Machine Learning Engineer ($400k - $600k salary)
1 нед. назад
400k–600k USD / годСШАSeniorOnsite
machine learningrecommendation systemsdata pipelinesmodel deploymentdeep learninga/b testing
Build and deploy recommendation models and machine learning systems for personalization, fraud detection, and content moderation.
О компании
- 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.
Обязанности
- 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.
Требования
- 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.
Условия
- 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.
Другое
- We work in person
- Hours can be long and unconventional
- The pace is intense
- Expectations are high, and impact is immediate
- Working at is not for everyone