Software Engineer [ML Tooling & Production] (Global Remote)

About MTailor

At MTailor, we are building the world’s most accurate body and clothing measurement technology through machine learning and computer graphics.

Highlights about MTailor:

• Profitable e-commerce business with $5M+ in annual revenue
• Fully remote and globally distributed, with teammates currently in 3 continents
• Backed by Y Combinator and Khosla Ventures
• Current ML measurement technology is 20% more accurate than a professional tailor
• Building groundbreaking new 3D Reconstruction and visualization technology to measure & preview clothing fit and end online returns as a new SaaS offering
• Founder is a Stanford alum who turned down the one of the largest Shark Tank deal ever and has been recognized on the Forbes 30 Under 30 List

About the Role

We're seeking a Software Engineer [ML Tooling & Production] with skills to productionize, optimize, and manage our end-to-end ML and non-ML production systems.

Responsibilities:

• Design, implement, maintain, and troubleshoot data processing pipelines and backend services, including data management, application deployment, data analysis, system administration, automation scripting, and general software development as needed
• Maintain and improve our production infrastructure and performance (e.g., resource utilization, cost optimization, response times, scalability)
• Stay up-to-date with the latest developments in software engineering and MLOps/DevOps practices, and continually improve the team's processes and tools to ensure efficient and effective delivery of projects
• Develop and distribute documentation and guidelines for best practices for the team
• Architect our software systems [both ML & non-ML] for modularity, adaptability, performance, and developer productivity
• Provide versatile technical support to the ML team, addressing needs ranging from environment setup and tool integration to data manipulation and performance analysis
• Other duties as assigned (we’re small and closeknit, so nothing is “not my responsibility”)

Requirements:

• Excellent in Python
• Excellent in scripting
• Medium in PyTorch
• Excellent in developing and deploying production-grade backend services and APIs.
• Excellent in implementing and managing automated cloud infrastructure and CI/CD pipelines.
• Extensive familiarity with the “reproducibility” problem of ML experiments
• Great understanding of general devops principles, e.g., continuous integration / deployment pipelines, git
• Experience with containerization technologies, such as Docker
• Experience with cloud computing platforms, such as AWS / GCP / Azure
• Understanding and experience working with web APIs and databases
• Understanding of concurrency and experience applying multi-threading concepts
• Comfortable with working from home:
• Self-disciplined on consistent work schedule and proactive communication
• Maintain a higher level of social life outside of work (e.g., friends, family, hobbies)

Successful Candidate Attributes:

• Can work independently, is a self-learner, and can self-unblock when stuck
• Loves learning new skills (for example: new frameworks, new MLOps platforms, new cloud vendors)
• Is comfortable in a variety of engineering settings, from jupyter notebooks, to scalable software engineering, to quick-and-dirty python scripts
• Thrives on technical variety, effectively handling tasks across data, scripting, systems, and software development both with and within the ML context
• Is practical and focused on end results → you are to be the glue that makes sure our research scientists are productive, and their work makes it into production
• Loves writing well documented code

Pluses:

• Basics of linear algebra, calculus, probability and statistics
• Familiarity with deployment of neural networks on different hardware with varying performance requirements
• Experience and understanding of techniques to compress / quantize machine learning models
• Experience and understanding of distributed training techniques
• Experience with any MLOps tools like ClearML, WandB or DVC
• Understanding of ML-specific computational complexity in code
• Experience with handling / transferring large image/video data across vms / cloud providers
• Excited to work from home

Current MTailor Tech Stack:

• Azure tools: Virtual Machines, Blob Storage.
• AWS tools: EC2, S3, Lambda, API.
• GCP tools: Filestore, Compute Engine.
• Python
• PyTorch
• Github/Github Actions
• Skypilot
• ClearML

Fill out this form to start the Interview Process:

https://forms.gle/mFeQW1q66HWGgnPi7

Note:

• Once you have submitted the Google form, we will send you an email containing the link to the (1 hour) initial screening test. Please note that you will have three days from the time you receive the link to complete the initial screening.

• Once you have successfully passed the initial screening test, you can expect to receive two important emails from us. The first email will provide details about the next round of the interview process. The second email will contain a Calendly link, allowing you to schedule a 15-minute information call with our ML Tech Lead to learn more about MTailor, our company culture, and the job role.

The salary range for this job post is between $35,000 - $40,000 USD per annum, depending on the exact experience and the qualification.

MTailor Company Values

• Testing and Data - we like to test ambitious hypotheses with the lowest amount of effort
• The Customer - we always start with what the customer wants (for both new features and product simplifications)
• An Excellent Work / Life Balance - everyone has a life outside of work (and we encourage that); we are focused on results, not time in the virtual office
• Self-Motivation - it is frequently up to you to design and execute new initiatives
• Collaboration and a friendly environment (we hate office politics)

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Interview Process Overview:

We believe candidates should know what our entire interview process looks like in advance for better understanding and expectations. Our process is:

1. A short online coding assessment (1 hours)
2. A larger take-home code project, after which you will send us a recording of your demoing the code and walking us through it and the decisions you made (6 hours)
3. Two one-hour live interviews on Zoom with one of our engineers which will involve a coding challenge and discussion of your technical qualifications
4. Up to 2 more live interviews with MTailor management or the CEO to discuss your qualifications and answer any questions you have about the position