Medium · 1 day ago
Staff Applied Machine Learning Scientist
United States
Full-time
Remote
Senior Level, Lead/Staff
$250K/yr - $300K/yr
7+ years expMedium is a company dedicated to deepening understanding of the world and spreading significant ideas through its platform. They are seeking a Staff Applied Machine Learning Scientist to own and enhance their recommendation systems, develop machine learning models to combat spam, and explore new applications of machine learning across the business.
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Responsibilities
You’ll help us apply machine learning thoughtfully across Medium - starting with recommendations, but extending far beyond them. You’ll look for places where ML can make the reading and writing experience more personal, relevant, and human
Experiment with ideas like smarter post discovery that helps writers find their natural audience
Explore opportunities for personalization, quality detection, topic modeling, or even AI-assisted editorial curation - all grounded in improving understanding, not chasing engagement for its own sake
Work closely with design, product, and engineering partners to translate ambiguous user needs into well-framed ML problems
Drive the research. Lead with curiosity and precision. You’ll design and interpret experiments, bring statistical rigor to our experimentation, and keep a critical eye on things like bias and spurious correlation in our thinking
Bring organizational leverage. Work across teams to ensure that ML improvements are well-integrated into the product, not off to the side. You’ll regularly influence decision-making through cross-functional collaboration, helping product and engineering leaders spot where ML can create leverage and where it shouldn’t
Own and continuously improve our recommendation systems. Evolve our two-tower retrieval and ranking stack, refine our feature set, and push on model quality, latency, and interpretability
Find new and innovative ways to use ML techniques to better serve our community of readers and writers. This might mean smarter spam and slop detection, writer quality modeling, or intelligent routing of human moderation. The goal: keep Medium a place where humans thrive, not bots
Positively contribute to the broader culture and data ecosystem at Medium. Mentor others, document your work with clarity, and help raise the bar for how we think about, design, and deploy ML systems. Share learnings generously and make the people and systems around you better
Attend Medium’s twice-yearly, in-person offsites (hosted in locations around the U.S.)
Qualification
Required
You've been designing and building software for at least 7 years, with at least 3 years focused on architecting and shipping consumer-facing ML models
You have experience integrating ML into end-user products (recommendation, ranking, personalization, moderation). You have a proven track record of developing and deploying ML models that deliver measurable business and user impact, not just theoretical gains
You embody the 'applied' in applied ML: You enjoy the research, but love seeing models ship, move metrics, and make people's experiences better
You're fluent in Python and ML libraries such as TensorFlow, HuggingFace Transformers, and scikit-learn. You're comfortable taking models from notebook to production. It's a huge added bonus if you have experience with Apache Spark for distributed or large-scale training
You're an excellent collaborator, able to translate between data, product, design, and engineering worlds, helping non-ML partners see what's possible (and what's not). You're excited to be 'the voice of ML' in business and product conversations
You're skilled at identifying and evangelizing high-leverage ML opportunities across the organization, from recommendation systems to new personalization or quality signals
You have hands-on experience with modern model architectures and techniques e.g., feature interaction modeling, advanced negative sampling and bias correction techniques, and efficient large-scale candidate retrieval
Preferred
Experience with modern recommender systems
Experience utilizing modern AI tooling to accelerate development efforts
A passion for online writing, publishing, or long-form content
Familiarity with Medium, as a reader, writer, or both!
Benefits
Working with a fully distributed team: We’re fully remote and have teammates across the U.S. & France.
Healthcare benefits covered at 100% for employees and 70% for dependents.
Generous parental leave policy.
Mental health support through Talkspace.
Financial wellness support through Northstar.
Stipends for co-working, professional development, wifi, and a one-time home office bonus.
Unlimited PTO and standard company holidays.
A discounted Medium membership!
Company
Medium
Medium is a social publishing network that connects ideas and perspectives on topics that matter.
51-200 employees
H1B Sponsorship
Medium has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2023 (2)
2022 (1)
2021 (7)
2020 (1)
Funding
Current Stage
Growth StageTotal Funding
$162.97MKey Investors
Spark CapitalAndreessen HorowitzGreylock
2021-11-18Series Unknown· $30.97M
2016-04-21Series C· $50M
2015-09-29Series B· $57M
Leadership Team
Scott Lamb
VP, Content
Recent News
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2025-12-05
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