Beacon Biosignals - Manager, Algorithms and Machine Learning

• Experience managing a mid-sized ML or algorithm engineering team, with a track record of coaching, hiring, and growing individuals across levels while maintaining strong team health and accountability. • Proven ability to lead teams through technically complex, ambiguous work with cross-functional dependencies, balancing short-term delivery with longer-term capability building. • A strong depth of knowledge in algorithm/ML-model development, deploying production-ready ML systems, and model-maintenance to assess approaches, guide tradeoffs, and make sound decisions. • Experience operating within established frameworks and improving team-level ways of working, including prioritization, planning, and execution, while pragmatically addressing delivery friction and scaling challenges. • Strong communication and stakeholder management skills, with the ability to align partners around decisions, tradeoffs, and evolving plans, including in regulated or quality-sensitive environments. • A bias toward simplicity, with the ability to introduce the right level of process, avoid unnecessary complexity, and continuously improve how the team works. • Experience developing ML or algorithmic systems in regulated domains, with familiarity in regulatory submissions, including validation, reproducibility, documentation, and model governance requirements. • The salary range for this role is $180,000- $200,000. Salary ranges are determined using current market compensation data for this role and adjusted based on experience, skills, and location.The base salary is one component of the total compensation package, which includes equity, PTO and other benefits. • At Beacon, we've found that cultural and scientific impact is driven most by those that lead by example. As such, we're always seeking new contributors whose work demonstrates an avid curiosity, a bias towards simplicity, an eye for composability, a self-service mindset, and - most of all - a deep empathy towards colleagues, stakeholders, users, and patients. We believe a diverse team builds more robust systems and achieves higher impact.