Senior Data Scientist

Who We Are

Simpplr is the AI-powered platform that unifies the digital workplace – bringing together engagement, enablement, and services to transform the employee experience. It streamlines communication, simplifies interactions, automates workflows, and elevates the everyday experience of work. The platform is intuitive, highly extensible, and built to integrate seamlessly with your existing technology.

More than 1,000 leading organizations – including AAA, the NHS, Penske, and Moderna – trust Simpplr to foster a more aligned and productive workforce. Headquartered in Silicon Valley with global offices, Simpplr is backed by Norwest Ventures, Sapphire Ventures, Salesforce Ventures, and Tola Capital. Learn more at simpplr.com.

About the Role
Join our forward-thinking team as a Data Scientist where you will address real-world challenges
through the lens of AI innovation, specifically focusing on Enterprise Search, Personalization,
Content Recommendation, and pioneering work with custom LLM fine-tuning. Work in an
environment that fosters collaboration among highly skilled professionals to build next-
generation products that significantly impact our clients' operational effectiveness.
Key Responsibilities
● Innovate and develop scalable solutions leveraging AI technologies to process and
analyze vast amounts of data efficiently.
● Quickly prototype, test, and deploy effective AI solutions, managing project timelines and
deliverables while incorporating the latest advancements in AI research.
● Engage with cross-disciplinary teams to identify and implement AI-driven enhancements
for user experiences, leading the charge from ideation to deployment.
What We’re Looking For
● 3-5 years of experience in crafting and implementing AI models, with a particular interest
in applications within Enterprise Search and Content Personalization.
● Solid grounding in AI technologies, with proficiency in Python and familiarity with AI
development frameworks.
● Interest or experience in ML-Ops, emphasizing the journey from concept to production
scalability of ML models.
● Openness to candidates with a robust background in backend development who have
delved into AI, especially those who have engaged in Enterprise Search, Developing
learning to rank models, Agentic Workflows and LLM fine-tuning.
● Knowledge in developing analytical applications and working with cloud platforms,
capable of managing large data sets and complex AI models.
Technical skill sets
● Strong coding skills
● Understanding basics of Machine Learning, Deep Learning, and Natural Language
Processing algorithms
● Experience in working with data annotation tools and building ML evaluation pipelines
● Comfort with working in multiple tech stacks
● Experience in API Development, Docker and AWS Services
Nice to have:
Experience in ML research, focusing on LLMs, Information Retrieval Systems, Reinforcement
Learning, Knowledge Graphs, Agentic Workflows, Retrieval-Augmented Generation (RAG),
Recommender Systems, Scaling, Monitoring, and Deploying LLMs

Our Ideal Candidate
We are in search of individuals who are not merely experienced but deeply passionate about
unearthing new challenges and inquiries in the realm of AI. We value creativity, positivity, work
ethic and the pursuit of answering intricate questions with methodical accuracy. Multiple
positions at different seniority levels are available.

Simpplr’s Hub-Hybrid-Remote Model:

At Simpplr we believe that when work is good, life is better and that belief guides all we do. Including how we approach our flexible work model. Simpplr operates with a Hub-Hybrid-Remote model. This model is role-based with exceptions and provides employees with the flexibility that many have told us they want.

• Hub - 100% work from Simpplr office. Role requires Simpplifier to be in the office full-time.
• Hybrid - Hybrid work from home and office. Role dictates the ability to work from home, plus benefit from in-person collaboration on a regular basis. 
• Remote - 100% remote. Role can be done anywhere within your country of hire, as long as the requirements of the role are met.