Associate Machine Learning Engineer
- Design, build, and deploy machine learning models and algorithms into production environments.
- Develop scalable data pipelines using Python and Spark to process large and complex datasets.
- Collaborate with software engineers to integrate ML solutions into distributed systems.
- Improve and maintain real-time and batch inference systems with a focus on reliability and performance.
- Design clean, interpretable experiments and evaluate results using sound statistical methods.
- Analyze ambiguous data sources, navigate irregularities, and link datasets to generate meaningful insights.
- Write high-quality, maintainable code following software engineering best practices.
- Own the lifecycle of projects, including scoping, estimation, risk management, documentation, and monitoring.
- Communicate findings and recommendations clearly to technical and cross-functional partners.
- Contribute to team growth by sharing knowledge, modeling strong collaboration behaviors, and participating in hiring processes.
- Bachelor's degree in Computer Science, Engineering or related field, or equivalent work experience.
- 1–3 years of experience (including internships or academic research) building and deploying machine learning models in areas such as computer vision, traditional ML, or agent-based systems.
- Strong proficiency in Python for data processing and advanced analytics, with experience in frameworks such as PyTorch, TensorFlow, or OpenCV.
- Familiarity with agentic or autonomous system design patterns (e.g., tool-use agents, multi-step reasoning pipelines, reinforcement learning).
- Experience with SQL and working with large-scale datasets.
- Experience implementing statistical and mathematical modeling techniques (e.g., linear regression, tree-based models).
- Understanding of experiment design, A/B testing, and statistical significance.
- Experience building or contributing to production-grade algorithms and systems.
- Solid software engineering fundamentals, including version control, testing, and documentation.
- Curiosity, strong problem-solving skills, and the ability to independently learn new tools and techniques.
- Ability to prioritize the right tools for the business problem and manage competing timelines.
- Clear written and verbal communication skills, with the ability to tailor messaging to different audiences.
- 4-day work week, with Fridays off
- Hybrid work environment: 3 days in the office and 1 day remote each week
- Competitive salary (we leverage market data)
- Many ThredUp employees also have the opportunity to own shares of ThredUp stock and are eligible for discretionary restricted stock unit awards
- Employee stock purchase plan
- Flexible PTO (take the time you need) + 13 company holidays
- Paid Sabbatical after 3 years of full time employment
- Generous paid parental leave for new mothers and fathers
- Medical, dental, vision, 401k, life and disability insurance offered
- We live by our Core Values of Transparency, SpeakingUP, Thinking Big, Infinite Learning, Influencing Outcomes & Seeking the Truth
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