Senior Data and ML engineer

• Preferably one strong project utilizing either NLP or computer vision stacks.
• Preferable if you can share a portfolio of work that you can show off -- either on Github, Kaggle, your personal webpage, or something similar.

Other details

• Probation. Let's make it easy for both of us to find out if we enjoy working with each other. We will give ourselves two months - and we get to decide whether we want to continue working with each other after that. Your salary etc. will be unchanged during this time period.
• Flexible place of work. We understand that every engineer has their own preference in working. We have office spaces in Kathmandu and Bangalore -- if you're not comfortable working from home, feel free to use this office space. For the first two months, let us both see what works best for us -- if we find that you benefit from slightly focused guidance, we will insist that you come to office for a few days a week. If we find that you are very successful and are producing high quality results despite being independent and fully remote, then feel free to continue working remotely.
• This is a team that we are building from scratch. The opportunities are immense. Listen to the legendary programmer Dave Cutler

• Collecting data from various disparate sources
• Analyzing collected data
• Visualize and communicate that information to stakeholders.
• Design and train learning models on it.
• Architect and implement the ML-ops aspect of the models---so that the model can be used in production
• Quick prototyping of products to show off how such trained models can be used.
• Mentoring younger engineers
• If interested, engage with the pre-sales, sales conversations on the product. This will give you a sense for how these products are taken to market.
• Documenting and publishing your work on the organization's technical blogs.

• curious: about the different machine learning tools and stacks available. You want to learn by trying out a diverse set of these technologies.
• a go-getter: loves to get things done; has a "let's do it" attitude, and is willing to try out things, fail, prototype, and improve their skill sets.
• sincere and conscientious: it is important you hold yourself to a high bar, have a keen attention to small details, and are sincere to yourself and the work you do.
• proudly owns their work: We want you to own the work you pick up. Invest your thoughts in your work as if the success of the organization depends totally on it.
• keen on learning what it takes to build and ship successful ML technology: You will see that it takes much more than putting together a few libraries.
• enjoys autonomy: you prefer trying out 10x more choices than what your mentor suggested. You will thrive and be productive despite not being spoon-fed how to exactly solve a problem. Start-ups and young engineering teams generally do not have the bandwidth to provide a lot of hand-holding.