Machine Learning Engineer - 2 at Weekday in Bengaluru

Job description

• 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
• ₹20,00,000 - ₹35,00,000 a year
• 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.

Responsibilities

• 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.

Requirements

• 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.
• Machine Learning, Conversational AI
• LangChain/LangGraph, vector databases, Hugging Face/open-source LLMs, MLOps/LLM evaluation, recommendation systems, or Indic/multilingual NLP.
• LLM, B2C

Skills

Required

• Machine Learning
• Conversational AI

Preferred

• LangChain/LangGraph
• vector databases
• Hugging Face/open-source LLMs
• MLOps/LLM evaluation
• recommendation systems
• Indic/multilingual NLP
• LLM
• B2C