Research Engineer, AI/ML
At a glance
Mid-level AI Research role at Tabs. New York · full-time · $170,000–$235,000 base.
aimlroles summary, based on the employer's posting.
What you'll do
- Take AI problems from early investigation to launch, turning messy financial information into usable products
- Create evaluations tied to user outcomes, then improve systems using error reviews, ablation tests and production feedback
- Balance model quality against cost, speed, consistency, reliability and ease of maintenance
- Build AI features with product and engineering teams to reduce finance teams’ manual work
What you bring
- Strong grounding in statistics and machine learning, with sound judgment about choosing classical models, LLMs or agents
- You have taken ML or AI systems from data and evaluation through production
- You can make progress with noisy data, weak labels and unclear specifications
- Strong Python skills and experience contributing to production software
Who this fits
This role suits someone comfortable owning work across exploration, evaluation and production, and contributing beyond a narrow specialty on a small team. You’ll work onsite in New York five days a week. Candidates can qualify through relevant education and experience, a relevant PhD, or practical work demonstrated through shipped systems, research or open-source contributions.
From the employer
Tabs is the AI Operating System for Revenue, built for modern finance and accounting teams. It combines deep revenue and accounting expertise with the agents and applications needed to run revenue work end to end. Tabs understands customer and contract context, applies accounting logic, and executes critical workflows with built in controls, auditability, and human oversight. With Tabs, finance teams can move from manually managing revenue workflows to directing outcomes while the system executes the work.
The Job
You’ll work on a fast-moving AI team, owning problems from initial exploration through production.
Turn messy financial data and ambiguous problems into working AI products, starting with simple baselines and adding complexity only when it earns its keep
Build evaluations that reflect real user outcomes, then use error analysis, ablations, and production feedback to make the system better
Make practical tradeoffs across model quality, cost, latency, determinism, reliability, and maintainability
Partner closely with product and engineering to build AI features that take real work off finance teams’ plates
What You Bring
Strong statistical and machine learning fundamentals, with good judgment about when the answer is classical ML, an LLM, agents, or something in between
Experience shipping ML or AI systems end-to-end, from data and evaluation through production
Comfort making progress with noisy data, weak labels, incomplete specifications, and imperfect supervision
Experience across several of: classical ML, embeddings, retrieval and reranking, similarity search, model evaluation, LLM applications, and agentic systems
Strong Python skills and the ability to contribute to production software; TypeScript or modern web application experience is a plus
Experience and education
We welcome a range of backgrounds. Successful candidates will typically have one of the following:
A bachelor’s degree in a relevant quantitative field plus 3+ years of relevant industry or applied research experience
A relevant master’s degree plus 1+ year of relevant industry or applied research experience
A relevant PhD; doctoral research counts as relevant experience, with 3 years of substantive doctoral research considered equivalent to the experience above
Equivalent practical experience demonstrated through shipped systems, independent research, open-source work, or another nontraditional path
How We Work
We’re a small team, so everyone has a hand in deciding what to build and making it work in the real world.
We ship, learn from real usage, and iterate
We make assumptions explicit, follow the evidence, and communicate tradeoffs clearly
We stick with hard problems and welcome better ideas, regardless of where they come from
We help where the team needs us, even when it falls outside our immediate scope
We collaborate closely in person five days a week
No one gets extra points for making the solution more complicated than the problem.
Even if you don’t meet every qualification, we encourage you to apply. We care most about curiosity, craft, judgment, and drive.
Perks and Benefits (Full-time Employees)
Competitive compensation and equity
Unlimited PTO
Up to 100% employer covered monthly healthcare premium (medical, dental, vision)
Lunch provided via Sharebite, plus dinner for any later in office days.
Parental leave up to 12 weeks
Tax free commuter and parking benefits
Voluntary insurances (Life, Hospital, Critical Illness, Accident)
Employee Assistance Program (Rightway)
Free One Medical Membership
401k
Tabs is an equal opportunity employer. We welcome teammates of all identities and do not discriminate on the basis of race, ethnicity, religion, gender identity, sexual orientation, age, disability, veteran status, or any other protected characteristic. We’re committed to creating an environment where everyone can grow, contribute, and feel comfortable being themselves.