All Content from Business Insider 10月09日
从牙医到苹果机器学习工程师:Anshul Gandhi的职业转型之路
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Anshul Gandhi在牙医行业工作多年后,毅然转型投身科技领域,并最终在激烈的竞争中脱颖而出,成功获得苹果公司的机器学习工程师职位。他的经历证明了跨领域职业转型并非不可能,尤其是在人工智能和机器学习人才需求旺盛的当下。Gandhi通过持续学习、积极拓展人脉和优化个人品牌,逐步积累了必要的技能和经验,最终实现了职业生涯的重大突破。他的故事为那些希望改变职业方向的求职者提供了宝贵的参考和启示。

💡 职业转型可能性:Anshul Gandhi的经历证明,即使是在看似截然不同的领域,如从牙医到机器学习工程师,职业转型也是完全可能的。他通过决心、毅力和持续学习,成功跨越了行业壁垒。

📚 技能积累与教育:Gandhi在决定转行后,积极学习编程语言,并通过硕士学位课程(生物医学信息学)深入掌握了AI和数据科学的专业知识,为进入科技行业奠定了坚实的基础。

🌐 人脉拓展与在线形象:在求职过程中,Gandhi高度重视LinkedIn等社交平台的建设,积极拓展人脉,并分享行业见解,提升个人在AI领域的专业形象,这为他赢得了宝贵的面试机会和内推。

🎯 求职策略:Gandhi强调了选择性申请与主动寻求内推的重要性。他通过建立有意义的在线关系来争取内推,并为机器学习面试做好了充分准备,包括LeetCode练习、模拟面试和系统设计。

🚀 AI行业发展与机遇:文章指出,人工智能工程师是当前增长最快的职业之一,科技公司对AI人才的需求巨大。Gandhi的成功也反映了抓住行业趋势并为之做好准备的重要性。

Anshul Gandhi landed a machine learning job at Apple roughly a decade after pivoting away from a career as a dentist.

When Anshul Gandhi graduated from dental school in India, the idea of working for a company like Apple — let alone as a machine learning engineer — felt far beyond his reach.

But 11 years later, after moving to the US for graduate school and navigating multiple job transitions, that's exactly where he ended up.

During his final years of dental school, Gandhi realized the profession wasn't for him. He and other students had begun treating patients, including performing root canals, dentures, and other procedures. The experience gave him a clearer sense of what day-to-day work in the field would look like.

"Deep down, I knew it wasn't something I wanted to do for the rest of my life," said Gandhi, who's in his 30s and lives in Austin.

So he began exploring other paths. Gandhi said he'd taken computer science courses in high school, which gave him some familiarity with the coding languages C++ and Java. During his final year of dental school, he enrolled in a few programming courses, which he said helped him develop his coding skills. The more he learned, the more confident he felt about pursuing a programming role in the tech industry.

"By the time I graduated, I knew I wanted to start my career in this field," he said.

In the years that followed, Gandhi would set his sights on an even bigger goal: landing an AI role at one of the largest US tech companies. However, his lack of formal education and work experience in the field, combined with a competitive tech job market, posed a real challenge. If he wanted a shot at Big Tech, he knew he'd have to keep building his skillset.

Gandhi is among the professionals who've pursued AI roles in recent years, as major tech companies like Meta and Google collectively invest billions of dollars in AI infrastructure.

While several tech giants have laid off workers in recent years, many are aggressively chasing AI talent and offering eye-popping pay packages. A LinkedIn analysis of job growth rates between early 2022 and mid-2024 found that "artificial intelligence engineer" was the fastest-growing role on the platform.

While AI roles are competitive, some job seekers have found ways to break through. Gandhi shared how he landed interviews at Microsoft and Walmart — and ultimately secured a machine learning role at Apple.

Setting his sights on Big Tech

After graduating from dental school in 2013, Gandhi said he secured a data analysis role in India that provided him with more hands-on programming experience. He also connected with computer science engineers who helped him find online boot camps and side projects focused on AI and machine learning.

While AI is arguably the biggest trend in tech today, Gandhi said that a decade ago, "big data" was the industry's buzzword. His early exposure to AI helped him build expertise that felt relatively niche at the time.

"At that time, nobody was talking about AI," he said.

After a few years, Gandhi decided he wanted more practical knowledge and hands-on experience in AI and machine learning, so he started applying to graduate school programs. In 2016, he moved to the US to pursue a master's degree in biomedical informatics at the University of Texas Health Science Center at Houston. He hoped the degree would give him a strong foundation in AI and data science, while also allowing him to build on his healthcare background.

"It gave me the technical depth I was looking for, while still feeling connected to my previous experience," he said.

After graduating in 2018, he began working as a data scientist until 2021, when he landed a machine learning engineering role at Dell. While Gandhi was generally happy with his new position, he hadn't given up on his goal of working at one of the largest US tech companies.

"I wanted to work on designing large-scale machine learning systems that serve tens of millions of users globally," he said. "And that kind of scale, you only get from working for a company like Meta, Amazon, Google, Netflix, or Apple."

Boosting his LinkedIn presence and pursuing referrals

Around August 2024, Gandhi began looking for a new role, he said. But he soon realized the job market was tougher than he'd previously experienced. He said demand for generative AI-specific skills — rather than traditional machine learning expertise — had surged, and the bar for technical proficiency was higher than ever.

"This round of hiring was totally different," he said.

One of the first steps he took to boost his chances was becoming more active on LinkedIn. At the time, he had about 200 connections, a number a recruiter told him raised concerns about the authenticity of his profile. She expected someone with his experience to have at least hit the "500+" threshold LinkedIn uses to display connection counts.

To boost his LinkedIn presence, Gandhi began connecting with more people. He now has over 500 connections and more than 3,000 followers. Over the past year, he has also begun posting his thoughts on the tech industry, aiming to establish himself as an expert in AI and machine learning.

Gandhi said he learned two other things during the early stages of his job search. One was that he needed to be more selective about what roles he applied for, prioritizing positions that were the best fit.

The other was that he might need a referral to land the type of job he desired, and that he needed to be strategic about how he pursued one. While Gandhi continued to reach out to strangers on LinkedIn for referrals, he said he also began investing time in building a minimal online relationship first.

"When you connect, you don't just say, 'Hey, can you refer me?' because nobody has the time," he said. "I realized that you have to keep engaging with their content, sharing your thoughts, and let them know that you not only exist, but are also a thought leader in your field."

It's possible to make a big career pivot

Gandhi said his experience working in the AI field helped him land interviews at multiple companies without referrals, including PayPal. However, he said that a referral from a friend helped him get an interview at Microsoft, and a LinkedIn connection led to a referral at Walmart.

In the fall of 2024, Gandhi accepted a machine learning role at a large healthcare organization that checked many of his boxes. However, he continued to interview for roles he'd previously applied for, and later that year, he landed an offer for a machine learning engineering job at Apple. He started in January and said he's very happy with his role.

Gandhi said he didn't have a referral for the Apple job — it came through a cold application — but he still considers pursuing referrals to be a wise strategy for job seekers. When preparing for machine learning interviews, Gandhi recommends practicing LeetCode problems, mock interviews, and system-design drills — as well as familiarizing oneself with agent-based AI, retrieval-augmented generation, prompt tuning, and inference engines.

Gandhi said among the top takeaways from his job search journey is that career pivots — even unconventional ones — are possible.

"I didn't have a linear path," he said. "I don't think a lot of people have a very pre-planned career path. So you can start over, even if it feels impossible."

Read the original article on Business Insider

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