ML Data and Experiment Infrastructure Engineer

HushOne, Inc.; Kirkland (WA); On-site; USD 150,000 - 210,000; Full time

Benefits offered by this job

Stock options

401(k) with company matching

Health, dental and vision coverage

Life and disability insurance

Gym membership

Remote-friendly / work from home days

Referral program

Job summary

HushOne, Inc. is building a robust ML research infrastructure to ensure traceability of results and decisions.

The role focuses on versioning datasets, model artifacts, experiment configurations, and evaluation results while keeping data lineage strong and ensuring privacy-conscious data handling. You will deliver pipelines with provenance, quality checks, and reproducible processes, coordinating with privacy engineers to separate household data from shared datasets and manage retention and

Qualifications

• Data systems, ML operations, or scientific computing experience.
• You have detected contamination, data drift, or an irreproducible result, and can describe how.
• You build lineage that survives people being in a hurry.
• You treat evaluation data as something to protect from leakage.

Responsibilities

• Trace a model-quality regression after a dataset update and explain which artifacts are necessary to reproduce it.

Skills

Data systems

ML operations

Scientific computing

Data lineage

Data leakage prevention

Experiment reproducibility

Job description

You make research results and model releases traceable to the data and decisions that produced them. Most irreproducibility is a data-lineage problem rather than a modelling one, and this role is the infrastructure that makes learning responsibly possible rather than aspirational.

The work

Version datasets, model artifacts, experiment configurations and evaluation results. Build provenance, quality checks and reproducible pipelines. Separate household data from shared research datasets, and coordinate deletion and retention behavior with privacy engineers.

What good looks like

In your first 90 days, deliver a reproducible experiment pipeline with dataset lineage and release checks that block unapproved inputs.

Evidence we look for

Bring experience with data systems, ML operations or scientific computing. Show how you have detected contamination, data drift or irreproducible results.

Required

• Data systems, ML operations, or scientific computing experience
• You have detected contamination, data drift, or an irreproducible result, and can describe how
• You build lineage that survives people being in a hurry
• You treat evaluation data as something to protect from leakage

Nice to have

• Experiment tracking and model registry systems
• Data versioning at scale
• You have built infrastructure researchers voluntarily used

The exercise

Trace a model-quality regression after a dataset update and explain which artifacts are necessary to reproduce it.

How we work

We work together in the office, five days a week, and you can be based at any of our garages: Kirkland Garage (Kirkland, WA); UAE Garage (Dubai, Dubai). We hire across the United States, India and the UAE. We are remote-friendly around family: if you need to work from home some days to look after the people you love, we arrange that with you one person at a time, and we encourage people to use it rather than tough it out.

Pay

We publish what we pay. Indicative ranges by market and level are on our compensation page, and they are realistic going market rates rather than headline numbers. Wherever we hire we pay at least the local market rate, and for full-time roles our floor is a living wage, never the statutory minimum. Compensation is reviewed every year and on promotion.

Equity

Every full-time teammate gets stock options. Four-year vesting with a one-year cliff, sized to role, level and impact, and confirmed in writing at offer. High performers earn refresh grants.

Bonus and commission

An annual performance bonus tied to clear company and personal goals, indicatively 10 to 20 percent of base for non-sales roles. Customer-facing roles carry on-target earnings, typically a 50/50 split of base and variable, with uncapped commission and accelerators above quota.

Health and peace of mind

Medical, dental and vision for you and your family, plus life and disability cover. We have chosen the highest plan tier available to us rather than the cheapest one that clears the bar, because the point of this is that you never have to think about it. The specific plan numbers are confirmed in your offer letter.

401(k) with company matching

A 401(k) with a company match, so the years you spend here compound into something that is yours whatever happens next. The match formula is confirmed in your offer letter.

AI tokens

A budget of AI tokens of your own, because a company that says you should own your AI cannot be the company that rations it. Use them on the work and on whatever you are curious about.

Gym, and the everyday things

A gym membership, and a corporate benefits programme with its own app, where you redeem real discounts with a long list of retailers on the ordinary purchases of a life.

Family

We are remote-friendly around your family, arranged one person at a time, and we would rather you took it than toughed it out.

Referrals

Refer someone we hire full-time who stays a year and you get $1,000 plus $10,000 in referral stock-based equity, on top of your own package.