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  • Stephanie Hollingshead posted an article
    things to keep in mind, along with specific examples, to help you find and secure top AI talent see more

    Proven Tips for Landing Top AI Talent

    Written by AInBC's Administrative Manager and Athena Pathways Project Lead: Norma Sheane

    Artificial intelligence is a new and emerging field and there are some unique characteristics to look for when hiring for AI roles. Here’s a list of things to keep in mind along with specific examples to help you find and secure top talent.

     

    1.  Define the role with specific terms 

    It’s important to be specific about the AI skillset you need. 

    For example, are you working with neural networks, and if so, do you need someone with experience with GANs? Until recently there were no degrees specifically in AI so there weren’t the obvious pathways into a career that more established disciplines have. Yes, many practitioners have studied machine learning in a Masters or PhD capacity, but you often encounter people skilled in this field who have come to it through a more generalized area of study like mathematics, computer science, data science, or physics.

    If you need to hire someone who can speak French, stating that you need someone from Europe is not specific enough. You need to know what part of the AI universe your job candidates are coming from.

     

    2.  Find lateral thinkers

    The skillset for AI positions is different than for typical software development roles. 

    In the case of developers, projects are typically well defined and structured, with clear milestones, start and endpoints, as well as little follow-up. AI projects often require exploratory and experimental work with unclear timelines. Plus, the nature of an AI system is that it will improve significantly once it gets exposed to first training data and then production data. It will constantly be improving and may require continual attention from the developer.

    AI roles often require interaction and teamwork with a number of people in the organization because data may come from a number of different areas. This is also because the AI teams within a company are typically not large so practitioners need to handle many different parts of the project and the people in the company who interface with the system. 

    Role requirements should include variety and critical thinking because the person in this role may need to "wear a lot of hats" and interface with many different parts of the organization. 

     

    3.  Set your expectations on salaries

    Here are general salary ranges in Canadian dollars for some typical roles:

    ML Researcher - $125,000-$350,000

    Data Scientist - $55,000-$190,000

    ML Engineer - $75,000-150,000

    Data Engineer - $55,000-130,000

    In more senior positions, there is a big difference between good and great in terms of how far someone will be able to take your company.  Expect to pay competitive salaries for people who can easily pick up a job in global centres like San Francisco or Singapore.

     

    4.  Work with agencies who know the area

    If you went to France not knowing the language, would you want a foreign tour company to show you around or a French one that’s connected to the local businesses and knows the language? 

    In AI, there are many places you can look to find different levels of talent but using a generic recruitment agency may not produce effective results as this area is highly specialized. Work with a recruiter with demonstrated knowledge and a network in this area - for example AInBC’s AI role placement service: https://www.ainbc.ai/placements

    Job boards are typically effective however they can generate hundreds of applicants for a single role creating the challenge of filtering through and finding the small percentage of qualified candidates. Some VP’s say that 80% of the applications they’re receiving are not even relevant. For senior roles, the applicant pool may not produce even one individual who will be able to do the job at a high level.

     

    5.  Ensure ethical alignment

    If you are building something that operates in an ethical gray zone - due to it being a rapidly developing area or otherwise - ensure you check the applicant's comfort level. For example, if you aim to make facial recognition technology, the person designing it will need to be comfortable with how your company will deploy it (i.e. for human health vs. for law enforcement). 

     

    6.  For junior talent, ask around at universities

    When looking for junior talent, contact universities as they can provide a number of opportunities to find talent. Professors can make recommendations of top students. You can sponsor hackathons and attend university hiring fairs and poster sessions. Also consider specialized talent programs that recruit students, programs like Insight Data Science.

     

    7.  Check for hard skills

    AI sits within data science, and since data science is a broad discipline which encompasses many skillsets, any number of people can call themselves a data scientist. But that doesn’t mean they know enough to do the job you have. 

    Applicants should be able to demonstrate that they can work with the technologies needed to commercialize the product. Academics may not have needed to code production-ready systems and may have relied on others to do coding work. 

    Applicants should be given a scenario to solve, to demonstrate they can be creative and think outside the box. They should also be able to demonstrate that they stay up to date on the latest developments in AI since the pace of change in the industry is so rapid. 

     

    In summary

    These tips can help you navigate the new realm of hiring AI talent. It also helps if you know someone who’s an AI expert. Reach out to them for a virtual coffee and pick their brain. It will be well worth it to get your data straight and your machines set on “smart”! 

