<aside> ⬅️ Learn more about Dryft and our recent funding from General Catalyst, Neo and people like Jeff Wilke (former Amazon CEO) & Claire Hughes Johnson (former Stripe COO).

Dryft - We are hiring

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This role is in person in San Francisco with the option to work temporarily remote.

About you

As our founding Optimization & Machine Learning Engineer, you’ll be the driving force behind Dryft’s intelligent decision-making capabilities. Think of yourself as the strategist on a high-performance sports team, designing and optimizing the plays that win the game.

Your top priority is to design and implement cutting-edge optimization and machine learning models that power Dryft’s decision intelligence. You’ll craft and refine robust data pipelines, integrate models seamlessly into production systems, and collaborate closely with our CTO to push boundaries with efficient, high-impact code.

You are right for this role if you consider yourself a world-class:

• Comprehension wizard: You can distill highly complex, messy data & problems quickly and draw conclusions. You are also able to explain these easily to your team.
• Problem-solver: You are relentless in tackling challenges at the intersection of optimization, and machine learning even if it means finding creative, out-of-the-box solutions.
• System-thinker: You design scalable, robust systems that integrate seamlessly with existing infrastructure. You understand the big picture and ensure your solutions are built to last.

Responsibilities

• 🧠 Algorithm Design & Optimization: Develop and refine optimization models and machine learning algorithms to solve complex supply chain and inventory challenges. Leverage your expertise to design both deterministic and stochastic approaches for real-world impact.
• 📈 Model Development: Build, debug, and optimize machine learning prototypes using PyTorch. Transform prototypes into production-ready, scalable solutions.
• 📊 Data Mastery: Implement robust data pipelines to process large datasets efficiently. Ensure data readiness for high-impact modeling and decision-making processes.

Qualifications

• ML & Optimization Expertise:
  • 4+ years of experience in machine learning and optimization algorithm development
  • Proficient in implementing and fine-tuning deterministic algorithms and stochastic models.
  • Hands-on experience with PyTorch for machine learning development
• Data Pipeline Skills:
  • Strong ability to build and manage data pipelines for large-scale data processing.
  • Familiarity with SQL and NoSQL databases for efficient data handling.
  • Ability to come up with new ways of leveraging available data
• Production-Ready Development:
  • Proficiency in deploying ML models in production environments with a focus on scalability and reliability.
  • Solid grasp of microservices architecture and API development.
• Additional Skills:
  • Expertise in GenAI tools, such as vector databases and LLM chaining, is a bonus.
  • Ability to collaborate cross-functionally with engineers and product teams.