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Hi All, Hiring skilled Data Scientist/AI Engineer with healthcare domain expertise for our leading client. Interested candidate can drop resume to sudebi.basu@orcapod.work Experreince-5+ years Skill- AI/ML with SLM knowledge (Small Language Models) Work Mode-WFO Work location- Chennai/Bangalore/Hyderabad Notice period- Immediate to 30 days max Role & responsibilities Architecture & Strategy - Define and own the enterprise architecture, standards, and roadmap for Small Language Model (SLM) development. - Design domain-specific SLMs optimized for accuracy, latency, cost, and scalability. - Drive architectural decisions for model selection, fine-tuning, compression, and inference optimization. - Ensure alignment of AI solutions with enterprise security, compliance, and governance requirements. Advanced Model Development - Lead the design, development, and deployment of ML, DL, and SLM-based solutions. - Apply deep mathematical and statistical knowledge to optimize model performance. - Demonstrate successful delivery of multiple production deployments with measurable business impact. - Provide architectural oversight for traditional ML, deep learning, and NLP-based systems. NLP & Language Modeling - Architect and guide solutions involving NLP, embeddings, transformers, and language models. - Lead fine-tuning and adaptation of language models for domain-specific use cases. - Establish best practices for prompt engineering, evaluation metrics, and performance monitoring. Technical & Platform Leadership - Provide technical authority in Python, scientific computing, and data processing frameworks. - Guide teams on the effective use of TensorFlow, PyTorch, and Keras. - Ensure high-quality analytical data access through complex and optimized SQL designs. - Oversee development in Linux and GPU-based environments. Cloud, MLOps & Production Readiness - Architect and govern ML/AI solutions on AWS or Azure platforms. - Define and enforce MLOps standards, including CI/CD, model versioning, monitoring, and lifecycle management. - Ensure reliability, scalability, and maintainability of AI systems in production. Leadership & Mentorship - Act as Principal Architect and technical mentor for Data Scientists and ML Engineers. - Lead design reviews, technical decision forums, and architectural governance boards. - Collaborate closely with product, engineering, security, and compliance stakeholders. - Drive innovation while ensuring delivery discipline in Agile environments. Preferred candidate profile - Solid foundation in ML algorithms: Random Forest, SVM, Regression models, Boosting & Bagging - Deep learning expertise: CNN, RNN, LSTM, GRU - Advanced NLP and language model experience - Expert-level Python programming - Cloud-based ML architecture and deployment - Enterprise AI governance and best practices Preferred / Nice to Have - Experience with Computer Vision cases - Exposure to Responsible AI, model risk management, and regulatory compliance - Experience defining AI strategy at an organizational or platform level .
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.