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Work Flexibility: Hybrid or Onsite What You Will Do:Lead the end-to-end development of critical AI subsystems in healthcare, from algorithmic direction through implementation, validation, optimization, and deployment readiness. Translate business and open-ended requirements into clear technical strategies and execution plans. Drive agent-assisted development by leveraging agentic AI to accelerate execution while maintaining accountability for technical outcomes. Critically review AI-generated code and artifacts to ensure technical rigor, quality, and reliability. Design and implement scalable, high-performance AI/ML and computer vision solutions. Oversee model evaluation, inference optimization, and deployment for real-world applications. Collaborate with cross-functional, different geographically located teams to deliver robust AI solutions aligned with business and regulatory requirements. Identify technical risks early and ensure timely, high-quality delivery of AI subsystems. What You Need:Required Qualifications- Bachelors or Masters degree in Computer Science, Artificial Intelligence, Machine Learning, Electrical Engineering, or a related field. 1217 years of experience in AI/ML, computer vision, deep learning, or AI systems engineering. Strong foundations in algorithms, system design, software engineering, model evaluation, and optimization. Advanced programming expertise in Python with hands-on experience in PyTorch or TensorFlow. Experience with inference optimization and deployment using TensorRT, ONNX, or OpenVINO. Familiarity with cloud platforms such as AWS or Azure and ML services such as AWS SageMaker or Azure ML. Preferred Qualifications- Experience leading agentic AI workflows or teams and reviewing AI-generated code and artifacts. Experience in the medical/healthcare domain or shipping AI/ML products in regulated environments with validation and risk management requirements. Travel Percentage: 10% .
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.