MLabs Ltd
Member of Technical Staff - Applied ML
Location:
New York, NY (100% On-site) Compensation:
$175,000 - $300,000 (Base Salary) + Highly Competitive Equity We are a rapidly growing AI company that has achieved product-market fit by equipping accountants with a team of autonomous
AI Agents
to tackle real workflows. Backed by world-class investors and experiencing 10x revenue growth in the last five months, we are scaling fast. We are looking for an
Applied ML Engineer
to take full ownership (Responsible Party, or RP) of end-to-end projects, reasoning, experimenting, and shipping agent systems that get smarter over time. This is a high-autonomy role for engineers who want to operate like researchers and builders simultaneously. You will have the freedom to scope projects, define success, run experiments, and decide when systems are ready to ship, always designing for clarity and instrumenting deeply. What you’ll be doing: Agent System Evolution:
Design and iterate on multi-agent architectures that automate complex, real accounting workflows. Encode
autonomy boundaries, tool usage, and fallback behaviors
to make agents safe and reliable. Evaluation & Experimentation:
Build scalable evaluation pipelines (offline and online) to automatically run hundreds of experiments. Define golden tasks, labeling strategies, and metrics to track regressions, error taxonomies, and drive closed-loop improvement. Context & Retrieval Engineering:
Architect
prompt stacks
and instruction hierarchies to structure model reasoning. Build
retrieval and indexing pipelines
that surface context efficiently, including parsing messy documents into structured representations. Model Optimization:
Route, evaluate, and optimize models under real-world constraints (latency, cost, accuracy). Design guardrails and validation layers to keep behavior safe and deterministic. Full Ownership (RP):
Operate as the
Responsible Party —scoping projects with clarity, writing concise specs, building/testing/instrumenting systems end-to-end, and driving delivery. Experience:
3 to 10 years of experience developing complex
data-heavy products and Machine Learning models . Technical Stack:
Strong proficiency in
Python
and experience with database systems like
Postgres . Engineering Fundamentals:
Strong software engineering fundamentals and the ability to instrument deeply and design for clarity. Autonomy & Ownership:
Proven ability to operate with full autonomy, taking ownership from first principles to successful delivery. AI/ML Experience:
Experience designing and implementing systems that leverage LLMs or complex machine learning models in production. Mindset:
A mix of high competence, work ethic, eagerness to learn, and a commitment to building production-quality agentic systems. Equity & Compensation:
Competitive salary ($175,000 - $300,000) with
highly competitive equity
compensation that is well above market rate. Growth & Ownership:
Unprecedented ownership and responsibility from day one in an
extremely fast-growing company
(10x revenue growth in 5 months). Work Policy:
100% On-site
work, 5 days a week, in our New York City (Flatiron) office, fostering interdisciplinary collaboration. Health:
100% employer-paid
medical, dental, and vision
insurance. Office Perks:
In-office lunches
provided. Team:
Join a dedicated, high-caliber team backed by world-class investors and leaders from the ML and fintech communities. Visa Support:
Visa sponsorship is available
for all types. Due to the high volume of applications we anticipate, we regret that we are unable to provide individual feedback to all candidates.If you do not hear back from us within 4 weeks of your application, please assume that you have not been successful on this occasion. We genuinely appreciate your interest and wish you the best in your job search. Commitment to Equality and Accessibility:
At MLabs, we are committed to offer equal opportunities to all candidates. We ensure no discrimination, accessible job adverts, and providing information in accessible formats. Our goal is to foster a diverse, inclusive workplace with equal opportunities for all. If you need any reasonable adjustments during any part of the hiring process or you would like to see the job-advert in an accessible format please let us know at the earliest opportunity by emailinghuman-resources@mlabs.city. MLabs Ltd collects and processes the personal information you provide such as your contact details, work history, resume, and other relevant data for recruitment purposes only. This information is managed securely in accordance with MLabs Ltd’s Privacy Policy and Information Security Policy, and in compliance with applicable data protection laws. Your data may be shared only with clients and trusted partners where necessary for recruitment purposes. You may request the deletion of your data or withdraw your consent at any time by contacting legal@mlabs.city.
