Company
Technology
AppliedMLEngineer
Neural analysis suggests this role is
optimal for Senior candidates.
“Applied ML Engineer. Skills: Applied ML, Customer engagement, ML solutions. Identify opportunities. Build solutions”
Industry & Context.
Consequential problems
What They're Looking For.
Must Have
4+ years of experience in machine learning, 2+ years customer-facing technical role, Software engineering skills, Familiarity with ML frameworks, Solid understanding of data modeling
Nice to Have
Experience with online learning, Experience with reinforcement learning, Experience with efficient ML architectures, Experience training models using human feedback, Experience fine-tuning models using human feedback, Experience training models using reward signals, Experience fine-tuning models using reward signals, Experience training models using adaptive learning techniques, Experience fine-tuning models using adaptive learning techniques
What You'll Do.
Identify opportunities
Implement ML solutions
Partner from discovery through deployment
How You'll Work.
Team & Collaboration
Strategic customers; Senior stakeholders
Communication Scope
Technical presentations; Business impact
Full Job Description
THE ROLE We're looking for an Applied ML Engineer who thrives at the intersection of applied research and building real-world products, and who's equally comfortable sitting across from a customer as they are in the codebase. You'll work directly with strategic customers tackling some of their most consequential problems — figuring out where our platform falls short, and building the ML solutions that close the gap. Then you'll do it again for the next customer with an entirely different domain, data landscape, and set of constraints. The problems you solve in the field become the product. RESPONSIBILITIES - Find and Unlock Alpha: Go deep on customer problems and data workflows to identify the highest-leverage opportunities others miss — then build the solutions that capture them. - Ship What's Missing: When the product doesn't cover it, you do. Identify gaps through hands-on customer engagement and implement production-grade ML solutions that fill them. - Drive Adaptable Data Strategy: Lead the design and implementation of efficient, adaptive ML systems across real production environments and varied customer tech stacks. - Own the Outcome: You're not handing off a deck — you're a strategic and technical partner from discovery through deployment, accountable for results. - Raise the Bar: Develop compelling demos, deliver technical presentations to senior stakeholders, and set the standard for what great looks like across our customer base. QUALIFICATIONS - 4+ years of experience in machine learning, applied research, or systems-level engineering for AI; 2+ years in a customer-facing technical role - Strong software engineering skills and familiarity with ML frameworks (e.g., PyTorch, JAX, TensorFlow) - Solid understanding of data modeling for training and how curation decisions shape model performance - Excellent communication skills and the ability to translate complex technical work into business impact across varied stakeholder environments - A mindset of ownersh
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