Michael Page
Create a free account
One signup unlocks everything for this job:
- Apply to this job and track your application
- See your personalized profile match score
- Generate an AI cover letter for this role
Gurugram · On-site · 5-8 Yrs · Aug 23
5001 to 10000 Employees · London, United Kingdom
We’ve been changing lives for 50 years, connecting people with roles that bring out their best, and helping teams find the talent they need. It all started in London in 1976, and we’ve grown steadily since, building a global network and a reputation customers trust. People choose Michael Page for the lives we help shape, the service we give our customers, and the exciting career opportunities we offer all around the world. Join us and you’ll be working for one of the best in the industry.
Hiring: Engineering
What employees say
+ 1) A firm that rewards hardwork, intent and trusts you to grow 2) Best platform to build your career in executive search 3) You set benchmarks for the industry’s best practices
− 1) Things can be overwhelming at times
More reviews on the company profile.
Interview experience · Consultant
3 interviews and 1 case presentation round. Each was to understand my experience and why Michael Page. Case study is to understand person's thinking and how would a person do day to day work at Michael Page.
Average difficulty · Bengaluru · 29 reports
More interview insightsJob description
Overview
• High-Impact Product & Client Exposure • Digital Engineering + AI-Led Innovation
Responsibilities
- Models in production
- Build, train, tune and deploy ML and deep learning models using TensorFlow or PyTorch and scikit-learn.
- Own model evaluation, optimisation, monitoring and governance - robustness, fairness, drift and scale, not just offline accuracy.
- Do the unglamorous work well: preprocessing, wrangling and feature engineering with pandas and NumPy.
- GenAI and LLM applications
- Develop GenAI applications - conversational agents, summarisation, RAG pipelines, document intelligence.
- Design retrieval and prompting strategies that hold up on messy enterprise data - and recognise when fine-tuning is the better answer.
- Instrument outputs so quality is measurable rather than anecdotal.
- Pipelines and engineering rigour
- Partner with data engineering to design scalable data and model pipelines for training and inference.
- Enforce reproducibility, testing and code quality across the team's work.
- Leadership and communication
- Mentor data scientists, run technical reviews and promote coding excellence.
- Present findings and AI strategy to non-technical stakeholders in language that drives a decision.
- 8-10 years in data science and applied AI, including experience leading a small technical team.
- Expert Python: advanced OOP, data structures, API design and testing.
- Strong ML/DL delivery with TensorFlow and scikit-learn, and fluency in pandas and NumPy.
- Practical LLM and GenAI experience: Hugging Face Transformers, LangChain or LlamaIndex.
- Solid statistical foundations: regression, time-series, hypothesis testing and anomaly detection.
- Communication that bridges technical and business teams - clear, specific and actionable.
- A proven mentoring record and a bias for shipping over perfecting.
- Permanent role in a technology and telecoms company based in Gurugram.
- Opportunity to lead a team and work on impactful projects.
- Scope to stay updated with cutting-edge tools and practices.
Verify Python for this role
Free PRACTICE for Python adds a verified skill signal that can boost how roles like this rank for you — optional, not required to browse or apply.
Sign up — verify Python free →Want match scores and deeper insight? Create a free candidate profile