Note: The job is a remote job and is open to candidates in USA. SentiLink provides identity verification and risk solutions for institutions and individuals. The Applied Machine Learning Manager will lead a team of applied ML scientists while owning execution, developing fraud detection and identity models, partnering across the organization, and contributing hands-on to technical work and product strategy.
Responsibilities
- Directly manage a team of applied ML scientists, 4 today and growing to 6 by the end of 2026, and help set the engineering and modeling practices they work by
- Own execution for your area: priorities, delivery, and the results your team produces
- Coach and mentor team members through model development, experimentation, and technical decision making, and remain hands-on where it matters most, including code review and production systems
- Partner with senior leadership, Product, Engineering, and Risk to prioritize work and deliver impactful ML solutions
- Communicate progress, tradeoffs, and results clearly, and grow into representing your domain in product strategy discussions
- Develop and improve SentiLink's fraud detection and identity models across the full lifecycle: data acquisition, feature engineering, labeling strategy, model training, experimentation, production deployment, monitoring, and iteration
- Research emerging fraud patterns, build new ML capabilities for identity verification and financial risk, and design analyses that inform product and business decisions
- Use AI throughout your team's work, help push the boundary on what that unlocks, and contribute to our exploration of where AI belongs inside the products themselves
Skills
- 6+ years of industry experience applying machine learning or statistics to real-world problems, including 3+ years directly managing machine learning or data science teams
- Experience leading ML or data science teams in fraud, identity, fintech, banking, financial services, payments, or adjacent risk-focused domains, and interest in growing into ownership of product direction for that domain
- Bachelor's, Master's, or PhD in Computer Science, Statistics, Mathematics, Physics, or another quantitative discipline
- Demonstrated success developing and deploying production machine learning models, plus experience writing production-quality Python code and tests
- Strong practical ML and applied statistics knowledge: able to scope solutions quickly with standard tooling and go deep where it pays off
- Comfortable working end to end, with a track record of measurable business impact: planning, defining success criteria, getting buy-in, building the solution, and delivering it, whether in production, in a deck, or as strategy
- Comfortable with modern LLMs and AI-assisted development workflows and interested in pushing them further
- Sound judgment when working with sensitive data under real information security and data governance constraints
- Strong communicator who enjoys mentoring others while remaining technically hands-on
- Detail oriented and thoughtful, someone we can rely on to make high-stakes calls while thriving on varied, open-ended, high-impact problems
- Candidates must be legally authorized to work in the United States and must live in the United States
- Experience at high-growth startups preferred
Benefits
- Employer paid group health insurance for you and your dependents
- 401(k) plan with employer match (or equivalent for non US-based roles)
- Flexible paid time off
- Regular company-wide in-person events
- Home office stipend
Company Overview