Lead Machine Learning Engineer

The SpringCube team curated the following job opportunity to help you in your

job search. Explore the position below to find your next career move.

Company Overview

This is a global technology consultancy that integrates strategy, design, and engineering to drive digital innovation. With a focus on¹ creating custom software and digital platforms, the company partners with clients across various industries to solve their most complex challenges. They are known for their commitment to social and economic justice and their collaborative, values-driven culture.

Job Description

Lead Machine Learning Engineer

Job responsibilities

This role involves embracing a strategic mindset, contributing to the direction of machine learning (ML) initiatives and aligning technical solutions with broader organizational goals. The individual will play a pivotal role in program inception, shaping the development of new systems and applications from idea to reality, overseeing technical feasibility and resource allocation. They will leverage their deep understanding of modern architectures to lead the development of scalable and maintainable ML systems, ensuring optimal performance and efficiency. Translating client needs into technically feasible and impactful ML applications, driving solution design and deployment within complex, high-stakes projects will be a key responsibility. Ownership of the development and maintenance of ML applications, including ML pipelines, model training and deployment, and monitoring and evaluation is expected. As a key influencer, the individual will champion Responsible AI and effective ways of working within the team, advocating for a culture of excellence and continuous improvement. Navigating intricate technical challenges with proficiency, employing specialized knowledge to troubleshoot issues and guide the team towards successful resolutions is crucial. Staying at the forefront of the evolving field of machine learning, actively seeking out and implementing new technologies and advancements to ensure the organization remains a leader in innovation is important. Fostering a collaborative environment, effectively leading the team through hands-on coding alongside mentorship and guidance, empowering individual growth and knowledge sharing is a key aspect. Measuring and analyzing the impact of ML initiatives, iteratively refining approaches and ensuring solutions deliver tangible value to clients and the organization will be a regular part of the role.

Job qualifications

Technical Skills

The ideal candidate will have experience in developing a technical vision and strategy, keeping it relevant and aligned to the business needs. They should be able to design and execute cross-functional requirements based on business priorities. Experience in writing clean, maintainable and testable code, demonstrating attention to refactoring and readability of the code using Python or Shell is required. Experience with distributed systems and scalable architectures to handle large-scale ML applications is necessary. Familiarity with building, deploying and maintaining ML systems using relevant ML techniques and platforms, i.e.: Scikit-learn, Tensorflow, MLFlow, Kubeflow, Pytorch is expected. Experience with building, deploying and maintaining ML systems and experience with application of MLOps principles and CI/CD to ML is important. A solid understanding of machine learning engineering and data science, familiarity with key ML concepts, algorithms and frameworks, and understanding of ML model lifecycles is required. Experience with designing and operating the infrastructure required to run different types of ML training and serving workloads, i.e.: on-premise vs. cloud infrastructure, infrastructure as code, monitoring, etc. is necessary. Hands-on experience with on-premise and cloud services for building and deploying ML pipelines, i.e.: Azure, AWS, GCP or Databricks and associated ML managed services is expected.

Disclaimer

SpringCube curates tech job listings from various company websites to support tech professionals in Singapore.

1. No Endorsement: Job ads on SpringCube do not imply endorsement of their authenticity or quality.
2. No Client Relationship: This company is not a client of SpringCube unless stated.
3. To Apply: Click the “Apply” button to be redirected to the hiring company’s application page for this job.
4. No Liability: SpringCube is not liable for inaccuracies.