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Omnifold

MTS - ML Research Scientist

  • Seen live on Omnifold's site today
  • Mid level
Pay
$150k to $300k a year USD
Location
San Francisco HQ
Open for
11+ days
First seen
Oct 24, 2026
Apply on Omnifold's site (opens in a new tab)

Posting record

No flags

Open 11+ days

The posting's record, oldest first
  1. Omnifold's site dates the posting
  2. Ghostless first sees this listing
  3. Last checked: still up
How we know

It hasn't been reposted, listed twice, or left up unusually long, and the posting doesn't say it's a talent pool.

Ghostless records the day it first sees a posting, so a repost can't reset its age. This one was already up when Ghostless started tracking Omnifold, so its true age is longer.

Last checked Nov 4, 2026.

How well do you match?

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What it asks of you

PhD asked for
“PhD or equivalent research experience preferred, but exceptional engineers with relevant industry experience will be considered” (quoted from the posting)

What the posting discloses

Pay
$150k to $300k a year USD
Compensation: $150K to $300K base | Equity | Health, dental, vision | 401(k) (quoted from the posting)

Not stated: Real vacancy, AI screening.

Why these three

Ontario requires postings from employers with 25 or more staff to state the pay, whether the vacancy exists, and whether AI screens applicants.

Skills mentioned

About the role

Member of Technical Staff, ML Research Scientist

Omnifold trains custom AI models for each customer's supply chain - purpose-built systems that forecast demand, optimize decisions, and adapt continuously to a changing world. The research team is responsible for the core intelligence that makes this possible: developing new model architectures, curating proprietary data assets, and pushing the boundaries of what ML can do.

What makes this job interesting

  • You will work on problems that frontier models can't solve. Supply chain dynamics require modeling physical systems and processes.
  • You will own the full research cycle, from hypothesis to production model, with direct visibility into real-world impact.
  • You will work at the intersection of machine learning models, optimization, LLM reasoning capabilities, and proprietary data - a combination few research teams are building

What you'll own

  • Designing and training models for forecasting and optimization across complex, multi-variable supply chain environments
  • Building and curating proprietary data assets that carry signal about real-world physical and commercial systems
  • Integrating LLM knowledge and reasoning capabilities into purpose-built models to maximize accuracy and adaptability
  • Continuously improving model performance as market conditions shift (consumer sentiment, product launches, geopolitical changes, competitive dynamics)

What we're looking for

  • Strong foundations in machine learning — experience developing and evaluating forecasting models, and LLM pipelines
  • Deep understanding of time-series forecasting, optimization, or related domains
  • Experience working with messy, heterogeneous real-world data
  • PhD or equivalent research experience preferred, but exceptional engineers with relevant industry experience will be considered
  • Comfort operating in a fast-moving, early-stage environment where research directly feeds production systems

Location: San Francisco (in-person, 5 days per week)

Omnifold’s Mission

Every bad forecast has a physical consequence. Unnecessary goods are manufactured, shipped, and stored. Emergency air freight is needed for misallocated products. Poor production planning means workers show up with nothing to do, or work frantic overtime. Inefficiency is everywhere.

Our mission is to eliminate waste and accelerate growth for every company with physical products.

Compensation: $150K to $300K base | Equity | Health, dental, vision | 401(k)

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