What is Splore
Founded and funded by Temasek and Menyala, Splore is an early-stage venture focused on reimagining how people find and interact with information. In a world teeming with data, the challenge is no longer about obtaining information but finding what is relevant quickly and efficiently. Splore's AI Answer Engine provides direct and contextual answers, thereby transforming the way information is discovered and consumed.
Splore empowers businesses to unlock the vast potential of not only their information assets, but leverage Splore's proprietary Knowledge Index, thereby enabling them to make quicker, more informed decisions. At the same time consumers getting fast, relevant, and trusted answers, thereby eliminating the all-too-common frustration of sifting through irrelevant search results or waiting for answers.
Crafted by experts in machine learning, distributed systems, and consumer applications, Splore.com blends data from the web with walled garden information to provide diverse, tailored results.
Our mission is to be the Knowledge and Discovery engine for this generation, pioneering a new way of discovering and engaging with information in a world that is increasingly digital and diverse in its interests.
What is the role
We are seeking for a Senior Machine Learning Engineer to join our ML/AI team. In this role, you will oversee the entire ML lifecycle, from translating use cases to developing, deploying, and monitoring machine learning models in production environments. Additionally, you will be responsible for the development, mentorship, and career growth of your team members.
Responsibilities
In this role, you will:
Business Use Case Translation: Understand business needs and collaborate with the product and sales teams to define ML requirements and execution plans.
AI Research: Stay updated on the latest AI advancements, especially in generative AI; evaluate potential technologies and apply them to our domain for continuous ML feature upgrades.
Proof of Concept (POC): Design and customize solutions for customer POCs, and evaluate these solutions using appropriate metrics to demonstrate their value.
ML Pipeline: Apply suitable SDLC practices to develop and deploy scalable tools and services for managing ML data pipelines, model training, and inferencing.
ML Tracking and Evaluation: Develop effective tracking mechanisms with relevant data and metrics to continuously monitor ML service performance, and conduct model retraining using appropriate evaluation criteria.
Technical Leadership: Provide technical guidance to junior ML engineers, ensuring high-quality technical delivery and continuous product improvement.
Attributes
We are looking for a Senior Machine Learning Engineer with the following:
Dealing with Ambiguity - You thrive in navigating dynamic environments, making informed decisions amid evolving scenarios and comfortably embracing uncertainty.
Collaborates - We're all about teamwork here. You will work closely with the Product Management and Engineering teams to align long-term AI capabilities and solutions with both business and technical requirements. Strong communication skills are essential for liaising with stakeholders across engineering, product, business, and client teams.
Nimble Learning - We're looking for someone who thrives in a startup environment. You're not afraid to get your hands dirty and learn through experimentation when faced with fresh challenges. You're always on the pulse of the latest ML trends and immersing yourself in new technologies.
Functional/ Technical Skills - MS/PhD in Computer Science/Information Technology. (minimum 6+ years experience in ML engineering or a related field)
High proficiency in Python and extensive hands-on experience with DL frameworks such as TensorFlow and PyTorch.
Expertise in MLOps practices, including continuous training, model deployment, and monitoring.
In-depth knowledge of software testing, benchmarking, and continuous integration
Over 5 years of experience working with cloud platforms such as Microsoft Azure, AWS, or GCP, including building custom integrations between cloud-based systems using APIs.
Ability to translate business needs into technical requirements, with a strong understanding of software testing, benchmarking, and continuous integration.
Experience with multi-language systems and proficiency in languages like Go, Java, and C++ are advantageous.
