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ROLE OVERVIEW We are looking for an AI / ML Engineer to help build, train, and deploy machine learning models and AI-powered features that drive real business outcomes. You will work on projects involving predictive analytics, NLP, and generative AI integration with hands-on exposure to the full ML lifecycle, from data preparation to deployment, supported by the team as you grow into owning projects end to end. KEY RESPONSIBILITIES 1. Build and train machine learning models for business use cases classification, regression, and NLP. 2. Prepare data for modelling cleaning, preprocessing, and feature engineering. 3. Integrate LLMs (Claude, OpenAI, Gemini) into products and workflows using APIs and prompt engineering. 4. Assist in building RAG-based features embeddings, retrieval, and semantic search. 5. Help deploy models and AI features, and monitor how they perform in real use. 6. Document your work clearly and stay updated with new AI tools and techniques. 7. Build data pipelines for model training clean, transform, and structure raw data. REQUIRED SKILLS Machine Learning & Deep Learning Python (mandatory) NumPy, Pandas, scikit-learnCore ML fundamentals model training, evaluation metrics, and basic statisticsFamiliarity with TensorFlow or PyTorch (either one)Experience working with LLM APIs (OpenAI / Claude / Gemini) and prompt engineeringSQL basics querying and extracting dataGit & GitHub version control basicsGood to have: LangChain / LlamaIndex, vector databases (ChromaDB, FAISS), RAG concepts, Flask / FastAPI, or exposure to any cloud platform. WHAT WE'RE LOOKING FOR 12 years of hands-on ML/AI experience internships, freelance work, and strong personal projects all count.Curious, self-learning mindset AI moves fast and you enjoy keeping up.Ability to communicate your work clearly to non-technical teammates.A portfolio or GitHub with projects youve built academic or personal projects are welcome.WHY JOIN US Work on diverse, real-world AI/ML problems across marketing, automation, and client growth.Access to latest AI tools, APIs, compute resources, and learning budget.Competitive compensation as per Ludhiana market standards with performance upside.High-ownership environment your models and systems will be in production, not shelved.Compensation: 30,000.00 - 50,000.00 per month Benefits: Health insuranceLeave encashmentAbility to commute/relocate: Ludhiana, Punjab (Ludhiana): Reliably commute or planning to relocate before starting work (Preferred)Application Question(s): What is your current CTC What are your salary expectations Experience: Machine learning: 2 years (Preferred)Location: Ludhiana, Punjab (Ludhiana) (Preferred)Work Location: In person .
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.