Senior Machine Learning Engineer (R&D)

About the Role:

We are seeking a self-starting Full Stack ML Engineer to join our venture studio engineering team. In this role you will rapidly prototype and develop tools visualizations and products that empower researchers and entrepreneurs to build AI-driven startups. This position requires deep expertise in machine learning proficiency across the full stack and the ability to work independently in a fast-paced innovative environment.

This is a remote role with travel expectations to attend our bi-annual All Hands and other travel as needed (~10% or less).

Responsibilities:

• Rapidly prototype and build full-stack tools and visualizations to support researchers and entrepreneurs.

• Design implement test and debug code across front-end back-end and data pipelines.

• Collaborate with research teams to translate cutting-edge ML techniques into production-ready solutions.

• Work with entrepreneurs and users to gather requirements incorporate feedback and iterate on product development.

• Develop and optimize robust pipelines for model fine-tuning evaluation and deployment.

• Establish best practices for reliable and reproducible ML model development.

• Contribute to the creation of scalable high-performance infrastructure for AI-driven products.

Minimum Qualifications:

• Bachelor’s degree in Computer Science or equivalent practical experience.

• 5 years of experience in software development (e.g. C++ Python Rust) with a focus on data structures and algorithms

• 3 years of experience building production-quality machine learning systems and infrastructure with deep expertise on data engineering (SQL/Spark)

• Proficiency in JavaScript React and other web technologies for front-end development.

• Experience with backend languages (preferably Python or Rust) and system design.

• 2 years of experience with ML frameworks (e.g. PyTorch TensorFlow JAX Ray MLFlow) and AI accelerators (e.g. GPUs TPUs).

Preferred Qualifications:

• Master’s degree or PhD in Computer Science or a related technical field.

• Hands-on experience with large language models (LLMs) generative AI or natural language processing.

• Familiarity with model architectures (e.g. transformers encoders decoders) and post-training techniques.

• Experience launching AI-driven products or working with technical customers

• Proficiency in distributed computing containerizing ML workloads and debugging complex ML pipelines.

• Familiarity with SEO principles and web accessibility standards.

• Strong interest in AI safety and responsible deployment

• 2+ years of experience working in an early stage (Seed / Series A) startup

You Might Thrive in This Role If You:

• Are a versatile team player comfortable with ambiguity and rapid iteration.

• Excel at building maintainable backend infrastructure and user-facing products.

• Can balance research exploration with engineering rigor and operational reliability.

• Have a track record of shipping high-quality software under tight deadlines

• Enjoy collaborating across research engineering and entrepreneurial teams to drive innovation.

Representative Projects:

• Optimizing inference request routing to maximize compute efficiency

• Scoping an AI Agent Architecture to automate a business need or be a part of a new feature for a new incubation we are working on.

• Contributing to new inference features (e.g. structured sampling fine tuning)

• Supporting inference for new model architectures

• Building a custom BERT model for bespoke classification needs

• Ensuring smooth and regular deployment of inference services

• Analyzing observability data to tune performance based on production workloads

Benefits:

• Career track opportunity with potential for rapid advancement with strong performance as the firm grows.

• 100% employer paid comprehensive health care including medical dental and vision for you and your family.

• Paid maternity and paternity for 14 weeks at employees' normal pay.

• Unlimited PTO with management approval.

Salary Range: $200000-250000. This represents the typical salary range for this position based on experience skills and other factors.

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