Lead NLP and LLM fine-tuning initiatives using PEFT methods, curate and validate training datasets, implement RLHF and DPO alignment, optimize models through quantization, design evaluation benchmarks, manage distributed multi-GPU training, and prepare model checkpoints for cloud deployment. Requires advanced expertise in Python, PyTorch, transformer architectures, CUDA, and NLP, plus a mandatory AWS or Google Cloud machine learning certification.
This is a remote position.
NLP Data Scientist / LLM Fine-Tuning Specialist
Job Details
- Employment Type: Contract
- Work Mode: Remote
- Location: Offshore
- Total Experience Required: 4 to 8 years
- Relevant Experience Required: 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
Job Summary
We are seeking an experienced NLP Data Scientist / LLM Fine-Tuning Specialist to take ownership of our specialized open-source model optimization tracks. The ideal candidate will possess deep expertise in deep learning, dataset preparation, and parameter-efficient training methodologies to fine-tune foundational models for industry-specific terminology, domain-specific reasoning, and custom task execution.
Key Responsibilities
- Lead LLM fine-tuning initiatives, leveraging Parameter-Efficient Fine-Tuning techniques (PEFT) including LoRA, QLoRA, Prefix Tuning, and Prompt Tuning to optimize open-source architectures (e.g., Llama, Mistral).
- Curate, clean, and structure high-quality training datasets, implementing automated data deduplication, tokenization schemes, synthetic data generation pipelines, and human-in-the-loop validation frameworks.
- Implement advanced reinforcement learning alignment layers, configuring Reinforcement Learning from Human Feedback (RLHF) or Direct Preference Optimization (DPO) to enforce model safety, helpfulness, and tone guardrails.
- Optimize model footprint constraints and memory overhead, applying post-training quantization techniques (e.g., GGUF, AWQ, GPTQ) to minimize parameter degradation and compute budgets.
- Design rigorous evaluation benchmarks and metrics panels, executing automated validation tests (e.g., BLEU, ROUGE, custom verification matrices) to audit model hallucinations, factual accuracy, and domain alignment.
- Manage distributed deep learning training jobs, scaling pipeline configurations, tensor parallelism parameters, and gradient checkpointing scripts across multi-GPU compute blocks.
- Collaborate with MLOps infrastructure teams, formatting completed model weight checkpoints cleanly for scalable cloud deployment and real-time inference serving layers.
Requirements
- 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).
- Mandatory certification: Professional ML Engineer or Specialty Machine Learning credential from a major cloud vendor (AWS/GCP).
Preferred Qualifications
- 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.
Similar Jobs
Artificial Intelligence • Productivity • Software • Automation
Leads Zapier’s India entity as statutory Board Director and General Manager. Owns local operations, governance, legal, tax, audit, transfer pricing, regulatory compliance, risk management, vendor relationships, and people decisions. Serves as the bridge between India-based teams and global leadership, translating strategy into execution and establishing operating rhythms for a fully remote workforce. Partners with Deloitte, HR, finance, auditors, regulators, and global executives while overseeing hiring, performance, compensation, employee relations, and compliance with Indian labor requirements.
.jpeg)
Artificial Intelligence • Hardware • Information Technology • Machine Learning
Leads industrial engineering for semiconductor assembly and test manufacturing, including capacity and resource planning, labor optimization, operational excellence, cost reduction, manufacturing analytics, and factory systems. Develops capacity models, staffing standards, dashboards, and automation initiatives while supporting budgets and capital planning. Builds and mentors an industrial engineering team and collaborates globally to standardize manufacturing practices and improve efficiency, utilization, cycle time, and cost performance.
Top Skills:
Advanced AnalyticsAIManufacturing SimulationMesExcelPower BISQLTableau
Cloud • Information Technology • Internet of Things • Machine Learning • Software • Cybersecurity • Infrastructure as a Service (IaaS)
Lead Ericsson Antenna System’s Asia business, owning regional strategy, sales, business development, customer partnerships, and profit and loss. The role manages antenna and filter product lines, establishes strategic customer relationships, collaborates with market-area organizations, and directs annual business planning and target setting. Success requires telecommunications expertise, international leadership, large-account management, customer-facing experience, strong business acumen, and the ability to lead culturally diverse teams.
Top Skills:
Ericsson Antenna SystemMobile Communication AntennasRf FiltersTelecommunications
What you need to know about the Delhi Tech Scene
Delhi, India's capital city, is a place where tradition and progress co-exist. While Old Delhi is known for its rich history and bustling markets, New Delhi is defined by its modern architecture. It's clear the region places a strong emphasis on preserving its cultural heritage while embracing technological advancements, particularly in artificial intelligence, which plays a central role in shaping the city's tech landscape, fueled by investments in research and development.
