table, utilizing AI and machine learning to address business challenges. Timely Project Delivery: Work on projects with tight timelines and deliver high-quality results within the specified deadlines. Demonstrate the ability to manage multiple tasks concurrently and prioritize effectively. Communication & Collaboration: Strong communication skills with the ability to convey complex technical concepts to non-technical stakeholders. Work closely with cross-functional teams, including data scientists, engineers, and business stakeholders, to understand requirements and contribute to the development and deliver high-quality innovative solutions. Continuously research and apply the latest advancements in AI and machine learning to drive innovation, improve efficiency, and maintain a competitive edge in the rapidly evolving landscapes of insurance and manufacturing. Qualifications: bachelors degree in a relevant field (eg, Computer Science, Data Science, AIML). 12+ years of proven experience as a Data Analyst and atleast 4 yrs experience in AIML Experience in working with Artificial Intelligence and Machine Learning is a must Strong proficiency in SQL and Python If you are a self-motivated Data Analyst with strong passion for AI based innovation and a desire to contribute to the evolution of the industry, we invite you to apply. Join us in shaping the future of data-driven AI solutions at the intersection of technology and business.
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.