Senior Machine Learning Engineer

Want to impact the lives of 10 million students in real Bharat?? Then come with us,

Arivihan

is building an

AI tutor

that actually teaches better than a human faculty, because it’s

ultra-personalized

, infinitely scalable, and extremely

affordable

.

We’ve already rocked the

MP Board

. Now we’re moving to different boards and competitive exams, with a clear vision to be pan-India across multiple exams. If you always focus on making a big

impact

with your coding more than completing hours in the office, then you’re meant to do big things and

exponential

growth

at

Arivihan

is waiting for you.

Title

: Senior ML Engineer Location

: Bangalore, (Indore - a week in couple of months) Working Days

: Monday–Friday (5 days)

Key Responsibilities : ● Work closely with Product, Design, Content, and Engineering to understand student problems deeply and ship AI features end-to-end into the product. ● Do hands-on research + experimentation to find the best approach–model selection, prompting, evaluation, iteration, and rapid learning. ● Build and improve AI systems for real learning workflows like numerical problem solving, image-to-text extraction, and AI-powered content/lecture generation. ● Debug, optimize, and improve performance (accuracy, latency, cost), and maintain strong evaluation + testing pipelines (test sets, automated checks, regression testing) to ensure reliability at scale. ● Own outcomes like a builder—you don’t watch the clock, you watch the impact: driven to do bold, innovative work that students have never experienced before.

Key Requirements : ● 3–4 years of hands-on experience building and deploying AI solutions, with strong practical work in LLMs/GenAI (prompting, tool/function calling, RAG or similar approaches, and evaluation). ● Strong Python + production engineering: building scalable APIs/services using FastAPI/Django/Flask, and solid experience with ML stacks like PyTorch/TensorFlow/Scikit-learn/Keras + Hugging Face and supporting pipelines/scripts. ● Deep ML lifecycle + multimodal exposure: strong command over prompt → evaluate → iterate → improve, with focus on accuracy/robustness; experience across text, image, audio, video (tools like ElevenLabs/Wav2Lip/Manim/AI4Bharat are a plus). ● Builder mindset + collaboration: sharp problem-solving in ambiguous situations, strong experimentation skills, and clear communication to align technical decisions with product outcomes.