Cohere

Pros: I've learned a ton here as a Software Engineer, especially diving deep into machine learning models. The people are super smart, which is great for career growth in this AI startup. We also have a decent hybrid work setup, giving some flexibility.
Cons: The company culture can feel really intense, with a constant push for speed. It's tough to maintain a good work-life balance when the pace is so high. There isn't much focus on team building or social events, making it feel a bit isolating.
Advice to Management: Try to prioritize employee well-being and team cohesion more. A slightly slower pace could improve retention and overall company culture, especially for our engineering roles.

Pros: As an AI Engineer, I've learned a ton about building and deploying large language models. The technical challenges are huge and you're always pushed to grow your skills in NLP. There's a strong focus on innovation, which is great for staying current in the generative AI space.
Cons: The career growth path for ICs isn't super clear once you're past the initial stages. It feels like promotions are slow to come for machine learning roles, and there isn't much formal mentorship beyond your direct manager. This can be frustrating if you're looking to quickly climb the ladder in a startup.
Advice to Management: Create more transparent and structured career ladders, especially for individual contributors in technical roles. Formalize mentorship programs to help engineers see their next steps.

Pros: You do get some flexibility to work from home a few days a week, which is nice for avoiding the daily commute in Toronto. The hybrid work model does let you balance some personal stuff with office collaboration. It's not fully onsite, which is a plus for many in AI development.
Cons: The mandated office days can feel a bit rigid when you have deep work that needs unbroken focus, especially as a Machine Learning Engineer. There's not much room to shift those days if something comes up. It often felt like we were just onsite for the sake of it, not always for crucial collaboration.
Advice to Management: Reconsider the strict hybrid schedule and allow teams more autonomy to decide their in-office days based on actual project needs, especially for roles like Machine Learning Engineers. Trust your employees to get the work done, whether they're in the office or remote from Toronto.

Pros: As a Machine Learning Engineer, my base salary was definitely competitive. The stock options are a big plus if the company keeps growing like it has in the AI startup scene. We also get pretty decent health and dental, which is standard.
Cons: The overall benefits package isn't quite on par with big tech companies. Things like matching 401k or more comprehensive wellness programs aren't really there. You're betting a lot on the stock options, which are still illiquid.
Advice to Management: It would be great to see an improved benefits package beyond just health and dental. Things like better retirement plans or more robust wellness initiatives would make Cohere even more attractive, especially for retaining talent in a competitive AI industry.

Pros: Working remote from Vancouver as a Machine Learning Engineer was a big plus for me. The hybrid model is offered for those near an office, which is decent. You do get some leeway for your personal schedule.
Cons: It's still a fast-paced AI startup, so the expectation for core hours is pretty strong. True work_flexibility isn't always there, especially when project deadlines hit. Sometimes you feel like you need to be constantly online for technical roles.
Advice to Management: Try to set clearer guidelines for remote work and team syncs. It feels like some teams have better work_flexibility than others, which creates an unfair system. A bit more trust in asynchronous work for technical roles would go a long way.

Pros: I've learned a ton working on cutting-edge large language models. The engineers here are genuinely smart, which makes problem-solving effective. For AI Research Engineer roles, the daily work is challenging and interesting.
Cons: Leadership can feel a bit distant from day-to-day operations. Decisions often get made quickly without enough input from us doing the actual machine learning work. It's tough to get clear strategic direction sometimes.
Advice to Management: Try to be more present with the individual teams. Get more feedback before making big strategy changes. This would really help with team morale and understanding the real-world impact on AI development.

Pros: The benefits package is genuinely good, especially for an AI startup. I'm talking decent health insurance and a solid remote work stipend, which is great when you're working remote from Canada. Stock options are there too, but it's early stage.
Cons: Base salary for Machine Learning Engineer roles can feel a bit under market for big tech standards, especially compared to US companies. There aren't many clear paths for rapid salary increases unless you get promoted quickly. Raises sometimes feel like they don't quite keep up with inflation.
Advice to Management: Really look at the base salary bands for senior Machine Learning Engineer positions. Make sure they're competitive with the wider natural language processing market.

Pros: As a Machine Learning Engineer here, I've learned a ton. The compensation package is solid for the AI industry. You're working on cutting-edge natural language processing models. There's a decent hybrid work option if you're in the Toronto office.
Cons: Work-life balance here is often a struggle. It's a demanding startup environment, so be ready for that. Communication sometimes gets lost with all the rapid changes, which can be frustrating.
Advice to Management: Focus on clear communication and managing expectations around workload, especially for hybrid teams. It's a fast environment, but burnout is real.

Pros: As an AI Research Engineer at Cohere in the Toronto office, the base salary was pretty competitive for a startup, especially in the AI industry. The stock options package was also a nice perk. Our health benefits were solid.
Cons: I felt like the PTO policy could really use some work; it wasn't super generous, which made work-life balance tough at times. Also, year-over-year salary increases weren't huge, so it felt like I topped out quickly for my role.
Advice to Management: Consider reviewing the PTO policy to offer more vacation time, especially given the demanding nature of AI development. Also, perhaps more structured yearly compensation reviews for existing employees would boost morale.

Pros: As a Software Engineer in the Toronto office, I've found the work-life balance is generally decent. The hybrid model helps avoid constant burnout, letting me manage my time. It's not the 80-hour weeks you hear about in the AI industry.
Cons: Project deadlines can definitely mean some long nights before a major release. There's an expectation to push hard when things get critical. It can be tough to fully disconnect sometimes.
Advice to Management: Try to smooth out the crunch times more evenly across projects. Also, make sure vacation requests are processed faster for everyone.