Machine Learning Engineer

Location: Gurgaon

Type: Full-time

Level: Senior

We are a venture-backed, stealth-stage technology company building next-generation matchmaking and relationship platforms. Our mission is to reimagine how people connect, using AI, community, and content as our building blocks.

We’re not building another dating app — we’re creating an experience where users feel:

“This app gets me.”

At the core of our product is a real-time, ML recommendation engine and understanding of users preferences  similar to Spotify for song moods or TikTok for discovery.

We are well funded and backed by marquee VCs in India and the US

We’re looking for an AI Engineer (1–3 years experience) to build and improve the AI agents that talk to users, understand their preferences, keep conversations safe, and feed that signal into our matching system. 

You’ll work on prompts, evals, memory, safety, voice, and early recommendation logic.

You’ll be hands-on with LLM-powered conversational interfaces (chatbots, voicebots, copilots), multi-turn stateful conversations, and retrieval-augmented responses grounded in real data — not just “vibes.”

• Context engineering - Write and iterate prompts (tone, instructions, safety rules, structured JSON output).
• Build and extend LLM-based chat and voice agents using tool / function calling, memory, and controlled dialogue flow.
• Implement context and state tracking so conversations feel continuous and personalised.
• Build evals to score quality, safety, accuracy, and policy compliance before changes go live.
• Add and tune safety / guardrails for sensitive topics.
• Structure free-form conversation into clean JSON (interests, intent, boundaries) that feeds our personalisation and ranking.
• Contribute to early recommendation and retrieval logic (embeddings, vector similarity, preference signals) to improve “who you see next.”
• Work with the team to review real sessions, spot failure modes, and ship fast fixes.

We value engineers who are comfortable across Generative AI, large language models (LLMs), deep learning, NLP, and traditional ML techniques — and who care about making the AI feel safe, fast, and human.

• 1–3 years in applied AI / ML / NLP / conversational AI.
• Hands-on with LLMs (OpenAI / Gemini / Claude or similar) in real multi-turn or voice use cases.
• Strong prompt writing: persona, boundaries, refusal logic, tool usage, chain-of-thought style reasoning for goal completion.
• Comfortable forcing models to return reliable structured output (JSON schemas, key-value extraction).
• Can build simple services in Python or Node.js to call LLM/speech APIs, stream responses, and manage latency.
• Exposure to retrieval / RAG (vector DBs, grounding responses on facts) and/or recommendation basics (embeddings, nearest-neighbor match, reranking).
• Basic classical ML intuition (ranking, classification, evaluation metrics) plus interest in personalization.
• Bonus: experience with speech (ASR/TTS, streaming agents), long-term memory / session state, or monitoring agent behavior in production.



• Join a founding team where your work is core to the product experience
• Shape the future of how humans connect in the AI era
• Significant ESOPs and wealth creation + competitive cash compensation