Machine Learning Engineer ($400k - $600k salary)
Batoncorporation · New York
About this role
**Baton Corporation — Machine Learning Engineer** Baton Corporation builds and operates the full technology stack behind [pump.fun](http://pump.fun), the largest memecoin launchpad in production today. Our systems are low-latency, high-throughput, live under constant load, and must be reliable. --- ## What you’ll do As a Machine Learning Engineer, you’ll work with engineers and product teams to build algorithms powering: - **Personalisation, recommendations, search, and real-time decision-making** Your primary focus will be **recommendation systems**, with opportunities to apply ML to: - **Fraud detection** - **Content moderation** You’ll take projects from problem definition through deployment and iteration—owning **models, data pipelines, and supporting infrastructure**. **Key responsibilities:** - Design, develop, and deploy **recommendation models** to 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 **ML infrastructure** for scalable, efficient, reliable training and inference in production - Integrate models into the platform with **low-latency inference** and **real-time data processing** - Design experiments using **offline evaluation + A/B testing** to measure impact - Apply techniques across **deep learning, NLP, and reinforcement learning** when they solve meaningful product problems - Monitor, optimise, and iterate on deployed models as user behaviour and data evolve - Develop models for **fraud detection, abuse prevention, and content moderation** - Collaborate on challenges involving **high-volume, on-chain, and user activity data** - Identify ML research developments and turn them into practical improvements --- ## Who you are - Experienced ML Engineer with strong foundations in **algorithms, data structures, and statistical modelling** - Proven experience building and deploying **recommendation systems** in production with measurable impact (highest priority) - Familiar with **retrieval, ranking, and personalisation** (embeddings, candidate generation, cold starts, sparse data) - Proficient in **Python** and frameworks like **TensorFlow** or **PyTorch**, with strong software engineering skills - Skilled in **ML infrastructure** (data pipelines, deployment, monitoring, scaling) - Comfortable across the full ML lifecycle: **research → experimentation → deployment → maintenance** - Experience in startups; able to deliver at high pace amid ambiguity and shifting priorities - Hands-on and resourceful—willing to build models, pipelines, and infrastructure to get to production - High-agency, ownership-driven, able to lead end-to-end with minimal guidance - Highly collaborative; can communicate technical concepts clearly to technical and non-technical stakeholders - Experience with production **fraud detection / abuse prevention / content moderation** is highly advantageous - Interest in **blockchain, crypto, and SocialFi** is a plus --- ## What it’s like to work here - **In-person** work - **Long and unconventional hours** - **Intense pace** - High expectations with **immediate impact** - Not for everyone --- ## Why join us? - Unmatched **ownership and autonomy** - Exposure to systems operating at the edge of **crypto scale** - Ability to **ship fast** and see real-world impact immediately If you’re motivated by responsibility, speed, and building products
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