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Job Title: Machine Learning Engineer - Artificial Intelligence Company: Skima Innovation Private Limited Experience: 3 - 5 Years Skills: Machine Learning, Artificial Intelligence, Python, SQL, Deep Learning, Tensorflow, AWS, Google Cloud Platform Description: Job Description :Machine Learning EngineerLocation : Mumbai (Andheri East), India (In-Office)Experience : 3+ YearsAbout Skima Innovation :At Skima, we don't just build models; we build the future. We are a dynamic team dedicated to pushing the boundaries of what's possible through data-driven innovation. We are looking for a talented Machine Learning Engineer who is ready to take ownership of end-to-end ML lifecycles and transform complex data into scalable, real-world solutions.The Role :As an ML Engineer at Skima, you will sit at the intersection of data science and software engineering. You won't just be "playing with data" - you will be designing, developing, and deploying high-performance models that drive our core products. You will work in a collaborative environment where your algorithms directly impact business outcomes.Key Responsibilities :- Production Pipelines: Architect and manage automated ML implementation pipelines for seamless transition from research to production.- Deep Learning Deployment: Optimize and deploy large-scale Deep Learning models using specialized inference engines.- Containerization & Orchestration: Package ML services using Docker and manage deployments via Kubernetes to ensure high availability and scalability.- MLOps Mastery: Establish CI/CD for ML, implementing automated testing, versioning (DVC), and model registry workflows.- Model Observability: Implement comprehensive monitoring for model drift, data integrity, and real-time performance latency.- Optimization: Fine-tune models for resource efficiency, focusing on quantization and pruning for production-grade inference.What You Bring :- Experience: 3+ years of hands-on experience in ML engineering with a focus on production-grade deployments.- MLOps Stack: Proficiency with tools like MLflow, Kubeflow, W&B for managing the model lifecycle.- Cloud & Infrastructure: Strong experience with AWS/Azure/GCP ML services and containerized environments.- Technical Depth: Expert-level Python and deep familiarity with PyTorch or TensorFlow. .
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.