Cedar is the AI-powered healthcare financial experience platform, built for the rising cost and complexity of healthcare payments. We help millions of people every year understand and resolve their medical bills with clarity and compassion, while helping healthcare organizations operate more efficiently. We’re combining AI, smart design, and empathy to fix one of healthcare’s most urgent crises.
Tech Lead Manager (Machine Learning) |M1|
Location
United States
Posted
21 days ago
Salary
$195.5K - $247K / year
Seniority
Senior
Job Description
Tech Lead Manager (Machine Learning) |M1|
Cedar
Our healthcare system is the leading cause of personal bankruptcy in the U.S. Every year, over 50 million Americans suffer adverse financial consequences as a result of seeking care, from lower credit scores to garnished wages. The challenge is only getting worse, as high deductible health plans are the fastest growing plan design in the U.S. Cedar’s mission is to leverage data science, smart product design and personalization to make healthcare more affordable and accessible. Today, healthcare providers still engage with its consumers in a “one-size-fits-all” approach; and Cedar is excited to leverage consumer best practices to deliver a superior experience. The Role We are in search of a Tech Lead Manager to lead development of the machine learning systems that underlie our foundational Personalization Engine within Cedar Pay. This role requires deep expertise in machine learning engineering (from ML modeling to MLOps) and a desire to drive impact through a combination of hands-on technical contributions and people management. Your work will serve as the "decisioning brain" for a vast array of product features that are developed by multiple Cedar squads. Your models will navigate thousands of unique patient variables, economic situations, healthcare-specific intricacies, and behavioral patterns, to ensure every patient journey is optimized for both financial resolution and a positive healthcare financial experience. The robust system that you build and scale will be the intelligent core that powers personalized experiences within Cedar Pay. Key responsibilities - ML System Ownership: Serve as key DRI (Directly Responsible Individual) for the ML System that powers the Personalization Engine. You will own the machine learning lifecycle end-to-end, ensuring system reliability, platform scalability, and model effectiveness, in partnership with the engineers on the team. - Full-Stack ML Execution: Lead and execute engineering work ranging from high-performance MLOps (feature stores, pipelines for model deployment, inference, and monitoring) to sophisticated ML modeling (can include training ensemble models, reinforcement learning, multi-armed bandits, or more), while employing guardrails for compliance and fairness. You will lead by example by making hands-on contributions, and also by guiding and empowering the two ML engineers on your team. - Technical Leadership and People Management: Act as a force-multiplier for the Personalization Foundations squad. You will conduct rigorous code and design reviews, elevating the bar across the team, contributing to a culture that is committed to technical excellence and product impact. You will serve as direct manager for the machine learning engineers on the squad, mentoring and coaching them to support their professional growth. - Balancing Rigor with a Bias for Action: With a deep understanding of software engineering principles, you build robust, production-grade systems that can handle the scale of millions of healthcare transactions, while also enabling the ability to rapidly operationalize, iterate on, and improve ML models and approaches as we collect data and generate new insights. You understand that the first approach is never perfect, and that learning is a continuous process; you focus on building for the validated present rather than over-engineering for an unproven future. - Feedback Loop Optimization: Using your combined skillset in data engineering and ML model design, you will improve and expand upon the feedback loop that captures patient reactions to real-time decisions, ensuring that our models learn autonomously and adapt to changing economic and healthcare landscapes. - Cross-Functional Leadership: Partner with Product and Design to translate ambiguous patient journey touchpoints into concrete ML problems. You will help to define the "surface area" of where and how machine learning can provide the most leverage within the Cedar Pay ecosystem. Required Skills and Experience - Track record of building production ML systems: You have 6+ years of professional experience in machine learning engineering, where you have designed, built, and deployed effective ML-powered personalization systems or recommendation engines at scale for consumer-facing products (e.g., fintech, e-commerce, social media, etc.) - Strong programming skillset: You bring technical excellence as you contribute hands-on across the full ML lifecycle—building data pipelines for feature engineering, training the core models, and enhancing the MLOps infrastructure required to serve and monitor these insights at scale. Expertise in both Python and SQL is highly preferred. - Leadership: You have 1+ years of experience managing ML engineers and scientists, and you have led a team to execute on a technical roadmap, from ideation to production. Although we prefer candidates who have previous management experience, candidates with experience in an IC Tech Lead ML role where they had informal or dotted-line management responsibilities will still be considered (and for these candidates, we can craft a tailored growth plan into a formal management role at Cedar). - Collaboration: You have experience collaborating closely with product leaders and software engineers, understanding that ML systems don’t work in isolation but only in the context of a larger software product. - ROI-driven mindset: You go beyond training models or engineering systems—you have an inclination to dive into the data to understand the "why." You can articulate how to formulate a business problem as a supervised, unsupervised, or reinforcement learning task. You possess the judgment to determine when the incremental benefits of a model justify the cost of building and operating it. You are comfortable