Research Engineer – Applied Generative AI; LLMs & Multimodal Systems

Position: Research Engineer – Applied Generative AI (LLMs & Multimodal Systems)
Location: Bengaluru

About Pocket FM

Pocket FM is where audio storytelling comes to life, powered by cutting-edge AI. With a global community of over 100 million listeners, we are building the world's largest platform for immersive audio series. Our Generative AI team is the engine behind our next leap forward, and we're looking for an engineer who doesn't just study AI, but builds it, scales it, and ships it.

If you are a hands-on builder passionate about transforming novel AI research into real-world products, we want to talk to you.

The Role:

What You'll Build and Own

As a Research Engineer on our team, you won't just be experimenting—you'll be architecting the core of our AI-first content stack. Your work will directly impact the stories our users hear every day.

- Architect & Implement Fine-Tuning Pipelines:
Go beyond notebooks. Design, build, and optimize robust pipelines for fine-tuning foundation models (e.g., LLaMA, Mistral, Qwen) on custom datasets. You'll own the process from data curation and training to evaluation for tasks like narrative generation and dialogue synthesis.
- Develop & Deploy Multimodal AI Systems:
Engineer and product ionize models that seamlessly blend modalities. Your primary focus will be on creating state-of-the-art systems for text, speech, and audio generation to power dynamic and immersive storytelling.
- Own the AI Orchestration Layer:
Design and implement a scalable orchestration system (e.g., using Lang Graph, Ray, or custom frameworks) to manage complex, multi-agent AI workflows. This includes planning agents, tool-using models, and evaluation layers that work in concert.
- Build Scalable MLOps

Infrastructure: Bridge the gap between models and our production environment. You will integrate generative AI workflows with our cloud infrastructure, ensuring our systems for training, inference, and deployment are efficient, reliable, and scalable.
- Translate Research into Production-Ready Code:
Be the critical link between theoretical research and tangible product features. You'll read the latest papers, identify promising techniques, and write the high-quality, efficient code needed to make them work at scale.

The Ideal Candidate :
Who You Are

We're looking for a pragmatic engineer who is obsessed with making AI work in the real world.

- A Proven Builder:
You have a track record (ideally 3+ years) of building and shipping machine learning models into production environments. Your resume shows projects, not just publications.
- LLM Fine-Tuning Expert:
You have deep, hands-on experience fine-tuning large language models using techniques like LoRA, QLoRA, DPO, or RLHF. You can speak to the practical challenges and trade-offs.
- Multimodal Practitioner:
You have practical experience building models that integrate multiple modalities (e.g., text-to-speech, audio understanding, vision-language).
- Systems Thinker:
You understand that a model is just one piece of the puzzle. You have experience building or maintaining the full AI pipeline, from data ingestion to model serving and monitoring.
- A Pragmatic Mindset:
You have a bias for action and an obsession with shipping robust, efficient code. You know when to use an off-the-shelf solution and when to build from scratch.

Your Technical Toolkit:

- Required:

Proficiency in Python, PyTorch, and the Hugging Face ecosystem (Transformers, Accelerate, PEFT).
- Distributed Training:
Demonstrable experience with frameworks like FSDP, Deep Speed, or Megatron-LM.
- Orchestration & MLOps:
Familiarity with AI workflow orchestrators (e.g., Lang Graph, Prefect, Ray) and experience connecting models to cloud infrastructure (AWS, GCP, or Azure).

- Bonus Points:

Experience with Retrieval-Augmented Generation (RAG) systems, building AI agents, and designing novel evaluation frameworks for generative models.

Why Join Us?

- Pioneer AI in Storytelling:
Work on unique, real-world generative AI challenges that are defining the future of entertainment for millions of users.
- Impact at Scale:
See your work go live and shape a product used by a massive global audience.
- Ownership and Autonomy:
We hire smart people and trust them. You'll have the freedom to drive your initiatives and choose the best tools for the job.
- Top-Tier Rewards:
We offer competitive compensation, meaningful employee stock options (ESOPs), and the chance to be a leader in a rapidly growing, innovative company.