NLP Data Scientist

Job not on LinkedIn

🕒 4 days ago

🇮🇳 India – Remote

⏳ Contract/Temporary

🟡 Mid-level

🟠 Senior

📊 Data Scientist

👻 Ghost score 12%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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FyerX - Your Trusted Marketing Partner

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2021

📣 Marketing

🤝 B2B

Marketing • B2B

FyerX is a marketing agency based in Bangalore that specializes in helping businesses enhance their digital presence and improve online outcomes through tailored marketing strategies. With a passionate team of marketing experts, FyerX focuses on various aspects of digital marketing including social media marketing, branding, search engine optimization, and influencer marketing. They aim to fuel the growth of purpose-driven brands by developing integrated marketing plans that drive online growth and improve brand visibility.

📋 Description

• Lead LLM fine-tuning initiatives using PEFT techniques including LoRA, QLoRA, Prefix Tuning, and Prompt Tuning to optimize open-source architectures such as Llama and Mistral • Curate, clean, and structure training datasets • Implement automated data deduplication, tokenization schemes, synthetic data generation pipelines, and human-in-the-loop validation frameworks • Implement reinforcement learning alignment layers using RLHF or DPO to enforce model safety, helpfulness, and tone guardrails • Apply post-training quantization techniques such as GGUF, AWQ, and GPTQ to minimize parameter degradation and compute budgets • Design evaluation benchmarks and metrics panels using automated validation tests such as BLEU, ROUGE, and custom verification matrices • Audit model hallucinations, factual accuracy, and domain alignment • Manage distributed deep learning training jobs across multi-GPU compute blocks • Scale pipeline configurations, tensor parallelism parameters, and gradient checkpointing scripts • Collaborate with MLOps infrastructure teams to format model weight checkpoints for scalable cloud deployment and real-time inference serving

🎯 Requirements

• Total experience: 4 to 8 years • 3+ years of dedicated natural language processing (NLP) and hands-on Large Language Model (LLM) fine-tuning experience • Mandatory certification: Google Cloud Certified Professional Machine Learning Engineer or AWS Certified Machine Learning - Specialty • 4 to 8 years of core data science or advanced machine learning engineering experience, with 3+ dedicated years actively training, evaluation, and fine-tuning natural language processing systems • Expert-level technical mastery of Python, deep learning frameworks (PyTorch), transformer architectures (Hugging Face Transformers, Accelerate, PEFT), and vector calculations • Deep structural understanding of attention mechanisms, tokenization constraints, context window degradation behaviors, loss function optimization, and hardware compute limitations (CUDA) • Preferred: Master’s or Ph.D. in Computer Science, Data Science, Computational Linguistics, or an adjacent quantitative field with a research focus on neural network text models • Prior experience implementing custom embedding model structures or optimizing domain-specific classification layers inside constrained enterprise runtimes