    Do you want to know more about Artificial Intelligence in BC? Check out the AInBC and Athena Pathways websites, or contact info@ainbc.ai for more information.

     

     FOR MORE TECH INDUSTRY TALENT INSIGHTS, CHECK OUT HR TECH GROUP'S BLOG PAGE HERE

  • HR Tech Group posted an article
    Remote recruiting and on-boarding is hard. Here are 10 tips and ideas from tech industry stars. see more

     10 Tips for Remote Recruiting and On-boarding

    Remote recruiting and on-boarding is hard. 

    We recently hosted a webinar on the topic and were fortunate to have Tim Khoo-Jones, Senior Talent Acquisition Lead at Shopify, Saleema Chaudhry, Talent Acquisition Manager at PayByPhone and Ilya Brotzky, CEO and co-founder of VanHack join us for a panel discussion. 

    With such diverse perspectives from an award-winning start-up, a high growth SME and a tech unicorn, I took a lot of notes! Here are 10 tips and ideas from the conversation. 

    Let’s start with sourcing.

    Tip #1. Virtual hiring events are proving effective for sourcing. Consider hosting webinars for candidates so they can learn about your company. Location is no longer a barrier for attending. Attend virtual career fairsbeing organized by post-secondary institutions and industry associations. 

    Tip #2. Virtualize your job postings. The job has changed. Make sure the posting has too. 

    What about assessment? We’re accustomed to bringing someone to our office where we can interview them, test them and watch them interact with a number of different people. How do you assess candidates’ skills and capabilities from afar? 

    Tip #3. Watch out for unconscious bias. It’s magnified in a remote setting. 

    Unconscious bias training is more important than ever. Do more of it. 

    Build your hiring team’s awareness about potential bias “traps”. Check your own biases before starting an interview. 

    Some additional biases that candidates face in a remote interview setting are:

    • Technical difficulties during interview = inability to work from home
    • Lower than average communication skills = inability to perform the job well 
    • Messy background, poor lighting, bad camera angle = general incompetence
    • Inexperienced = too risky. unlikely to perform job well from home

    These are not facts. These are common biases that candidates are facing right now, in a remote setting. Watch for these, on top of other unconscious biases.

    Tip #4. Be flexible with candidates. Internet connections lag and drop. Construction happens next door. Babies cry. Poop happens! Know that it will and prepare to adjust for it. Work to put the candidate at ease when it happens. 

    Tip #5. Try new assessment tools. They won’t always work so you may need to keep trying. Maybe it’s as simple as using shared Google docs. Give candidates “take home projects” to get a sense for their skills. 

    Compensation and relocation need to be considered in a remote model. 

    Tip #6. Determine your compensation and relocation approach before you’re in the thick of it with a candidate. Some companies are stipulating compensation levels based on the local home country of the hire. If they are living and working in Costa Rica, their compensation is X. If/when they relocate to Canada, their compensation becomes Y. Determine if it’s even feasible to have someone work for your company from another country. You’ll need to pay them through a legal entity in the country in which they reside. Is it cost effective to have someone in a high cost global location? Much to consider.

    Remote on-boarding is hard.  

    How do you welcome people and connect them to your organization and your company culture? 

    Tip #7. Education – Figure out what additional context new hires need. Provide more documentation than you did before. Spend more time educating new hires on your tools, processes and expectations. Be very clear on what's expected. 

    Tip #8. Build connection – Build relationships. Focus on building two-way trust. Have weekly one-on-ones between the new hire and their manager. Get everyone in the company/division/team (depending on your size) to reach out and personally introduce themselves to the new hire. Survey the new hires after 1 week, 1 month, 3 months. Tap your ‘cultural leaders’ to connect individually with new hires and loop them in socially. 

    Tip #9. Watch your language!  Don’t inadvertently create a barrier to belonging. 

    Pre-COVID hires worked together in an office. They have a security ID badge. They met Dale’s friendly old dog and they know the receptionist well. They remember hanging out Friday nights at the beer fridge. Post-COVID hires do not. 

    Remove the ‘in-office’ language and lore from stories, conversations and documentation, especially if remote work is here to stay for many months or more.  

    Employee burnout was identified as a challenge right now. Some good mitigation ideas came forward from panelists and participants, like encouraging accountability partners who can hold each other to task to commit to their stated personal boundaries, like setting core hours for a team, and offering additional wellness and mental health resources. (think of these as bonus tips, leading up to tip #10)

    All that said, from interviewing to on-boarding, empathy was the word of the day. 

    Tip #10. Have empathy.

     

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