Faculty For Data Engineering & Machine Learning

Position: Assistant
Professor/Associate Professor/Professor

Track: Data
Engineering & Machine Learning  

Location: Sonepat,
NCR of Delhi.

Mode: Full Time;
On -Campus

Programme: B. Tech
CS and Data Science

ABOUT US

Rishihood
University       

Rishihood
University (RU) has been established under The Haryana Private Universities
(Amendment) Act, 2020 and is empowered to award degree as specified in section
22 of UGC Act, 1956. 

Rishihood
University is India’s first and only impact university. ‘Impact’ is the living
spirit of Rishihood. The purpose of education envisioned by the thought leaders
of our civilization and that which has motivated the founders to build
Rishihood University is beyond just awarding degrees and jobs. The purpose of
education is to achieve the highest potential in a learner i.e., Rishihood.
Rishihood University provides a unique mix of globally relevant education that
is rooted in Indian ideas, quality education that is affordable, and a
multi -disciplinary exposure with cutting edge skills of a specialist. To
achieve this outcome, education cannot be limited to within the classrooms. RU
is a fully residential campus where living and learning seamlessly integrate
throughout the day. RU faculty and learners have an active participation with
society, industry, researchers, entrepreneurs, and policy makers. This keeps
the learning at RU focused on solving the biggest challenges faced by humanity
and prepares our learners for the real world. It is time India builds
universities driven by a higher purpose, that have a strong committed board to
back it, that redefine the way education is imparted both within and outside
the classroom. Rishihood is a bold initiative to fulfill this idea.
Hence, we are looking for like -minded founding faculty members at Rishihood
University.

About Position

Track   | The
DS Core

Foundations of
Data Science   •   Data Mining and Warehousing   •  
Machine Learning   •   Supervised Learning

India produces
some of the world's best data scientists. Most of them were trained to use
tools. We want to train students who can build the tools and understand deeply
why they work. That is the difference between an execution hub and a technology
defining nation. This track is where that shift starts.

You will join Rishihood
as a Faculty at the heart of what makes this a Data Science programme and not
just another CS degree with a few ML electives tagged on. The DS Core takes
students from raw data to predictive intelligence. As you grow into the Track
Lead role, you will own this domain entirely: designing the learning arc from
data foundations to production grade ML, building the faculty team, and holding
the standard of every student who graduates from it.

Requirements

Key
Responsibilities

1.      Teach Foundations
of Data Science, Data Mining and Warehousing, Machine Learning, and Supervised
Learning

2.      Run labs that
feel like real professional work: ETL pipelines with messy datasets, models
that students deploy rather than just submit as notebooks

3.      Guide capstone
projects with rigorous validation: K fold cross validation, A/B testing, and
production readiness checks

4.      Lead MLOps
integration into the curriculum and run seminars on data governance, GDPR,
DPDP, and algorithmic fairness

5.      Own curriculum
design, faculty hiring, and the output standard for this track as Track Lead

 

Job Specifications

You should hold an
MTech, PhD, or equivalent in a relevant field. Beyond the degree, here is what
we actually care about.

Technical Depth

• Expert knowledge of supervised
  learning (Decision Trees, SVM, Random Forest, XGBoost, linear and logistic
  regression) and data engineering (Star and Snowflake schemas, ETL
  orchestration, Data Lakes vs Warehouses)
  
• Python data science stack: scikit
  learn, Pandas, NumPy, advanced SQL; model evaluation at depth: Precision
  Recall, F1 Score, ROC AUC, cross validation
  
• Working understanding of MLOps in
  practice and familiarity with cloud ML deployment on AWS SageMaker, Azure
  ML Studio, or GCP
  

The Person

• You care about data quality as much
  as model sophistication, correct someone's thinking not just their code,
  and always ask whether it actually works when deployed
  
• You can translate real industry
  experience into classroom substance that students recognize as genuine
  

Good to Have

• Industry experience as a Senior Data
  Engineer, ML Engineer, or ML Architect in a product based company
  
• Strong Kaggle ranking or open source
  ML contributions; experience deploying ML models at scale in cloud
  environments
  

This job
description is not intended to be all -inclusive. The employee may be expected
to perform other duties as assigned by the supervisor.