The Candidate would be tasked with solving a real-life business problem that requires processing/analysing TBs of data and handling variety of data sources
The candidate will be expected to deal with data extraction and munging, using appropriate ML techniques to build data science solutions and to implement these solutions in production.
The work is organized as a project with clear deliverables and stringent timelines
The Candidate would collaborate with other team members who would provide support and mentoring
The Candidate would proactively investigate, report, and where possible, address data quality issues
Core Skills:
Experience in using LLMs , both open source & proprietary models
Experience in building Q&A models using RAG , fine tuning LLMs – beyond prompt engineering techniques.
Experience in using tools like Langchain , LLamaIndex, vector databases is preferred
Understanding of LLM Ops is a big plus
Strong SQL skills (6-7 Years of hands-on experience with complex queries and data munging)
Deep Machine Learning expertise (hands on with 6-7 years of experience)
Strong expertise in Python (particularly Machine Learning Libraries)
Experience implementing machine learning solutions in at least 3-5 real-life Analytics Projects (Excluding Academic/side projects)
Solid fundamentals, knowledge of supervised, unsupervised, machine learning and deep learning algorithms, such as classifiers, cluster analysis, dimension reduction, regression, time series forecasting, boosting/bagging, model explain ability techniques
Exposure to deep learning algorithms and areas such as NLP is a strong plus.
Excellent communication (written/verbal), presentation and facilitation skills
Ability to engage with business teams directly, especially with key stakeholders spread across different Geos (particularly AMER and EMEA)