Applied ML Engineer

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 ownership, curiosity, and a bias toward action

Bonus Qualifications

• Experience with online learning, reinforcement learning, or efficient ML architectures
• Experience training or fine-tuning models using human feedback, reward signals, or other adaptive learning techniques