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

Department Icon Data Science Analytics & Machine Learning
149+ Applicants
Posted: 8 months ago
0-1 years
India
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Posted: 8 months ago
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Applicants: 150+
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Job Description

Machine Learning (ML) Engineer Intern (India/Remote)
Apply using this link - https://app.dover.com/apply/Peakflo/f885883d-1ae9-48a7-bd64-8e2898be07b7rs=42706078
???? What Were Building
  • Finance operations at any high-growth SMB or startup are plagued with resource-intensive customer collections and vendor payment processes. This culminates into hundreds of wasted finance manhours and thousands of dollars in payment fees!
  • Peakflo with its simple API and one-click accounting software integrations, allows businesses to streamline their customer collections and vendor payments. 187 finance team users, from early-stage startups to unicorns in SE Asia, use Peakflo each week to:
?Save 100 hours/month on finance ops ?
?Get paid faster on customer invoices by 10-20 days ????
?Streamline vendor payments and save 50-90% on fees ????
Most importantly, we have begun building an environment that encourages intellectual curiosity, problem-solving, and ownership. An environment that provides the support and mentorship needed to succeed, learn, and grow ??
???? What Were 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 Youll Do
  • Craft voice?optimized prompt flows:
    • Design conversational flows that account for natural speech patternspauses, interruptions, intonationwith 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?agentsfor 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&aposs Gemini, OpenAI&aposs GPT series, Anthropic&aposs 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 driftespecially 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 Were Looking For
    • Bachelor&aposs or Master&aposs 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.
    ? Were Particularly Interested In People Who Have
    • Looking to get Placed? Try our Placement Guarantee Plan

      Experience with multiple LLM platforms and frameworks.
    • Familiarity with natural language processing (NLP) techniques and libraries.
    • 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.
    Apply using this link - https://app.dover.com/apply/Peakflo/f885883d-1ae9-48a7-bd64-8e2898be07b7rs=42706078

    Skills

    PythonData ScienceMachine LearningSolution DevelopmentPrompt EngineeringMl EngineerLarge Language ModelAiGoogle CloudMl

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    Important dates & deadlines?

    Application Deadline

    18 Sep 25, 02:47 PM IST

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