Machine Learning Engineer

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New York City, New York / $170000 - $200000 annum

INFO

Salary
SALARY:

$170000 - $200000

Location

LOCATION

New York City, New York

Job Type
JOB TYPE

Permanent

Machine Learning Engineer

Flatiron, New York City - IN-PERSON ROLE 5 DAYS PER WEEK

$170,000 - $$200,000

Harnham is currently partnered with an innovative hypergrowth tech start up that is based out of NYC. This company is focused on creating an AI service for financial and accounting firms to automate workflows with the end goal of saving time and money.

THE ROLE

  • IN PERSON 5 DAYS PER WEEK; FLATIRON NYC
  • Deploy, manage, and scale machine learning models in production environments
  • Maintain the system and make sure it is responsible over time
  • Move research into the production world; strong backend capabilities to contribute to the production code base
  • Data cannot be wrong- needs to be able to scale models efficiently and accurately
  • Organize, scale, and maintain many models that operate in tandem
  • Evaluate and monitor machine learning pipelines
  • Heavily work on data pipelines and the engineering side of business; be ready to own and scale

YOUR SKILLS AND EXPERIENCE

  • Proficient in Python
  • Proven track record of putting models into production
  • Have completed a project from scratch (0-1 architecting, planning, and scaling)
  • Experience working in an accounting environment would be ideal (Other types of financial data are also great i.e. Quickbooks, Plaid, and downstream financial data)
  • Has been in a hyper-growth start-up environment that has previously gone through rounds of funding
  • Strong across LLMs, backend, and product side of business

THE BENEFITS

A competitive base salary of $170,000 - $200,000 will be offered + Equity.

HOW TO APPLY

Please register your interest by sending your resume to Grace McCarthy via the Apply link on this page.

KEYWORDS

Machine Learning | Accounting | FinTech | Start Up | Funding | Python | MLOPs | Research | 0-1 | Infrastructure | Deployment | Scale | Deep Learning

CONTACT

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