Machine Learning Engineer - 2

About the Role

**This role is for one of our clients** Seniority level: Associate level Industry: Technology, Information and Internet Company Name: MyNaksh Experience: 3\+ yrs Location: Bengaluru Job Type: Full\-time **About this Role** * We’re building AI that can form genuine, long\-term relationships with people. * For the first time in history, millions of people are building relationships with AI. MyNaksh is at the forefront of this shift, combining conversational AI across chat and voice with deep expertise in domains where people share highly personal parts of their lives. * We started with astrology, where our 2M\+ users tell us everything about their relationships, careers, families, ambitions, fears and day\-to\-day lives. Over time, this gives us something extremely rare: rich, longitudinal data that allows us to understand people as evolving individuals rather than as isolated interactions. * Historically, the ability to build this depth of understanding about millions of individuals was a moat reserved for companies like Google and Facebook. We believe that is changing. The next generation of AI products will be defined not just by how intelligent the underlying model is, but by how deeply the AI understands each individual and how well it can build a relationship with them over time. * Our ambition is to use what we’ve built in astrology as a foundation for AI that can build relationships across domains \- from matchmaking and companionship to other deeply personal and professional use cases. * For a Machine Learning Engineer, this means working on some of the hardest problems at the intersection of AI, personalization and human relationships: building models that understand users deeply, learn from long\-term interactions, develop persistent context and deliver increasingly personalized conversations at scale. * *This is in our opinion the most exciting work in frontier AI today \- figuring out how AI learns to know a person, and how that person can trust our AI more than anyone else in their world.* **What You’ll Do** * Build and own **production\-grade ML/AI systems** end\-to\-end. * Develop **LLM, RAG, conversational AI, and agentic workflows**. * Work on **personalization, memory, recommendations, and user intelligence**. * Build **LLM orchestration, evaluation, and optimization** systems for quality, latency, and cost. * Combine **structured astrology intelligence with ML, retrieval, and LLM reasoning**. * Work closely with Product, Backend, and other teams to **ship impactful features at scale**. ### **What We’re Looking For** * **3–5 years** in ML, Applied ML, NLP, or GenAI engineering. * Strong **Python and software engineering** fundamentals. * Hands\-on experience with **LLMs, RAG, embeddings, vector search, or conversational AI**. * Experience deploying **ML/AI systems to production**. * Strong understanding of **ML fundamentals, evaluation, APIs, system design, scalability, and cloud**. * Ability to **own problems end\-to\-end: design build evaluate production**. ### **Good to Have** LangChain/LangGraph, vector databases, Hugging Face/open\-source LLMs, MLOps/LLM evaluation, recommendation systems, or Indic/multilingual NLP. **About the company** --------------------- MyNaksh is India's fastest\-growing AI astrology platform. \- raised \~$2M in VC funding \- 1M MAUs \- $2M in ARR All in \~7m since launch, focusing on building trust and offering mass India world\-class experiences. Next 6m hyperscale phase \> 10M MAUs, $15M ARR, going global \+ adjacent markets. **Must\-have skills** --------------------- Machine Learning, Conversational AI **Good\-to\-have skills** ------------------------- LLM, B2C We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.