Machine Learning Engineer

Graphene is an award-winning AI company, developing customized insights and data solutions for corporate clients. With a focus on healthcare, consumer goods and financial services, our proprietary AI platform is disrupting market research with an approach that allows us to get into the mind of customers to a degree unprecedented in traditional market research.

Graphene was founded by corporate leaders from Microsoft and P&G and works closely with the Singapore Government & universities in creating cutting edge technology. We are gaining traction with many Fortune 500 companies globally.

Graphene has a 6-year track record of delivering financially sustainable growth and is one of the few start-ups which are self-funded, yet profitable and debt free.

We already have a strong bench strength of leaders in place. Now, we are looking to groom more talents for our expansion into the US. Join us and take both our growths to the next level!

• Primary Purpose: As part of a highly productive and creative AI (NLP) analytics team, optimize algorithms/models for performance and scalability, engineer & implement machine learning algorithms into services and pipelines to be consumed at web-scale
• Daily Grind: Interface with data scientists, project managers, and the engineering team to achieve sprint goals on the product roadmap, and ensure healthy models, endpoints, CI/CD,
• Career Progression: Senior ML Engineer, ML Architect

• Work in a product-development team capable of independently authoring software products.
• Guide junior programmers, set up the architecture, and follow modular development approaches.
• Design and develop code which is well documented.
• Optimize of the application for maximum speed and scalability
• Adhere to the best Information security and Devops practices.
• Research and develop new approaches to problems.
• Design and implement schemas and databases with respect to the AI application
• Cross-pollinated with other teams.

HARD AND SOFT SKILLS

Must Have

• Problem-solving abilities
• Extremely strong programming background – data structures and algorithm
• Advanced Machine Learning: TensorFlow, Keras
• Python, spaCy, NLTK, Word2Vec, Graph databases, Knowledge-graph, BERT (derived models), Hyperparameter tuning
• Experience with OOPs and design patterns
• Exposure to RDBMS/NoSQL
• Test Driven Development Methodology

Good to Have

• Working in cloud-native environments (preferably Azure)
• Microservices
• Enterprise Design Patterns
• Microservices Architecture
• Distributed Systems