Senior Ml Engineer

Website: https://www.invisible.co/
Blog: https://inv.tech/blog
Overview/Sales Deck: https://docsend.com/salesdeck
Recorded Demo: https://www.youtube.com/demo
Core Values: https://www.notion.so/invisibletech/Invisible-Values
Invisible Technologies stands at the forefront of operations innovation. We remove strategic roadblocks for clients, providing solutions to the world's most complex business problems. A technology-led managed execution service, our success is driven by our powerful process orchestration platform, which blends the perfect mix of artificial and human intelligence with automation to create extraordinary growth and scale opportunities for clients
We have experienced exponential growth, quadrupling in size year over year for the past three years. By the conclusion of 2023, we are on track to achieve an annual recurring revenue (ARR) of $100 million. Operating as a profitable business, we maintain a near complete ownership stake, with a firm foundation built on robust financial management. As part of our commitment to our team, we are excited to offer substantial equity compensation, presenting life changing equity opportunities for our Partners.
The Role
As a Senior ML Engineer, your job is to evaluate and design AI/ML solutions in coordination with your team to have a measurable impact on our business outcomes. In this role, you partner directly with your team manager and other team members to evaluate and integrate new AI models into our platform offering. The resulting solutions are focused on task categories but remain independent of specific business use-cases, yielding reusable AI Enablement value across client verticals.
Culture
We believe in continuous learning and growth, and as a senior, we expect you to model this learning culture within your team. You have the opportunity to fill in the gaps in your own knowledge of emerging technologies as well as mentoring others along their learning journey. A key purpose of your role is to define standards for AI experimentation and model usage within our platform and demonstrate to your team how those standards will be upheld.
Execution
Execution is key to our operations and growth. We expect you to commit to delivery and effectively prioritize tasks to make sensible, expedient progress. As a senior member of your team, you remove obstacles to successful delivery for other engineers around you as well as delivering on the outcomes of your own work.
We are a remote team, so communication is crucial - commit publicly to what you will accomplish, carry out the work, and then demonstrate the outcome when it is delivered.
The Technology
Our platform is built in Typescript and Python.
Our software engineers use NextJS, React, Django, Postgres, Kubernetes, and GraphQL.
Our ML team is continuously evaluating new AI models and integrating them into our platform.
We're always eager to learn and try new technologies where they are practical.
Requirements

• You are comfortable solving problems in remote team environments. Our team spans the globe, and requires excellent communication and teamwork to succeed.
• You are able to partner directly with Product Managers and demonstrate leadership within your team. As a senior member of your team, you cut through complexity in requirements to determine right-sized commitments for implementation.
• You can analyze and author documentation. You will need to research and synthesize new technologies (model, frameworks, libraries, techniques), explain them to your team, and evangelize their usefulness in our platform on a regular basis.
• You have strong experience with Python and AI/ML libraries (Pandas, LangChain, PyTorch, Keras, scikit-learn, etc.). You are comfortable publicly weighing the pros and cons of each technology, as well as incorporating your insights into production-ready code.
• You understand the underlying theory and capabilities of widely-used machine learning models.
• You have proven expertise in partnering with software engineers to deploy machine learning models that solve real world problems. Your team includes software engineers, but you know enough about MLOps to establish success metrics for your models in production.

Location

• Currently, we're looking to hire in North/South America to ensure reasonable time zone overlap with our existing teams and stakeholders.

Working Schedule

• The candidate should be available between 10am to 3pm EDT from Monday to Friday.

Compensation:

• Working Times: US (EST or PST) Hours
  • Compensation Breakdown
    • $105k Base
    • $35k Target Cash Bonus
    • $40k-$96k Equity
    • Total Comp: $180k - $236k = $140k Max Cash + $40k-$96k Equity
    • Equity value based on $200M-$500M valuation range, and represents 1 year of vesting.
    • Total equity grants are on a 4-year vesting schedule with a 1-year cliff.
  • Flexible Work Schedule / Unlimited Vacation Days
  • Work Remotely