Research Engineer (Multilingual LLM Fine-Tuning)

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 is as excited about applied research as they are about shipping it into products used by millions. If you are passionate about transforming novel AI research into real-world impact, and want your work to reach a massive audience, we want to talk to you.

What you'll build

• Planner: story planning systems for characters, world building, plot arcs, and pacing; involves narrative reasoning, long context planning, agentic workflows, and memory/knowledge graphs
• Prose: scene generation, dialogue, prose refinement, and tone adaptation using long context, controllable, and multilingual generation models
• Feedback: AI editing systems that catch pacing, continuity, and structural issues like a developmental editor, using critique and evaluation models with human in the loop workflows
• Audio Native Infrastructure: voice over formatting, audio mastering, trailer generation, and narration aware adaptation

Who we're looking for

• 3+ years of hands-on experience building ML/LLM systems, with exposure to production environments
• Strong applied research experience in Generative AI, with hands on LLM fine tuning and post training
• Experience building AI copilots, agents, or workflow assistants
• Experience translating research into production systems, especially long context, memory, planning, or evaluation
• Exposure to creative or content generation systems is a strong plus
• Genuine curiosity about content, storytelling, or creative tooling

Multilingual & Hindi LLM experience

• Hindi or multilingual/non English LLMs, fine tuning multilingual foundation models, instruction tuning, domain adaptation, cultural and linguistic alignment, and low resource language optimization
• Experience with Indian language AI systems is highly valued

Technical Stack

• Required: Python, PyTorch, Hugging Face, distributed training (DeepSpeed, FSDP, Megatron LM), production AI systems experience
• Preferred: LangGraph/Ray, RAG and memory systems, AI evaluation pipelines, multilingual NLP/Hindi LLMs, speech/audio AI