championing simpler, non-ML solutions when they offer a higher return on investment for the business. - Machine learning for a mission: The idea of applying your technical skillset to improve the healthcare financial experience is something that excites and inspires you. Nice-to-have, but not required: - Experience with agentic personalization: You have built and integrated effective Generative AI features into a personalization system, or you have designed tools, components and modules that help enable the development of safe, high-performance GenAI features. - Leading the build of software products, beyond the AI/ML components: If your tech leadership skillset crosses over from machine learning engineering to product engineering, you will thrive as a leader in this cross-functional team. Compensation Range and Benefits: - Salary Range*: $195,500 - 247,000 - This role is equity eligible - This role offers a competitive benefits and wellness package *Subject to location, experience, and education #LI-Remote #LI-JJ2 What do we offer to the ideal candidate? - A chance to improve the U.S. healthcare system at a high-growth company! Our leading healthcare financial platform is scaling rapidly, helping millions of patients per year - Unless stated otherwise, most roles have flexibility to work from home or in the office, depending on what works best for you - For exempt employees: Unlimited PTO for vacation, sick and mental health days–we encourage everyone to take at least 20 days of vacation per year to ensure dedicated time to spend with loved ones, explore, rest and recharge - 16 weeks paid parental leave with health benefits for all parents, plus flexible re-entry schedules for returning to work - Diversity initiatives that encourage Cedarians to bring their whole selves to work, including three employee resource groups: be@cedar (for BIPOC-identifying Cedarians and their allies), Pridecones (for LGBTQIA+ Cedarians and their allies) and Cedar Women+ (for female-identifying Cedarians) - Competitive pay, equity (for qualifying roles), and health benefits, including fertility & adoption assistance, that start on the first of the month following your start date (or on your start date if your start date coincides with the first of the month) - Cedar matches 100% of your 401(k) contributions, up to 3% of your annual compensation - Access to hands-on mentorship, employee and management coaching, and a team discretionary budget for learning and development resources to help you grow both professionally and personally About us Cedar was co-founded by Florian Otto and Arel Lidow in 2016 after a negative medical billing experience inspired them to help improve our healthcare system. With a commitment to solving billing and patient experience issues, Cedar has become a leading healthcare technology company fueled by remarkable growth. "Over the past several years, we've raised more than $350 million in funding & have the active support of Thrive and Andreessen Horowitz (a16z). As of November 2024, Cedar is engaging with 26 million patients annually and is on target to process $3.5 billion in patient payments annually. Cedar partners with more than 55 leading healthcare providers and payers including Highmark Inc., Allegheny Health Network, Novant Health, Allina Health and Providence.
Benefits
- 401(K), 401(K) matching, Commuter benefits, Company equity, Company-sponsored outings, Customized development tracks, Dental insurance, Disability insurance, Documented equal pay policy, Volunteer in local community, Family medical leave, Flexible Spending Account (FSA), Flexible work schedule, Free daily meals, Generous parental leave, Company-sponsored happy hours, Health insurance, Job training & conferences, Open door policy, Life insurance, Mentorship program, Open office floor plan, Paid holidays, Paid industry certifications, Pair programming, Paid sick days, Pet friendly, Pet insurance, Promote from within, Lunch and learns, Remote work program, Free snacks and drinks, Team based strategic planning, OKR operational model, Mandated unconscious bias training, Unlimited vacation policy, Vision insurance, Wellness programs, Mental health benefits, Diversity employee resource groups, Hiring practices that promote diversity, Fertility benefits, Employee resource groups, Employee-led culture committees, Hybrid work model, In-person all-hands meetings, Employee awards, Meditation space, Mother's room, Personal development training, Company-wide vacation
Related Guides
Related Job Pages
More Machine Learning Engineer Jobs
• Own the model lifecycle: requirements, experimentation, model development, evaluation, and model cards, partnering with ML engineers on deployment and production infrastructure • Translate business problems into well-framed ML solutions: defining what to model, what success looks like, and where ML adds value vs. simpler approaches • Design and maintain feature engineering pipelines for model development • Drive experiment design and statistical rigor: ensuring models are evaluated with sound methodology before and after launch • Monitor model quality in production, tracking performance over time, detecting data drift, and determining when to retrain • Cultivate a culture of learning and collaboration within and across partner teams • Perform design and code reviews to raise the technical excellence bar • Hire, mentor, and coach data scientists
• Lead the technical strategy and architecture for our company’s ads identity modeling solutions and other related ads measurement models • Design and train advanced ML models while ensuring accuracy, scalability, and compliance with privacy requirements, managing trade-offs between complexity, latency, and prediction quality • Oversee end-to-end ML workflows—from data ingestion and feature engineering to model training, evaluation, and deployment—optimizing for performance and cost • Partner with cross-functional teams (e.g., product management, data science, platform engineering, privacy, legal) to define the roadmap and set long-term goals • Establish engineering best practices, code quality standards, and data governance guidelines to ensure maintainability and trustworthiness of the identity graph • Mentor and coach junior engineers, fostering a culture of innovation, technical excellence, and knowledge sharing across the organization.
