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AIML Engineer - Data Scientist 5+ Years The candidate will be required on Deqodes payroll. Must Have Skills- White box / black box models, python, Classification Modeling & Logistic Regression Delivery of key Advanced Analytics/Data Science projects within time and budget, particularly around DevOps/MLOps and Machine Learning models in scope Collaborate with data engineers and ML engineers to understand data and models and leverage various advanced analytics capabilities Ensure on time and on budget delivery which satisfies project requirements, while adhering to enterprise architecture standards Use big data technologies to help process data and build scaled data pipelines (batch to real time) Automate the end-to-end ML lifecycle with Azure Machine Learning and Azure Pipelines Setup cloud alerts, monitors, dashboards, and logging and troubleshoot machine learning infrastructure Automate ML models deployments Qualifications: 4 7 years of overall experience that includes at least 4+ years of hands-on work experience data science / Machine learning Minimum 4+ year of SQL experience Experience in DevOps and Machine Learning (ML) with hands-on experience with one or more cloud service providers (Azure preferred) is preferred BE/BS in Computer Science, Math, Physics, or other technical fields. Skills, Abilities, Knowledge: Data Science Hands on experience and robust knowledge of building machine learning models. Update from the hiring team: Candidate must have 4+ years of experience and must have worked on both classification and regression white box/ black box models. Keywords: OLS, Linear regression, Logistic regression, XGBoost, GBM. Disclaimer : This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying. .
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.