Machine Learning (ML) Engineer Intern - (Paid - India/Remote)

💻 What we’re Looking For:

We are seeking a highly motivated and detail-oriented Machine Learning (ML) Engineer Intern to join our dynamic team. As a ML Engineer Intern, you will play a crucial part in developing and implementing machine learning solutions to drive business growth and improve our products.

💪 What you’ll do

• Craft voice‑optimized prompt flows:
• Design conversational flows that account for natural speech patterns—pauses, interruptions, intonation—with goal‑oriented multi‑turn dialogue optimized for voice-only interactions.
• Ensure prompts are clear for TTS pronunciation (e.g. spelling out email IDs, phone numbers, dates explicitly) to avoid ambiguity
• Implement agentic architecture and hierarchical workflows:
• Build finance AI agents that coordinate sub‑agents—for example, a Research Agent to fetch financial data, a Finance Agent to analyze transactions, and an Editor Agent to craft reports.
• Organize these into hierarchical-sequential or plan‑and‑execute flows for scalability and modularity

• Continuous prompt refinement & iteration:
• Use LLM feedback loops or "self‑reflection" to score outputs, detect hallucinations, and improve prompts over time.
• Set up pipelines for A/B testing, prompt versioning, and performance QA tailored to financial use cases 
• Apply expertise in and potentially fine-tune leading LLMs (e.g., Google's Gemini, OpenAI's GPT series, Anthropic's Claude) to optimize AI Finance Employee performance.
• Optimize overall LLM system performance to ensure low latency and high efficiency across all financial AI applications.
• Grounding & retrieval true‑fact enhancement:
• Integrate RAG (retrieval-augmented generation) with enterprise knowledge bases or financial APIs to avoid misinformation or drift—especially for task‑sensitive use cases like invoicing or AR follow-ups.
• Maintain tight context control around business domains to limit actions only to finance‑specific interactions

• Voice integration & prompt‑tech stack collaboration:
• Collaborate closely with engineering teams to integrate prompts with speech recognition, intent extraction, LiveKit voice infrastructure, and telephony APIs.
• Ensure client-side and server-side orchestration maintains real‑time responsiveness and low latency in voice flows
• Architect and integrate LLM systems with a wide range of third-party tools and platforms to facilitate diverse use cases, including email interactions and user chat interfaces.
• AI Solution Development - Develop and optimize complementary AI components such as advanced customizable OCR models, intelligent chatbots, and automated approval systems to support financial workflows.
• Maintain a strong understanding of and stay current with the latest advancements, research, and best practices in large language model (LLM) technologies and AI to drive continuous innovation.

🕵️‍♀️ Who we’re looking for

• Bachelor's or Master's degree in Statistics, Machine Learning, Data Science, or a related field.
• 0.5 - 2 years of industry experience with Machine Learning, Statistics and / or LLM fine-tuning and prompt engineering.
• Excellent written and verbal communication skills in English.
• Extensive experience in Python programming.
• Proficiency with cloud platforms like Google Cloud.
• Strong expertise in Python back-end development and launching ML products in production.
• Passionate about AI and its potential to transform businesses.

➕ We’re Particularly Interested In People Who Have:

1. Experience with multiple LLM platforms and frameworks.
2. Familiarity with natural language processing (NLP) techniques and libraries.
3. Knowledge of software engineering best practices and version control systems (git)

🙂Benefits :

• Competitive stipend
• Performance based full-time role conversion
• Benefits package (post full-time conversion)
• Opportunity for career growth and skill development.
• Collaborative and innovative work environment.
• Flexible work hours and remote work options.

A meeting lands on your calendar

If they’re a yes, I book the chat. You show up — that’s the whole job-hunt.