Description review
Machine Learning Engineer
Quincus · Canada · back to the listing
HR standards
51/100
needs work
Title ↔ description
85/100
strong
Reads as
Machine Learning Engineer
100% confident
What this role officially is
data scientist — ESCO, the EU occupation classification
Data scientists find and interpret rich data sources, manage large amounts of data, merge data sources, ensure consistency of data-sets, and create visualisations to aid in understanding data. They build mathematical models using data, present and communicate data insights and findings to specialists and scientists in their team and if required, to a non-expert audience, and recommend ways to apply the data.
Also known as: data scientists, data engineer, research data scientist, data expert, data research scientist
How others title the same work
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Startups
- Attendi | Medior Machine Learning Engineer | Amsterdam, Netherlands | ONSITE (hybrid) | €6,000 - €7,000 per month | Full-time (80–100%, ~4–5 days/week) | Visa sponsorship + 30% ruling possible Attendi
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- Arcforma AI (arcforma.ai) | AI Engineer (Marketing / Construction / Arcforma AI (arcforma.ai)
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What the listing never says
- 19 bullet points. Long requirement lists deter qualified candidates, who read them as hard gates. Scope clarity
- No pay range published. Candidates cannot tell whether applying is worth their time. Pay transparency
- No location or timezone policy stated, so a candidate cannot tell where they may work from. Scope clarity
The listing, marked up
Nothing in the wording of this listing tripped a check. The scores above still judge how complete and coherent it is.
“Make every logistics journey your best one yet”
The Company.
Founded in 2014, Quincus is a B2B supply chain operating SaaS platform headquartered in Singapore. We solve today's global supply chain challenges with groundbreaking technology. Using AI and machine learning, we have digitized and optimized the logistics process while giving customers full transparency into their supply chain.
Quincus was founded by two visionary entrepreneurs who possess more than a decade of experience in tech. Chief Product Officer Katherina-Olivia Lacey is leading a tech revolution in this space while empowering women in the supply chain industry. Jonathan E. Savoir, Chief Executive Officer, appeared on Forbes' 30 Under 30 Asia List in 2020, and also serves on the boards of several startups.
Overview.
Quincus Research is building the next generation of intelligent systems for all Quincus products. To achieve this, we’re working on projects that utilize the latest computer science techniques developed by skilled software engineers and research scientists. Quincus Research teams collaborate closely with other teams across Quincus, maintaining the flexibility and versatility required to adapt new projects and focuses that meet the demands of the world's fast-paced business needs.
Job Overview.
We are looking for a highly motivated and experienced machine learning engineer to join our team and help us develop and deploy deep learning and reinforcement learning algorithms at scale. As a machine learning engineer, you will be responsible for designing and implementing scalable systems for serving models, optimizing inference performance, and managing production workflows.
Responsibilities:
• Design and implement scalable systems for serving deep learning and reinforcement learning models.
• Optimize inference performance of deep learning and reinforcement learning models using techniques such as quantization, pruning, and distillation.
• Utilize GPU computing to accelerate model training and inference.
• Develop and deploy production workflows for training and serving machine learning models.
• Collaborate with data scientists and software engineers to design and implement machine learning systems.
• Monitor and improve the performance of machine learning models in production.
• Stay up-to-date with the latest research and techniques in deep learning and reinforcement learning.
Qualifications:
• Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related field.
• 3+ years of experience in software engineering or machine learning engineering.
• Strong programming skills in Python (C++ or Java a plus)
• Experience with deep learning frameworks such as TensorFlow or PyTorch.
• Experience with GPU programming using CUDA, OpenCL, or similar libraries.
• Experience with distributed systems and cloud computing platforms such as Kubernetes, Docker, GCP, and AWS.
Preferred Qualifications:
• Ph.D. in Computer Science, Electrical Engineering, or a related field.
• 5+ years of experience in software engineering or machine learning engineering.
• Experience with reinforcement learning algorithms and frameworks.
• Experience with production deployment of machine learning models and implementation of APIs for big data.
• Strong understanding of computer architecture and performance optimization.
• Strong communication and collaboration skills.
If you are passionate about developing and deploying machine learning algorithms at scale, and want to join a dynamic team working on cutting-edge technology, we encourage you to apply for this position.
Originally posted on Himalayas
The Company.
Founded in 2014, Quincus is a B2B supply chain operating SaaS platform headquartered in Singapore. We solve today's global supply chain challenges with groundbreaking technology. Using AI and machine learning, we have digitized and optimized the logistics process while giving customers full transparency into their supply chain.
Quincus was founded by two visionary entrepreneurs who possess more than a decade of experience in tech. Chief Product Officer Katherina-Olivia Lacey is leading a tech revolution in this space while empowering women in the supply chain industry. Jonathan E. Savoir, Chief Executive Officer, appeared on Forbes' 30 Under 30 Asia List in 2020, and also serves on the boards of several startups.
Overview.
Quincus Research is building the next generation of intelligent systems for all Quincus products. To achieve this, we’re working on projects that utilize the latest computer science techniques developed by skilled software engineers and research scientists. Quincus Research teams collaborate closely with other teams across Quincus, maintaining the flexibility and versatility required to adapt new projects and focuses that meet the demands of the world's fast-paced business needs.
Job Overview.
We are looking for a highly motivated and experienced machine learning engineer to join our team and help us develop and deploy deep learning and reinforcement learning algorithms at scale. As a machine learning engineer, you will be responsible for designing and implementing scalable systems for serving models, optimizing inference performance, and managing production workflows.
Responsibilities:
• Design and implement scalable systems for serving deep learning and reinforcement learning models.
• Optimize inference performance of deep learning and reinforcement learning models using techniques such as quantization, pruning, and distillation.
• Utilize GPU computing to accelerate model training and inference.
• Develop and deploy production workflows for training and serving machine learning models.
• Collaborate with data scientists and software engineers to design and implement machine learning systems.
• Monitor and improve the performance of machine learning models in production.
• Stay up-to-date with the latest research and techniques in deep learning and reinforcement learning.
Qualifications:
• Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related field.
• 3+ years of experience in software engineering or machine learning engineering.
• Strong programming skills in Python (C++ or Java a plus)
• Experience with deep learning frameworks such as TensorFlow or PyTorch.
• Experience with GPU programming using CUDA, OpenCL, or similar libraries.
• Experience with distributed systems and cloud computing platforms such as Kubernetes, Docker, GCP, and AWS.
Preferred Qualifications:
• Ph.D. in Computer Science, Electrical Engineering, or a related field.
• 5+ years of experience in software engineering or machine learning engineering.
• Experience with reinforcement learning algorithms and frameworks.
• Experience with production deployment of machine learning models and implementation of APIs for big data.
• Strong understanding of computer architecture and performance optimization.
• Strong communication and collaboration skills.
If you are passionate about developing and deploying machine learning algorithms at scale, and want to join a dynamic team working on cutting-edge technology, we encourage you to apply for this position.
Originally posted on Himalayas