1 point by exampleco 2 years ago flag hide 15 comments
curiousdev 2 years ago next
Interesting! I would love to learn more about ExampleCo's machine learning projects. Any insights on what kind of problems they are trying to solve?
ml_engineer_at_ex 2 years ago next
Hi curiousDev! At ExampleCo, we primarily focus on NLP problems, working on advanced text analysis tools and conversational AI applications. We have made some exciting progress in speech recognition and NLG as well!
oldschool_coder 2 years ago prev next
I remember ExampleCo from the old days of bootstrapping! Good to see they're doing well and scaling up their engineering team. Any senior ML engineer they hire is sure to face interesting challenges.
optimize_all_things 2 years ago prev next
You're hiring a Senior ML Engineer? Looking for expertise in ML infrastructure, scalable data processing, and cloud computing?
ml_engineer_at_ex 2 years ago next
Hey optimize_all_things! We appreciate your interest in our hiring process. The ideal candidate will have a strong foundation in ML, including experience with TensorFlow, PyTorch, and deep learning techniques. Moreover, we love engineers who have a heavy focus on optimization and automation to help our ML models scale seamlessly.
deploying_ml 2 years ago prev next
Implementing CI/CD for ML models is critical too, right? Version control for data, reproducibility in experiments, and automated testing?
ml_engineer_at_ex 2 years ago next
Absolutely, deploying_ml, you're spot on. Practices like data versioning and model card generation are essential for robust machine learning applications. Replicability and testing of experiments are high up on our priority list!
tech_thoughts 2 years ago prev next
Curious about the incentives/KPIs of the ML engineer. Are you emphasizing model accuracy, or are there a balance of business/technical metrics in their target?
ml_engineer_at_ex 2 years ago next
Interesting question. Here at ExampleCo, we ensure that there is a healthy balance of both technical and business metrics. Of course, model performance is important, but we also consider factors like deployment frequency, experimentation time, and model performance in production. We make sure that our engineers are rewarded for their contributions in various areas.
academic_ml 2 years ago prev next
Does ExampleCo encourage the publication of research papers? How much time is allotted for academic pursuits in this role?
ml_engineer_at_ex 2 years ago next
Hi academic_ml. While our first priority is developing and deploying reliable ML models to improve our products, we firmly believe in sharing knowledge and contributing to the academic community. Our engineers can allocate approximately 20% of their time to research activities and publishing papers. You'll find many of our engineers present their work at premier conferences like NeurIPS and ICML.
job_seeker_tf 2 years ago prev next
I see you're using TensorFlow for your ML projects; any preference for candidates with TensorFlow certifications? Also, how much on-the-job training is provided?
ml_engineer_at_ex 2 years ago next
@job_seeker_tf, certifications aren't a strict requirement, but they certainly help demonstrate understanding. We usually look for candidates with hands-on experience in designing ML models using TensorFlow or PyTorch, but those with certifications have an edge! And yes, we do provide on-the-job training to help new hires adapt to our tech stack quickly. We organize regular workshops, meetups, and one-on-ones!
hiring_process_question 2 years ago prev next
What's the hiring process like? Is there a coding test, pair-programming, or just an interview with ML/technical questions?
ml_engineer_at_ex 2 years ago next
Hello hiring_process_question! Our process includes an initial phone/video discussion about your research background and problem-solving skills. Then we move on to a take-home coding challenge to test your capability in designing ML models and working with data. After that, we usually have a final round of interviews with our team members, where we discuss various ML topics and your experience in-depth.