What is Splore?
Founded and funded by Temasek and Menyala, Splore is a Human Centric AI Platform that elevates and enhances the customer and employee experience, with a focus on revenue acceleration and cost efficiency.
Splore’s proprietary OS is powered by a trust-and-accuracy-focused, continually learning, multi-agent Answer Engine that can respond to complex queries and execute tasks with support for human-in-the-loop.
Splore empowers businesses to unlock the vast potential of not only their information assets but also leverage Splore's proprietary knowledge index and language models, thereby enabling them to make quicker, more informed decisions. Users get fast, relevant, and trusted answers, thereby eliminating the all-too-common frustration of sifting through irrelevant information or waiting for answers.
Crafted by experts in machine learning, distributed systems, and enterprise applications, Splore blends data from the web with proprietary information and enterprise data to provide tailored results.
Our mission is to help elevate human experiences through empathic access to services and information.
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.