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Location:
New York, NY (100% On-site) Compensation:
$175,000 - $300,000 (Base Salary) + Highly Competitive Equity We are a rapidly growing AI company that has achieved product-market fit by equipping accountants with a team of autonomous
AI Agents
to tackle real workflows. Backed by world-class investors and experiencing 10x revenue growth in the last five months, we are scaling fast. We are looking for an
Applied ML Engineer
to take full ownership (Responsible Party, or RP) of end-to-end projects, reasoning, experimenting, and shipping agent systems that get smarter over time. This is a high-autonomy role for engineers who want to operate like researchers and builders simultaneously. You will have the freedom to scope projects, define success, run experiments, and decide when systems are ready to ship, always designing for clarity and instrumenting deeply. What you’ll be doing: Agent System Evolution:
Design and iterate on multi-agent architectures that automate complex, real accounting workflows. Encode
autonomy boundaries, tool usage, and fallback behaviors
to make agents safe and reliable. Evaluation & Experimentation:
Build scalable evaluation pipelines (offline and online) to automatically run hundreds of experiments. Define golden tasks, labeling strategies, and metrics to track regressions, error taxonomies, and drive closed-loop improvement. Context & Retrieval Engineering:
Architect
prompt stacks
and instruction hierarchies to structure model reasoning. Build
retrieval and indexing pipelines
that surface context efficiently, including parsing messy documents into structured representations. Model Optimization:
Route, evaluate, and optimize models under real-world constraints (latency, cost, accuracy). Design guardrails and validation layers to keep behavior safe and deterministic. Full Ownership (RP):
Operate as the
Responsible Party —scoping projects with clarity, writing concise specs, building/testing/instrumenting systems end-to-end, and driving delivery. Experience:
3 to 10 years of experience developing complex
data-heavy products and Machine Learning models . Technical Stack:
Strong proficiency in
Python
and experience with database systems like
Postgres . Engineering Fundamentals:
Strong software engineering fundamentals and the ability to instrument deeply and design for clarity. Autonomy & Ownership:
Proven ability to operate with full autonomy, taking ownership from first principles to successful delivery. AI/ML Experience:
Experience designing and implementing systems that leverage LLMs or complex machine learning models in production. Mindset:
A mix of high competence, work ethic, eagerness to learn, and a commitment to building production-quality agentic systems. Equity & Compensation:
Competitive salary ($175,000 - $300,000) with
highly competitive equity
compensation that is well above market rate. Growth & Ownership:
Unprecedented ownership and responsibility from day one in an
extremely fast-growing company
(10x revenue growth in 5 months). Work Policy:
100% On-site
work, 5 days a week, in our New York City (Flatiron) office, fostering interdisciplinary collaboration. Health:
100% employer-paid
medical, dental, and vision
insurance. Office Perks:
In-office lunches
provided. Team:
Join a dedicated, high-caliber team backed by world-class investors and leaders from the ML and fintech communities. Visa Support:
Visa sponsorship is available
for all types. Due to the high volume of applications we anticipate, we regret that we are unable to provide individual feedback to all candidates.If you do not hear back from us within 4 weeks of your application, please assume that you have not been successful on this occasion. We genuinely appreciate your interest and wish you the best in your job search. Commitment to Equality and Accessibility:
At MLabs, we are committed to offer equal opportunities to all candidates. We ensure no discrimination, accessible job adverts, and providing information in accessible formats. Our goal is to foster a diverse, inclusive workplace with equal opportunities for all. If you need any reasonable adjustments during any part of the hiring process or you would like to see the job-advert in an accessible format please let us know at the earliest opportunity by emailinghuman-resources@mlabs.city. MLabs Ltd collects and processes the personal information you provide such as your contact details, work history, resume, and other relevant data for recruitment purposes only. This information is managed securely in accordance with MLabs Ltd’s Privacy Policy and Information Security Policy, and in compliance with applicable data protection laws. Your data may be shared only with clients and trusted partners where necessary for recruitment purposes. You may request the deletion of your data or withdraw your consent at any time by contacting legal@mlabs.city.
#J-18808-Ljbffr