Machine Learning Engineer ($400k - $600k salary)
Company websitebatoncorporation.com (Baton Corporation, opens in new tab)
Base salary $400K to $600K
Employer-published annual base salary, USD. Advertised base range in New York, NY
You apply on the employer's own site. Six Figure Work does not handle applications.
- LocationNew York, NY
- WorkplaceOn-site
- Status at last checkSource accepting applications when checked
- Last checked (1 h ago) · observed since
About this job
The Company
Baton Corporation is the development company that builds and operates the entire technology stack behind pump.fun, the largest memecoin launchpad in production today. The systems are low latency, high throughput, live under constant load, and break if you get them wrong.
What You’ll Do
As a Machine Learning Engineer, you’ll work alongside engineers and product teams to build algorithms that power personalisation, recommendations, search and real-time decision-making. Your primary focus will be recommendation systems, with opportunities to apply machine learning to fraud detection and content moderation.
You’ll take projects from initial problem definition through to deployment and iteration, owning the models, data pipelines and supporting infrastructure needed to deliver results.
Design, develop and deploy recommendation models that improve discovery, personalisation, engagement and retention.
Build scalable data pipelines and use large datasets to develop features, train models and inform product development.
Develop and optimise machine learning infrastructure, ensuring training and inference systems are scalable, efficient and reliable in production.
Work closely with product teams to integrate models into the platform, supporting low-latency inference and real-time data processing.
Design experiments and combine offline evaluation with A/B testing to measure impact and guide improvements.
Experiment with techniques across deep learning, natural language processing and reinforcement learning where they can solve meaningful product problems.
Monitor, optimise and iterate on deployed models as user behaviour, data and product needs evolve.
Develop models for fraud detection, abuse prevention and content moderation to improve platform quality and user experience.
Collaborate with engineers and data scientists to solve challenges involving high-volume, on-chain and user activity data.
Identify useful developments in ML research and turn them into practical improvements.
Who You Are
An experienced Machine Learning Engineer with a strong foundation in algorithms, data structures and statistical modelling.
Experienced in building and deploying recommendation systems in production, with measurable improvements to user experience or business outcomes. This is our highest-priority area of experience.
Familiar with retrieval, ranking and personalisation techniques, including embeddings, candidate generation and challenges such as cold starts and sparse data.
Proficient in Python and frameworks such as TensorFlow or PyTorch, with strong software engineering skills and hands-on experience deploying models.
Skilled in building and maintaining ML infrastructure, including data pipelines, model deployment, monitoring and systems that scale to large datasets.
Comfortable working across the entire ML lifecycle, from research and experimentation to deployment and maintenance.
Experienced working in startups, delivering at a high pace through ambiguity, shifting priorities and limited resources.
Hands-on and resourceful, willing to build the models, pipelines and infrastructure yourself to get a solution into production.
High-agency and ownership-driven, capable of identifying problems, making decisions and leading projects end to end with minimal guidance.
Highly collaborative, with the ability to communicate technical concepts clearly to engineers, product teams and non-technical stakeholders.
Experience with production fraud detection, abuse prevention or content moderation systems will be highly advantageous.
An interest in blockchain, crypto and SocialFi technologies is a plus.
What it's like to work here
We work in person
Hours can be long and unconventional
The pace is intense
Expectations are high, and impact is immediate
Working at Baton is not for everyone
Why Join Us?
Unmatched ownership and autonomy
Exposure to systems operating at the edge of crypto scale
The ability to ship fast and see real-world impact immediately
If you’re motivated by responsibility, speed, and building products used by massive audiences, you’ll feel at home here.
Source: Baton Corporation on Ashby · View original posting (opens in new tab)
This listingMachine Learning Engineer ($400k - $600k salary)$400K to $600K
Staff Data Scientist - Growth & Marketing ($400k - $500k)$400K to $500K
Staff Frontend Engineer ($400k - $500k salary)$400K to $500K
Staff Solana Program Engineer ($300 - $500k salary)$300K to $500K
Senior Staff Full Stack Engineer ($500k - $1.5m salary)$500K to $1.5M
Senior Staff React Native Engineer ($500k - 1.5m salary)$500K to $1.5M
Product Designer ($300k - $500k)$300K to $500K
Chart as a table
| Role | Published base |
|---|---|
| Machine Learning Engineer ($400k - $600k salary) (this listing) | $400K - $600K |
| Staff Data Scientist - Growth & Marketing ($400k - $500k) | $400K - $500K |
| Staff Frontend Engineer ($400k - $500k salary) | $400K - $500K |
| Staff Solana Program Engineer ($300 - $500k salary) | $300K - $500K |
| Senior Staff Full Stack Engineer ($500k - $1.5m salary) | $500K - $1.5M |
| Senior Staff React Native Engineer ($500k - 1.5m salary) | $500K - $1.5M |
| Product Designer ($300k - $500k) | $300K - $500K |
Observed changes
- Began meeting the published-salary criteria
- First observed on the employer's board
- Observed since
- Employer-stated posting date
- 2026-10-06
Where this pay comes from
Location as the employer wrote it: New York
USD 400,000 – 600,000 · 1 YEAR · Salary
- Method
- Structured pay field published by the employer
- Checked
- Rule set
- us-base-v2
The employer's job board publishes this pay as a dedicated data field. We read the field directly; no interpretation was needed.
What we verified
- The pay figures come from the employer's own listing, quoted exactly above.
- The pay is an annual base salary in US dollars with a minimum of at least $100,000.
- The role was publicly listed on the employer's job board when last checked.
We do not verify what the employer will actually offer, whether the employer is still recruiting for the role, or anything beyond what the employer published. Full methodology.