• Lead the end-to-end design, implementation, and maintenance of a highly available, low-latency GPU-based model serving system for search, ranking, and LLMs supporting Millions of QPS. • Design and develop ML and Generative AI systems in cloud-based production environments on Kubernetes at scale. • Rapidly develop prototypes and develop a high-performance feature hydration and processing system as a part of the inference stack - including routing, caching, and batching. • Lead a unified GPU model export framework to support converting trained models into optimized GPU inference models. • Strong understanding of real-time ML observability to track feature/model performance. • Experience working with LLM serving online at scale. • Built an E2E inference performance benchmarking framework • Deep Understanding of multi-cluster compute environment and network topology that is specific to ML inference use cases.
At Bose Corporation, we believe sound is the most powerful force on earth — and for over 60 years, we have been a company built on innovation, excellence, and independence. Privately owned, fiercely customer-focused, and driven by our values, we continue to lead industries and transform lives through sound. Today, Bose Corporation is entering an exciting new era. Across multiple global Business Units and Global Functions, we are shaping the future of audio technology, automotive, luxury, and premium experiences. We invite you to join us in this transformation. Job DescriptionTimeframe: June 1 – August 21, 2026 THE ROLE The goal of the Audio Machine Learning Research team is to develop novel AI-powered audio processing algorithms. The twist is that our algorithms must run in real-time, on physical devices, for applications such as voice pickup, hearing augmentation and ones we haven't even thought of yet. As part of the team, you will work with experts in machine learning (ML), digital signal processing (DSP), software engineering and psychoacoustics to prototype and implement new algorithms. Bose has a strong history of combining creative thinking with cutting-edge technology in the audio domain. We are looking for candidates passionate about machine learning and audio to help us shape the next chapter in the future of Bose! Responsibilities: - Most of your time will be devoted to prototyping, implementing and evaluating ML algorithms, curating and developing internal resources, and presenting your findings. - You will integrate your novel solutions into existing systems and platforms to showcase new (proof of concept) solutions. - You will be able to contribute to projects, which will be shipped to Bose customers, apply for patents, and/or submit papers to top-tier AI and signal processing conferences (e.g., NeurIPS, ICASSP, Interpeech, etc.). Education: - Pursuing or recently finished a graduate-level degree in ML, Computer Science, Music Technology or a related field. Skills: - Practical knowledge of Applied audio ML (TensorFlow/PyTorch, TFLite/ONNX is a plus) and Audio DSP (Python, Matlab and/or C/C++). - Hands-on experience in at least one of the following research topics: Audio source separation, Speech enhancement, Microphone array signal processing, Tiny ML, Generative audio modelling - Familiarity with methods for spatial sound synthesis and/or room acoustics simulation/analysis is a plus. - Strong communication skills. You will be presenting your work to a large interdisciplinary community. At Bose, you're inspired to be and do your best and are rewarded for your unique talents! Our compensation is thoughtfully tailored to your skills, experience, education, and location, and goes beyond base salary. The hiring range for this position in the primary work location of Framingham, Massachusetts is: $40.00-$51.25 per hour.The hiring range for other Bose work locations may vary. In addition to competitive base pay we offer rewards including bonus programs, comprehensive health and welfare benefits, a 401(k) plan, plus exclusive perks designed to support your wellbeing, and a generous employee discount where you can immerse yourself in our products and experiences. We are a proudly independent company—driven by purpose, guided by our values, and united by a belief in the power of sound. As the world leader in audio experiences, we’re creating what’s next—pushing boundaries and delivering transformative sound experiences for people everywhere. Join us and make your next career move a mic-drop. Let’s Make Waves. Bose is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, genetic information, national origin, age, disability, veteran status, or any other legally protected characteristics. The EEOC’s “Know Your Rights: Workplace discrimination is illegal” Poster is available here: https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf. Bose is committed to providing reasonable accommodations to individuals with disabilities. If you require reasonable accommodation in completing this application, interviewing, completing any pre-employment testing, or otherwise participating in the employee selection process, please direct your inquiries to applicant_disability_accommodationrequest@bose.com. Please include "Application Accommodation Request" in the subject of the email. Our goal is to create an atmosphere where every candidate feels supported and empowered in the interviewing process. Diversity and inclusion are integral to our success, and we believe that providing reasonable accommodation is not only a legal obligation but also a fundamental aspect of our commitment to being an employer of choice. We recognize that individuals may have different needs and requirements based on their abilities, and we provide reasonable accommodations to ensure ideal conditions are met during the application process.



