First it was Google, Amazon and Facebook – now another tech firm has announced big expansion plans in Singapore: Dyson. And some of the company’s current vacancies, in particular those in machine learning, indicate it is targeting similar technology skills to those that banks are also seeking.
Dyson, which shifted its global headquarters from the UK to Singapore in May, announced yesterday that its HQ will be based in the landmark St James Power Station building by 2021. The 110,000 sq ft office will largely house engineers and scientists. Dyson in Singapore wants to double the number of these employees – from 350 to 700 – over the next five years, according to the Straits Times. The news follows Dyson’s decision earlier this month to scrap plans to build an electric car in Singapore.
Dyson does not appear to be waiting until its new office is ready to start hiring more tech professionals – it has 56 Singapore-based engineering vacancies on its jobs site. While some of these role focus on functions such as digital motors, heater control and acoustics, others are in areas in which banks also need staff.
Machine learning is perhaps the main case in point. Banks in Sinagpore, including Citi and DBS, are hiring ML experts to help them power, for example, robo advisers and anti-money laundering systems. But the candidate pool in Singapore is small, and now Dyson has followed Google in making a play for ML talent.
Dyson’s careers site states that it is establishing a machine learning team in Singapore, and is hiring “at all levels” as part of its overall push to build its research capability in the city state. Dyson has a vacancy for an ML lead, who will spearhead recruitment for the new unit. You’ll also need to be an expert in “feature extraction, time series analysis, signal processing, and statistical modelling” to land Dyson’s top ML job in Singapore.
In common with all ML jobs at Dyson, the team-lead role involves collaborating across “multi-disciplinary engineering teams” and even being embedded within those teams when needed. You’ll “act as a subject matter expert” as Dyson seeks to make all its products “tangibly intelligent”.
The ability of pure-play tech firms like Dyson to involve machine learning technologists in business-critical tasks right across their businesses gives them an advantage in the job market, says an IT recruiter in Singapore. By contrast, despite increased adoption of ML by banks such as JP Morgan globally, banks’ ML employees in Singapore are still generally working on niche projects, sometimes within their comparatively small inhouse innovation labs. If you want to make an impact in ML and stay based in Singapore, a big bank may not be your best option.
Meanwhile, other ML positions at Dyson include an associate principal machine learning engineer, who knows Java, Python, C, C++ and Matlab, and has a PhD in Engineering, Computer Science, or Applied Mathematics “with significant industrial experience”. Banks are also seeking similar people, and prefer to hire ML candidates with work experience (although not necessarily in finance) under their belt, rather than those who’ve only just completed their Masters or PhDs.
Dyson founder James Dyson reportedly chose St James Power Station – Singapore’s first coal-fired power station, which has most recently been used as a nightclub – for his new HQ because he wanted “an inspiring place” for staff to work in. Banking technology professionals currently based in CBD skyscrapers or bland Changi Business Park offices may find the funky digs – Dyson is renovating the entire building – particularly appealing.
The historic harbour-front building is also only an 11-minute drive from the British billionaire’s Wallich Residence ‘super penthouse’, the most expensive apartment in Singapore, which James Dyson reportedly bought for S$73.8m earlier this year.
Image credit: J2R, Getty
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