Job Overview

machine learning lead - llms, genai & conversational ai

noida (sector 63) - hybrid (office-based role)

2+ years hands-on in llm / generative ai

5+ years overall in ai/ml or it

full-time

about the role

jupiter ai labs is looking for a machine learning lead to spearhead development and deployment of cutting-edge ai solutions across nlp, vision, and speech. you'll architect llm & agentic-ai pipelines, build conversational agents, own ci/cd deployments, mentor junior engineers, and liaise directly with clients and stakeholders.

key responsibilities

end-to-end llm solutions : lead design, fine-tuning & deployment of chatbots, multi-agent (a2a/mcp) workflows.

open-source model integration : architect pipelines with llama2, mistral, claude, gpt-series via hugging face, langchain, etc.

ai agent orchestration : build automations with n8n langgraph.

conversational ai : develop assistants using botpress, rasa, azure bot framework, aws lex.

speech & vision : integrate asr (whisper, coqui), tts engines, and ocr models (tesseract, paddleocr).

full-stack ml apis : develop fastapi/flask services, integrate into react/node.js front ends.

cloud ci/cd : deploy scalable models on aws/azure/gcp, automate via docker, terraform, github actions.

team leadership : mentor ml engineers, run daily standups, produce status reports.

client engagement : represent jupiter ai labs in technical reviews, manage stakeholder expectations, deliver project documentation.

️ required skills & experience

2+ years in llm / generative ai (prompt-engineering, fine-tuning, rag).

proficient with hugging face , langchain, transformers, vector databases.

hands-on with agentic ai tools (langgraph, crewai) and a2a/mcp pipelines.

experience building conversational agents (rasa, botpress, azure bot, lex).

expertise in asr and tts integrations (whisper, commercial apis).

ocr modeling (tesseract, paddleocr, google vision api).

full-stack ml api development (fastapi/flask + react or node).

cloud deployment & ci/cd on aws/azure/gcp (docker, kubernetes, terraform).

workflow automation with n8n , or zapier.

computer vision experience (yolo, opencv, custom cnns).

strong understanding of mlops practices, version control, and monitoring.

proven track record running daily standups, reporting, and mentoring.

soft skills

exceptional verbal & written english communication.

collaborative leadership in cross-functional teams.

highly organized, proactive, and deadline-driven.

ability to train freshers and manage junior engineers.

strong stakeholder management and client-facing presence.

preferred qualifications

b.tech / m.tech / ph.d. in computer science, ai, or related field.

open-source contributions (github, hugging face spaces).

certifications in ai/ml (aws, google cloud, etc.).

what we offer

exposure to breakthrough llm, cv, asr & genai projects.

ownership of end-to-end architecture and experiments.

fast-paced, learning-driven culture.

competitive salary + performance bonuses.

medical insurance, flexible work hours, and career growth path.

to apply, please share your resume, answers to the screening questions, and links to any relevant github or project portfolios to ( ) . we look forward to building the future of ai together!