MLOps Engineer

MLOps Engineer

New York, New York, USA  - Permanent


Job Description

Our client is an AI platform for accounting firms, providing accountants with a team of AI assistants. Accounting teams integrate the product directly into their accounting software (SAGE, Quickbooks, etc), delegating core workflows and automating time-consuming, manual work.

With a $3.6M seed round led by Better Tomorrow Ventures with participation from BoxGroup, Avid Ventures, several top accounting firms, and leaders from the accounting and machine learning communities.

Many businesses in America rely on their accountant for far more than the traditional roles of maintaining books and filing taxes. For many businesses, accountants are among their most trusted advisors, in charge of steering them through both routine planning and unchartered waters.

Unlocking the potential of these emergent abilities requires far more than chatbots bolted onto the side of a product. It requires being a core part of the workflow. This is why we partner with accounting firms across practice areas to build and iterate on solutions that are native to the workflows. The platform is already serving clients across CFO advisory, assurance, client accounting services, bookkeeping, and more.

Your role:


- Build
- Design evaluation experimentation, and monitoring processes for ML
- Engineer ops systems on cutting edge of complex ML workflows
- Take ownership
- Report directly to co-founders
- Oversee significant parts of our tech and product
- Oversee end-to-end ML ops
- Set culture and practice
- Shape our early engineering culture and processes
- Serve as source of subject matter expertise for rest of engineering team
- Wear multiple hats
- Help hire and build out the rest of the early engineering team - there will be no shortage of responsibility
- Balance long-term thinking and smart abstractions with shipping fast and iteratively

Please Note - This role requires you to be in the office 5x/week in the Flatiron district


Must Have Skills:

•5+ years of experience in MLops and/or engineering
•Experience with Python
•Design, implement, and maintain robust DevOps pipelines for deploying, monitoring, and scaling machine learning runtime environment.
•ML Engineering: Experience building out production ML systems around complex workflows
•Interest in LLMs, NLP, Reinforcement Learning, Probabilistic Graphs, deep
•Manage ML infrastructure, both on premises and in the cloud.
•Excellent communication skills for engaging with both technical and non-technical stakeholders.


Nice to Have Skills:

•Demonstrated passion for startups or early-stage companies.
•Financial services experience.
•Ability to work on either frontend or backend aspects of the project, with some flexibility to move across the stack.
•Experience deploying, optimizating, and maintaining vector databases, and Large Language Models.
•Data engineering/ ETL pipeline experience


Details:

Starting: ASAP







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