Total 2 manufacturing engineer job vacancies in Maintenance / Repair category in Singapore

Salt is hiring Machine Learning Engineer for a yearly renewable contract role. The client’s team make an impact by delivering high-quality cutting-edge AI & IoT products which are closely integrated with the business

Responsibility:

• Implement and maintain machine learning algorithms and edge AI models provided by the data scientist team on Android based IoT devices.
• Integrate machine learning models and optimise performance on Android platforms.
• Work on video and audio processing using machine learning techniques on Android devices.
• Develop sensor data processing algorithms for the applications on Android platforms.
• Provide technical support for product and operations teams.
• Write related technical documentation and contribute to patent applications

Requirements:

• Bachelor’s degree in computer science, Electronic Engineering, or related fields, with 3+ years of experience in machine learning (framework layer & system services related).
• Proven track record of developing machine learning models and algorithms on Android platforms for successful commercial products or projects.
• Proficient in Java, Kotlin, or C/C++ languages, with good programming habits and large-scale software development experience.
• Familiar with Android kernel, including interrupt processing, memory management, process scheduling, device drivers, etc.
• Experience with Android system issue analysis and solving, including deadlock, crash, performance optimization, and low power optimization.
• Proficient in machine learning frameworks such as TensorFlow Lite, PyTorch Mobile, or similar

If this role sounds like your ideal job move, please reach out to me, Jaya at [email protected] alternatively you may apply via the system!

Regret only shortlisted candidates will be notified.

CEI No: R1659595 / EA No: 07C3147

We are hiring Machine Learning Engineer for a technology client on a yearly renewable contract role. The team is building cutting-edge tools and infrastructure to drive innovation and automation throughout the organisation. In this role you will contribute to the creation of new compute layer using Ray and you will help drive the set-up of the infrastructure for Ray on Kubernetes and its integration with the existing Data system

What you’ll do :

• Deliver high-quality AI infrastructure solutions: You will work with the Machine Leaning Platform team to design and develop the infrastructure to support Ray for distributed data processing and model training. You will develop using GitOps to ensure the reproducibility of the system's cloud infrastructure on different Kubernetes clusters.
• Develop observability solutions for Ray: You will be responsible for developing and integrating monitoring and alerting within the client’smonitoring stack powered by Datadog, Prometheus and Grafana. You will also contribute to the creation of runbooks and DevOps guides.
• Support the data science community in adopting Ray: You will work with our product team to socialise Ray's use. You will be responsible for supporting users in running their job on the Ray clusters.

What you’ll need:

• In-depth knowledge of ML-OPS with a solid understanding of distributed computing for data processing. Knowledge of Ray is preferable, but other frameworks, such as Dask, Modin, Beam, Horovod, and Deepspeed, are also valued.
• An understanding of, and ideally experience with, image generation models such as stable diffusion and flux.
• An understanding of ML inference using LLM and other generative models.
• Good knowledge of Python and ML ecosystems.
• Strong understanding of developing and deploying systems on Kubernetes.
• Previous experience with GitOps solutions like ArgoCD is preferred. Good knowledge of Helm and Kustomise is also valued.
• Good DevOps background, with Infrastructure as Code (IaC) such as code with Terraform preferred
• At least 3 years of relevant Machine Engineering experience

If this role sounds like an ideal job move, please hit the apply button with your latest resume alternatively you can email me the resume at [email protected]

Regret only shortlisted candidates will be notified.

CEI No: R1659595 / EA No: 07C3147