Experimentation and Optimization: You will help parallelize and distribute work amongst different experiment tracks, optimize model performance via hyperparameter tuning, model ensembling, or advanced training strategies, and design and conduct systematic experiments to validate hypotheses and model improvements.
Research and Development: Your responsibilities will include conducting literature reviews on state-of-the-art methods in medical imaging, designing and prototyping novel machine learning models, implementing model architecture and training strategies in code, and generating ideas and exploring methods for improvements to existing models or tasks.
Analysis and Validation: You will perform statistical analysis to assess model robustness and reproducibility, and compare proposed methods against baselines and benchmarks from existing literature.
Interdisciplinary Collaboration: You will collaborate with domain experts to define problem statements and interpret model outputs, ensuring our AI solutions are both technically sound and clinically impactful.

5+ years of hands-on experience in machine learning, including model design, training, and evaluation.
Extensive experience applying machine learning to real-world computer vision or NLP problems, including developing, deploying, and optimizing models.
Proficiency with deep learning frameworks such as PyTorch or TensorFlow and comfort writing clean, modular experimentation code.
Practical experience running experiments, tuning models, and comparing approaches via systematic validation.
Excellent grasp of modern ML concepts: regularization, loss functions, optimization strategies, generalization, overfitting, etc.
Basic data analysis skills using tools like Polars or Pandas for efficient data manipulation and exploratory data analysis.
An understanding of statistical testing and experimental design to assess performance, robustness, and reproducibility.
Curiosity about new techniques — you enjoy staying current with ML literature and applying ideas in production-minded ways.
Strong analytical skills with the ability to deconstruct complex problems into their core components and fundamental characteristics.
Capability to prioritize tasks strategically, develop clear work breakdown structures, and manage competing demands in a fast-paced environment.
A track record of generating novel ideas, exploring them rigorously, and translating them into working systems.
Experience building ML pipelines (training, evaluation, deployment) in production, especially in cloud environments like AWS.

Real Impact: You’ll work on meaningful products that make a measurable difference
from healthcare and commerce to sustainability and next-gen tech.
Remote-First, Office Friendly: Work from wherever you’re most productive
whether that’s your home, a co-working space, or one of our offices. We’re a remote-first company, but if you’re near an office, you’re welcome to drop in, collaborate in person, or work onsite regularly. We prioritize async collaboration, respect your time zone, and focus on outcomes over hours.
An Outstanding Team: Talented, kind, and hard-working people who care deeply about their craft
and about each other. No egos. No politics. Just professionals doing their best work.
Growth: You’ll be supported in growing your craft, exploring new paths, and stepping into greater responsibility
at your own pace A Culture of Excellence: We care deeply about doing the right thing
for our clients, our team, and ourselves. No burnout. No crunch. Just high-quality work, delivered sustainably.
Variety & Stability: We’re profitable, independent, and over a decade strong. Yet every project brings a fresh challenge. You’ll never be bored here.

Senior Machine Learning Engineer

Key skills