Job Title: Senior Machine Learning Engineer (Ranking & Recommendations)
Location: Fully Remote (US only)
Compensation: $185,000 base + bonus
A high-growth technology company is using machine learning to transform decision-making in a legacy-heavy, data-dense industry. With executive sponsorship and PE backing, the team is re-architecting core operations around ML systems that drive real-time prioritization, routing, and intelligent matching across millions of data points.
This role offers end-to-end model ownership - from feature design to deployment - and the opportunity to build practical, production-grade models in a greenfield setting.
Why This Role Matters
The team processes hundreds of millions of records annually, but current systems only touch a small fraction. Your models will unlock significant scale, efficiency, and accuracy across the business.
This is a hands-on, high-impact role with real users, direct value creation, and room to grow into a technical leadership path.
What You’ll Do
- Build and deploy ranking, scoring, and recommendation models
- Develop ML pipelines from exploration through to production
- Optimize real-world operations through intelligent prioritization
- Partner with product and engineering to deliver ML systems that scale
- Contribute to experimentation and evaluation frameworks
Tech Stack
- Languages/Frameworks: Python, Scikit-Learn, PyTorch, TensorFlow, Hugging Face
- Infra: Spark, SQL, Airflow
- Deployment: AWS, Docker, CI/CD pipelines
Ideal Candidate
- Ample applied ML experience (or Master’s/PhD equivalent)
- Strong background in ranking, personalization, or recommendation systems
- Proven ability to ship and iterate on ML models in production
- Fluent in Python and comfortable across the full ML lifecycle
- Bonus: experience with LLMs, MLOps, or cloud infra
About Us
People In AI partners with high-growth AI and ML companies to bring clarity and precision to technical hiring. We help candidates engage with innovative teams in a transparent and streamlined process.
