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What we want to accomplish and why we need you Suki is a leading technology company that provides AI voice solutions for healthcare. Its mission is to reimagine the healthcare technology stack, making it invisible and assistive to lift the administrative burden from clinicians. Its flagship product is Suki Assistant, an AI assistant that uses generative AI to automatically create clinical documentation by ambiently listening to patient-clinician conversations. Suki helps clinicians complete notes 72% faster on average, assists with other tasks including coding and answering questions, and generates incremental revenue for organizations, delivering a 9X ROI in year 1. Suki also offers its proprietary AI and speech platform, Suki Platform, to partners who want to create best-in-class ambient and voice experiences for their solutions. Clinicians that use Suki already spend over 70% less time on administrative tasks, and we’re striving to do even better. Come and join us! We are a user-driven company and are committed to making sure every pixel of our product is in service of the doctors. We’re a team of technologists, clinicians, and industry experts working together to push the limits on technology used in medicine. We’re confident enough to move fast and talented enough not to break things. What will you do everyday? The Machine Learning team forms the core of Suki's product, driving innovation and predictive excellence. You'll leverage your NLP expertise to enhance our computational infrastructure and improve our technical approaches and algorithms. Working directly on the platform powering our domain services, you'll collaborate with cross-functional teams to address NLP challenges and scale our platform for thousands of doctors. You'll manage and curate large datasets, ensuring data quality and relevance for training and evaluation. You'll monitor and analyze system performance metrics, identifying areas for optimization and implementing necessary improvements. By staying updated on NLP and Generative AI advancements, you'll incorporate innovations to maintain our competitive edge, reducing doctors’ administrative burdens and significantly impacting their daily lives. Ok, you're sold, but what are we looking for in the perfect candidate? Expertise: You know how to train models. You understand which models work best, and use LLMs only when necessary. You watch out for recall, accuracy, and precision. In other words, you’ve done this before. Action oriented: You love to build. You like to ship fast, quickly iterate, and see amazement in users’ eyes. Creativity: You enjoy listening to user feedback and then building products in novel ways. You’re resourceful and enjoy finding alternate paths to success. Problem solving: you use data to help point you in the correct direction. You optimize relentlessly, and understand the impact you’re making on the business. Humility: You’re humble and love working in a team without ego to deliver products Adaptability: You thrive in a fast-moving organization that uses light-weight processes and cutting-edge technology to have a huge impact. Confidence: You trust your abilities and you’re ready to push yourself to the next level. Communication: You are a clear communicator and demonstrated consensus-builder. Requirements 5+ years in overall Machine Learning experience, with at least 3 years focused on NLP and Contextual Embeddings. Proven record of an end to end workflow and with moving at least one NLP model to an enterprise production system. Expert in the understanding, practice, and deployment of state-of-the-art deep neural network models. Experience in building and maintaining distributed backend services for ML/AI Applications Strong grasp of CS fundamentals including abstractions, algorithms, probability, data structures and system design is preferred Strong working knowledge of LLMs, including prompting, orchestration, RAG, context and cost management Hands-on experience designing and implementing evaluation frameworks for LLM-based systems, including automated evals, human feedback loops, regression testing, and benchmark design *We don’t necessarily expect to find a candidate that has done everything listed, but you should be able to make a credible case that you’ve done most of it and are ready for the challenge of adding new skills to your resume. Tell me more about Suki On a roll: Named by Fast Company as one of the most innovative companies, named Google’s Partner of the Year for AI/ML, named by Forbes as one of the top 50 companies in AI . Great team: Founded, managed, and backed by successful tech veterans from Google and Apple and medical leaders from UCSF and Stanford. We have technologists and doctors working side-by-side to solve complex problems. Great investors: We’re backed by Venrock, First Round Capital, Flare Capital, March Capital, Hedosophia and others. With our $165M raised so far, we have the resources to scale. Huge market: Disrupting a massive, growing $30+ billion market for transcription, dictation, and order-entry solutions. Our vision is to become the voice user interface for healthcare, relieving the administrative burden on doctors instead of adding to it. Great customers: Our solutions are used in health systems and clinics across the country, supporting clinicians across dozens of specialties. Check out what one of our users says about how Suki has helped his practice. Impact: You’ll make an impact from day one. You’ll join a team working towards a shared purpose with a culture built upon deep empathy for doctors and passion for making their lives better. Suki is an Equal Opportunity Employer. We are dedicated to building a company that fosters inclusion and belonging and reflects the diverse communities we serve across the country. We know we are stronger this way, and we look forward to growing our team with these shared values.
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.
