Machine Learning Engineer

Key Skills

Continuous Integration & Continuous Delivery - CI/CD, Docker, GitLab, Google Cloud Platform (GCP), Kubernetes-K8s, Machine learning techniques, Python Programming, REDIS

Job Description

We are seeking a skilled full stack ML engineer who will straight away be responsible for our entire model training and deployment pipeline. By the end of your first year, success would mean: having personally halved our model inference speed and deployment cost, grown our Engineering team from 2 to 10.

We can move from application to offer within 10 days. Find out more about Chai Research on www.chai-research.com/

Requirements:

• Ability to own problems end-to-end, and are willing to pick up whatever knowledge you're missing to get the job done
• Experience building production software/ML systems at scale, bonus for building production apps at scale
• Comfortable building scalable applications and systems from the ground up, with limited development infrastructure available to you
• Knowing TDD is a big bonus

Here are the top 2 reasons why we are not for you:

• Currently, we only have a team of 5, everything gets super chaotic
• We keep our eyes on the prize, implementing fancy tech for the sake of it does not interest us, whereas iteration speed, user retention, and growth rate does

Here are the top 2 reasons why you should join us:

• Exceptional growth and autonomy, you will be working with a team of results-driven engineers and growing the team
• We are super outcome-focused, everything is geared towards delivering the best product and user experience possible, nothing else matters

Here is our tech stack:

• Front end: Python, Flutter, Dart, React
• Back end: Python, GCP, Redis, Kubernetes, Docker, Gitlab CI/CD

Process:

• Apply here
• First round video interview -> Second round panel interview -> Onsite day challenge
• Reference checks, negotiation and offer