LLM Finetuning Engineer/ Developer

LLM Finetuning Engineer/ Developer

Fluid AI

About the Company:

corporations. We specialize in delivering cutting-edge Generative AI solutions. Our GPT

product allows businesses to increase their productivity by getting assistance in all key

functions including sales and marketing, operations, customer support etc. Our founders,

Abhinav & Raghav Aggarwal have been on the cover of the Forbes Magazine as well as on

the Forbes 30 Under 30 list and the Fortune 40 Under 40 list. Abhinav & Raghav have

appeared on numerous TV channels including NDTV, CNBC TV18, ET NOW etc. They are the

authors of the worlds first ever book written by an AI Algorithm. They have worked with

Warren Buffet to create a digital human avatar for the Forbes centennial issue.

Location:

Office Address:

Position Overview:

As an LLM Finetuning Engineer / Developer, you will be responsible for adapting and

optimizing large pre-trained language models to meet specific business and product

requirements. You will work closely with data scientists, ML engineers, and product teams

to ensure our AI models are accurate, efficient, safe, and scalable.

Responsibilities:

• Design and implement strategies for fine-tuning and instruction-tuning large pre-

trained language models (e.g. LLaMA, Mistral, Falcon).

• Curate, preprocess, and generate high-quality training datasets for domain-specific

tasks.

• Apply parameter-efficient finetuning techniques (LoRA, PEFT, adapters,

quantization).

• Optimize training pipelines for speed, memory efficiency, and cost-effectiveness.

• Evaluate models against benchmarks (accuracy, perplexity, latency, hallucination

rates, bias/fairness).

• Deploy fine-tuned models into production, ensuring scalability and reliability.

• Collaborate with cross-functional teams to integrate LLMs into real-world

applications (chatbots, copilots, document understanding, knowledge retrieval, etc.).

• Research and implement the latest advancements in RAG (Retrieval-Augmented

Generation), alignment, safety, and model compression.

• Document processes, best practices, and performance improvements.

Requirements:

Must-Have:

• Strong programming skills in Python and experience with ML frameworks (PyTorch,

TensorFlow, Hugging Face Transformers).

• Hands-on experience with training and finetuning LLMs (instruction tuning, RLHF,

LoRA).

• Solid understanding of deep learning, NLP, and transformer architectures.

• Proficiency in data preprocessing, annotation, and augmentation techniques.

• Familiarity with evaluation metrics for generative models.

• Experience working with cloud platforms (AWS, GCP, Azure) and GPU/TPU training

environments.

Nice-to-Have:

• Exposure to RAG pipelines, vector databases (Pinecone, Weaviate, FAISS, Milvus).

• Knowledge of MLOps tools (Weights & Biases, MLflow, Kubeflow, Docker,

Kubernetes).

• Experience in model compression & deployment optimization (quantization,

distillation).

• Prior work with safety, bias mitigation, and hallucination reduction in LLMs.

• Contributions to open-source GenAI projects.

Soft Skills:

• Strong problem-solving and analytical abilities.

• Ability to thrive in a fast-paced, research-driven environment.

• Excellent communication skills to work across technical and non-technical teams.

• Passion for Generative AI and pushing the boundaries of whats possible.

What We Offer:

• Opportunity to work on cutting-edge Generative AI projects with global impact.

• Collaborative and innovative work culture.

• Access to state-of-the-art tools, GPUs, and research resources.

• Competitive compensation and growth opportunities.