• Provide expert-level advice and mentorship on the architecture, training, and production of text-to-speech (TTS) models • Guide the implementation of robust testing methodologies for TTS models using industry standards like MOS testing • Share expertise in distributed training, monitoring, and deployment of large-scale ML models on cloud platforms • Lead latency optimization initiatives in real-time systems for high-quality speech-to-speech conversion • Provide guidance on tuning TTS models for precise control over speech characteristics • Share in-depth knowledge of various TTS model architectures and waveform generation methods • Mentor the team on implementing advanced deep learning models for audio processing • Guide the development of transformer architectures for complex TTS model development

• Define and execute a translational ML strategy spanning omics, imaging, and other biomedical data modalities, in close partnership with translational biology, clinical, and ML leadership • Directly contribute to technical work: experimental design, model development, analysis, and interpretation of translational ML outputs in support of active drug programs • Manage a team (initially 2–3 ML scientists) working on imaging and omics applications; hire for emerging needs as the function scales • Translate clinical and translational biology questions into well-posed ML problems, and translate ML results back into actionable recommendations for drug discovery teams • Serve as a strategic voice into the Enchant development roadmap, ensuring that translational use cases, data requirements, and evaluation criteria inform model priorities • Co-design experiments and data collection strategies with translational biology colleagues to maximize the utility of biomedical data for ML modeling • Establish evaluation frameworks that connect ML model performance to clinically meaningful endpoints and decision criteria • Communicate translational ML results and strategy to internal stakeholders, partners, and at scientific conferences

About Upstart At Upstart, we’re united by a mission that matters: to radically reduce the cost and complexity of borrowing for all Americans. Every day, we bring creativity, experimentation, and advanced AI to reshape access to credit, helping millions move forward financially with clarity and confidence. As the leading AI lending marketplace, we partner with banks and credit unions to expand access to affordable credit through technology that’s both radically intelligent and deeply human. Our platform runs over one million predictions per borrower using more than 1,800 signals, powering smarter, fairer decisions for millions of customers. But the numbers only hint at the impact. Every idea, every voice, and every contribution moves us closer to a world where credit never stands between people and their financial progress. We’re proudly digital-first, giving most Upstarters the flexibility to do their best work from wherever they thrive, alongside teammates across 80+ cities in the US and Canada. Digital-first doesn’t mean distant. We’re intentional about in-person connection through team onsites, planning sessions, and moments that spark creativity and trust. And whether you choose to work primarily from home or collaborate in-person from one of our offices in Columbus, Austin, the Bay Area, or New York City (opening Summer 2026), you’ll have the support to work in the way that works best for you. If you’re energized by tackling meaningful problems, excited to innovate with purpose, and motivated by work that truly matters, we’d love to hear from you. The Team: The Machine Learning & Simulations Platform (MLSP) team builds and operates the core infrastructure that powers ML model training, inference, and marketplace simulation at Upstart. Our platform is foundational to the company’s success—every underwriting, fraud, conversion, and verification model runs here. We also provide the simulation capabilities that help teams experiment safely and assess business impact without requiring costly live experimentation. We are on a mission to reimagine our infrastructure to support the growing complexity of our ML models, the demand for low-latency inference, and the accuracy needed to simulate the dynamics of our borrower-lender marketplace at scale. The team partners closely with Engineering, ML, Product, and Finance to accelerate innovation while safeguarding performance and integrity. As a Principal Software Engineer focused on Machine Learning Simulations at Upstart, you will be responsible for building an MLOps platform to support machine learning model inference, process automation, model deployment, and observability. Machine Learning is critical to Upstart’s core business, and our greatest competitive advantage lies in the fact that we’re able to innovate on our AI engine quickly. You will also help build a marketplace simulation platform to support rapid innovation across ML and Finance teams. How you’ll make an impact - Build, maintain, and optimize Upstart’s next-generation machine learning and simulation platform, enabling increased scale, performance, and confidence in decisioning - Develop high-quality software applications that enable machine learning models to be applied to the ever-evolving needs of the business - Enable the modernization of our serving infrastructure, reducing inference latency to just a few seconds for our most complex models - Design and contribute to our simulation systems to more accurately reflect production environments, reducing simulation cost and enabling broader usage across teams - Communicate closely with cross-functional partners from ML, Engineering, Product, and Data Engineering teams, keeping all stakeholders informed - Mentor engineers across the team, sharing expertise on distributed systems, MLOps, and scalable architecture Minimum Qualifications - Bachelor’s degree in Computer Science, Engineering, or Mathematics, or a related field (or its equivalent) + 8 years of experience - Experience building or contributing to platforms or systems that support machine learning model simulation - Experience building self-serve or configuration-driven tooling for internal stakeholders - Experience building and maintaining backend software services and APIs - Proficiency with some or more of the following: Python, Kotlin, Databricks, and AWS - Exhibits a growth mindset - you’re not afraid to pick up new technologies that are best for the task, and learn from others. - Ability to quickly comprehend and reiterate complex requirements from product or engineering leadership and translate those to both technical and non-technical stakeholders - Track record of successfully mentoring and developing other engineers around you while seeking out and appreciating constructive feedback Preferred Qualifications - Familiarity with model serving technologies like Ray, and experimentation frameworks - Proficiency with Flask, FastAPI, Metaflow, MLflow, gRPC, Kafka, Spark/PySpark, ETL/ELT, Redshift (or similar) - Excellent quantitative reasoning skills with interest in working at the intersection of engineering and machine learning - Strong sense of ownership and accountability for the quality and timely delivery of work - Proven ability to effectively analyze and solve complex problems - Excellent written and verbal communication skills with stakeholders, peers and product owners - Ability to thrive both in self-directed work environments and in collaborative settings, contributing positively to team dynamic Position location This role is available in the following locations: Remote-US Time zone requirements The team operates on the East/West coast time zones. Travel requirements As a digital first company, the majority of your work can be accomplished remotely. The majority of our employees can live and work anywhere in the U.S but are encouraged to to still spend high quality time in-person collaborating via regular onsites. The in-person sessions’ cadence varies depending on the team and role; most teams meet once or twice per quarter for 2-4 consecutive days at a time. #LI-REMOTE #LI-MidSenior At Upstart, your base pay is one part of your total compensation package. The anticipated base salary for this position is expected to be within the below range. Your actual base pay will depend on your geographic location–with our “digital first” philosophy, Upstart uses compensation regions that vary depending on location. Individual pay is also determined by job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. In addition, Upstart provides employees with target bonuses, equity compensation, and generous benefits packages (including medical, dental, vision, and 401k). United States | Remote - Anticipated Base Salary Range $195,300—$270,400 USD What you'll love At Upstart, our benefits are designed to support your health, financial well-being, family, and personal growth. Here’s what you can expect: - Competitive compensation, including base pay, bonus opportunities, and annual equity grants that vest quarterly - Generous 401(k) plan with Upstart matching $2 for every $1 contributed, up to $15,000 per year - Employee Stock Purchase Plan (ESPP) with discounted stock purchase options for eligible employees - Affordable medical, dental, and vision coverage, with multiple plan options - Upstart covers 90% to 100% of the cost depending on the plans you choose - Health Savings Account contributions from Upstart for eligible plans - Income protection benefits, including company-paid Basic Life, AD&D, and Short- and Long-Term Disability coverage, with options to purchase supplemental coverage - Paid time off, sick and safe time, and company holidays - Paid family and parental leave to support caregiving and major life moments - Family-centered benefits through Carrot and Cleo, supporting fertility, parenthood, and caregiving - Employee Assistance Program (EAP) offering mental health support and life-centered resources - Financial wellness resources, including access to financial planning tools and a financial concierge service - Annual wellness allowance to support your physical and emotional well-being and personal development, based on what matters most to you - Annual productivity allowance to invest in relevant tools and resources you need to do your best work, no matter where you work from - Connection and community through team events and onsites, all-company updates, and employee resource groups (ERGs) - Onsite perks, including catered lunches and fully stocked micro-kitchens when working from one of our four offices, located in the Bay Area, Austin, Columbus, and New York City (opening Summer 2026!). Upstart is a proud Equal Opportunity Employer. Just as we are dedicated to improving access to affordable credit for all, we are committed to inclusive and fair hiring practices. If you require reasonable accommodation in completing an application, interviewing, completing any pre-employment testing, or otherwise participating in the employee selection process, please email candidate_accommodations@upstart.com https://www.upstart.com/candidate_privacy_policy

