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Job Description: We are looking for a Machine Learning Engineer to join the Data Science team with the Analytics and AI division. You will work with the team to develop and deploy machine learning models across a variety of healthcare products and domains. About you: You love to own important work and find it difficult to turn down a good challenge. You are excited about the latest developments in ML and keep abreast of the latest methods and technologies. You have experience building and evaluating ML models. You have strong communication skills and can work with colleagues from a variety of technical and non-technical backgrounds. Finally, you have a strong interest in improving healthcare. About the team: The data science team is bringing machine learning to bear against the hardest problems in healthcare. We are working with product and engineering leaders across the company to build machine learning into our Best In KLAS suite of products. We work hand-in-hand with platform engineers to deploy state-of-the-art machine learning models using cloud technologies. Job Responsibilities: As a member of the Data Science team, you are expected to work on projects within scrum teams of 2-4 people and execute the following: - Identify opportunities for different machine learning techniques and evaluate which are best - Assist in developing and deploying ML-based production services to our clients - Understand and follow conventions and best practices for modeling, coding, architecture, and statistics; and hold other team members accountable for doing so - Apply rigorous testing of statistics, models, and code - Contribute to the development of internal tools and data science team standards Typical Qualifications: - Bachelors or Masters in relevant field: Math, Computer Science, Data Science, Statistics, or related field - 3-5 years of professional hands-on experience in developing, evaluating & deploying machine learning models - Experience with Python, SQL , Unix - Experience with development and implementation of Deep Learning Models with complex neural network architectures is a bonus - Experience with training & fine tuning LLMs & GenAI models is a bonus. - Familiarity with NLP or computer vision techniques - Experience using the AWS ecosystem a bonus, including Kubernetes, Kubeflow or EKS experience - Excellent verbal communication and writing 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.