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Our client is looking for a passionate Machine Learning Engineer to join a rapidly growing AI team focused on building production-ready AI solutions that deliver real-world impact. This is an exciting opportunity to work on cutting-edge AI systems, large language model applications, AI agents, MLOps, and cloud-native machine learning platforms while collaborating with experienced data, engineering, and DevOps professionals. This role is ideal for someone who enjoys moving beyond experimentation and building scalable AI products that reach production environments. Key Responsibilities Design, build, deploy, and maintain production machine learning solutions Develop AI-powered applications, automation solutions, and intelligent agents Build and optimise data pipelines, model training pipelines, and inference workflows Implement MLOps best practices including CI/CD, monitoring, deployment, and scaling Work with AWS-based cloud infrastructure to support AI applications Develop and maintain APIs and AI services Collaborate with data scientists, engineers, and business stakeholders Contribute to AI platform engineering and internal AI product development Support the deployment of solutions into an AI marketplace environment Requirements Bachelor's Degree in Computer Science, Engineering, Software Engineering, Applied Mathematics, Statistics, or a related field 2+ years' experience in Machine Learning, Data Science, or Data Engineering 2+ years' experience developing software in Python Strong SQL skills Minimum 1 year of hands-on AWS experience (essential) Experience with model training, deployment, monitoring, and MLOps practices Experience building scalable ML infrastructure and AI-powered applications Strong software engineering principles and coding best practices Excellent communication skills and stakeholder engagement ability Highly Advantageous AWS certifications Experience with AWS Bedrock and Bedrock AgentCore Open-source contributions or startup experience Master's or PhD in AI, Machine Learning, or related fields Only shortlisted candidates will be contacted. Submit your CV to [Email Address Removed] or call [Phone Number Removed]; . Visit our website for more exciting career opportunities: [URL Removed] Correspondence will only be conducted with short listed candidates. Should you not hear from us within 4 days, please consider your application unsuccessful. Desired Skills: Strong SQL Excellent communication takeholder engagement ability Machine Learning Engineer (Intermediate / Senior)
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.