Working at Atlassian Atlassians can choose where they work - whether in an office, from home, or a combination of the two. That way, Atlassians have more control over supporting their family, personal goals, and other priorities. We can hire people in any country where we have a legal entity. Learn how we work at go.atlassian.com/distributed . Your Future Org Atlassian's Intern program combines hands-on technical training, professional growth opportunities, dedicated mentorship, and strong social connections. This holistic approach empowers students to hit the ground running and sets them up for a successful and impactful career at Atlassian! Applications will be accepted from Australian and New Zealand Citizens and Australian Permanent Residents. Our paid internship program runs for 12 weeks between November-February. Your Future Team As a Machine Learning Engineer intern, you'll report to a manager in Core Machine Learning within the broader Analytics group. The team pursues opportunities that produce revenue or MAU improvements, partnering across the company to scale insights into automated ML solutions with strong velocity from ideation to output. - Build machine learning and predictive models to solve product and growth problems. - Translate business problems into technical solutions; deliver robust, low-bug software artifacts. - Collaborate with cross-functional partners to deploy models that create measurable value. Minimum Qualifications - Able to commit to a 12-week full-time (40hrs/week) program from November 2026 - February 2027. - Currently enrolled full-time in a degree program (Master's preferred) and returning to the program after the completion of the internship, graduating by January 2028. - Experience writing software in Python, Scala, or Spark; experience with SQL is a plus. Preferred Qualifications - Coursework or projects in model development, evaluation, and productionisation. - Experience with experimentation, feature engineering, and data pipelines. Benefits & Perks Atlassian offers a wide range of perks and benefits designed to support you, your family and to help you engage with your local community. Our offerings include health and wellbeing resources, paid volunteer days, and so much more. To learn more, visit Atlassian Internships: Students and New Grads | Atlassian . About Atlassian At Atlassian, we're motivated by a common goal: to unleash the potential of every team. Our software products help teams all over the planet and our solutions are designed for all types of work. Team collaboration through our tools makes what may be impossible alone, possible together. We believe that the unique contributions of all Atlassians create our success. To ensure that our products and culture continue to incorporate everyone's perspectives and experience, we never discriminate based on race, religion, national origin, gender identity or expression, sexual orientation, age, or marital, veteran, or disability status. All your information will be kept confidential according to EEO guidelines. To provide you the best experience, we can support with accommodations or adjustments at any stage of the recruitment process. Simply inform our Recruitment team during your conversation with them. To learn more about our culture and hiring process, visit go.atlassian.com/crh .