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Urgent! GKM IT - Senior Data Scientist II - Machine Learning/Deep Learning Job Opening In India, India – Now Hiring GKM IT Pvt. Ltd.

GKM IT Senior Data Scientist II Machine Learning/Deep Learning



Job description

<p><p><b>Data Scientist Senior II (Machine Learning & Generative AI)</b><br/><br/><b>Company :</b> GKM IT<br/><br/>At GKM IT, data isnt just numbersits the foundation of intelligent systems and innovation at scale.

We are seeking a Senior II Data Scientist who thrives at the intersection of research and production engineering, with a focus on Machine Learning, Deep Learning, and Generative AI.<br/><br/>If you are passionate about LLMs, transformer models, applied ML research, and mentoring future leaders in data sciencethis is the role for you.<br/><br/><b>Role Overview :</b><br/><br/>You will lead end-to-end ML initiativesfrom reading and reproducing research papers to production deployment of cutting-edge AI models.

Youll contribute to advancing our Generative AI capabilities while guiding junior data scientists and interns through complex, real-world problem solving.<br/><br/>This is a hands-on research and development role where you will design, prototype, optimize, and scale next-generation ML systems that directly impact products, customers, and business outcomes.<br/><br/><b>Key Responsibilities :</b><br/><br/><b>ML Research & Development :</b><br/><br/>- Conduct in-depth research on state-of-the-art machine learning & GenAI techniques, with a focus on LLMs, transformer architectures, and diffusion models.<br/><br/>- Reproduce and implement novel methods from research papers; adapt them to business use cases.<br/><br/><b>End-to-End ML Lifecycle Ownership :</b><br/><br/>- Own end-to-end ML workflows : problem framing, feature engineering, model design, experimentation, evaluation, optimization, deployment, and monitoring.<br/><br/>- Build scalable ML pipelines for data ingestion, preprocessing, model training, inference, and A/B testing.<br/><br/><b>Applied Generative AI :</b><br/><br/>- Fine-tune, distill, and evaluate Large Language Models (LLMs) and multi-modal systems for domain-specific tasks.<br/><br/>- Build LLM-powered applications using frameworks such as LangChain, LlamaIndex, RAG (Retrieval-Augmented Generation), and vector databases.<br/><br/>- Experiment with prompt engineering, fine-tuning strategies, embeddings, and model compression techniques.<br/><br/><b>Model Engineering & Deployment :</b><br/><br/>- Convert research-grade models into production-grade, optimized systems using TensorFlow Serving, TorchServe, ONNX Runtime, or Triton Inference Server.<br/><br/>- Implement MLOps best practices (CI/CD for ML, model monitoring, data versioning, drift detection).<br/><br/><b>Mentorship & Collaboration :</b><br/><br/>- Mentor junior data scientists and interns through hands-on project execution, code reviews, and research guidance.<br/><br/>- Collaborate cross-functionally with engineering, product, and business teams to align research with high-value use cases.<br/><br/><b>Requirements :</b><br/><br/><b>Experience :</b> 5- 7 years in Data Science, Machine Learning, or AI research roles.<br/><br/><b>ML & DL Expertise :</b><br/><br/>- Proficiency in core ML algorithms (Linear/Logistic Regression, Decision Trees, Random Forests, SVMs, Gradient Boosting).<br/><br/>- Deep understanding of deep learning architectures : CNNs, RNNs, Transformers, Attention Mechanisms.<br/><br/>- Strong experience in training, fine-tuning, and deploying Transformer-based models (BERT, GPT, LLaMA, T5, etc.).<br/><br/><b>Programming & Tools :</b><br/><br/>- Advanced proficiency in Python; strong coding practices for production-quality ML systems.<br/><br/>- Expertise with Scikit-learn, TensorFlow, Keras, PyTorch, Hugging Face Transformers.<br/><br/>- Familiarity with LangChain, LlamaIndex, FAISS/Weaviate/Pinecone for vector search and LLM applications.<br/><br/><b>Math & Research :</b><br/><br/>- Strong foundation in statistics, probability, optimization, and linear algebra.<br/><br/>- Ability to read, interpret, and implement research papers into working prototypes.<br/><br/><b>MLOps & Infrastructure (Nice to Have) :</b><br/><br/>- Hands-on with cloud ML platforms (AWS Sagemaker, GCP Vertex AI, Azure ML).<br/><br/>- Familiarity with Docker, Kubernetes, Airflow, MLflow, Kubeflow.<br/><br/><b>Benefits @ GKM IT :</b><br/><br/>- Premium Work Setup : MacBook + accessories.<br/><br/>- Flexibility : Hybrid/remote support, flexible schedules, WFH utilities.<br/><br/>- Quarterly Bonuses : Performance-based payouts every 3 months.<br/><br/>- Learning Fund : Dedicated budget for courses, certifications, conferences.<br/><br/>- Family-First Culture : Maternity/paternity leaves, vouchers for family events.<br/><br/>- Celebrations & Rewards : Onboarding hampers, festive goodies, referral bonuses, weekend work incentives.<br/><br/>- Healthcare : Comprehensive health insurance for you & dependents.<br/><br/>- Team Bonding : Quarterly team lunches, retreats, and celebrations.</p><br/></p> (ref:hirist.tech)


Required Skill Profession

Mathematical Science Occupations



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