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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Software Engineer (R14284) - **Company:** Oportun - **Location:** Menlo Park, United States (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Artificial Intelligence, Amazon Web Services, Computer Programming, Databases, Continuous Integration, Data Validation, Distributed Systems, Python (Programming Language), Machine Learning, Microsoft Copilot, Azure Machine Learning, Service-Oriented Architecture, SQL Databases, Workflow Management Systems, Feature Engineering, Apache Spark, Caching, Backend, Pyspark, Git Flow, Kubernetes, Low Latency, Apache Kafka, Data Management, Machine Learning Operations, Api Design, Stream Processing, GPT, Serverless Computing, Docker, Databricks - **Published:** October 9, 2026 - **Apply:** https://arc.dev/remote-jobs/j/redirect/pq01efm02f ## About the Role * You'll have 5+ years of professional software-engineering experience building and operating production systems, with strong programming skills in Python and deep knowledge of API design, distributed systems, service architecture, testing, and software-design fundamentals. * You've demonstrated experience designing and operating reliable, scalable cloud-native services or data-intensive systems, with experience in ML platforms, model serving, feature engineering, data platforms, MLOps, or related systems. * You bring practical experience with SQL, databases, caching, and tracing data or requests across multiple systems, plus familiarity with the ML lifecycle from feature engineering and model training through evaluation, deployment, serving, monitoring, and governance. * You have experience with Docker, Kubernetes, CI/CD, Git-based workflows, and production observability, and you can evaluate technical alternatives and clearly communicate recommendations, trade-offs, risks, and dependencies. * You've demonstrated the ability to mentor engineers, improve engineering practices, lead through technical influence, and connect engineering work to member, business, product, and operational outcomes. Nice to Have * Experience with AWS, Databricks, MLflow, SageMaker, Spark/PySpark, Kafka, or streaming systems. * Experience building feature platforms, model-serving systems, workflow-orchestration platforms, or internal developer platforms. * Familiarity with monitoring model quality, data quality, feature coverage, latency, reliability, or cost efficiency, and experience working with sensitive data in a regulated or financial-services environment. * Experience with Java or another backend language in addition to Python, and familiarity with AI tools such as ChatGPT or Copilot to improve personal productivity. ## Description We're excited to consider talent currently based in India, as well as candidates who are open to relocating to India for this opportunity. Please note that, as this is a "Remote-India" position, the role must be performed from within India. The Opportunity The Machine Learning Platform team builds the software foundations that enable data scientists and machine learning engineers to develop, validate, deploy, and operate models safely and efficiently in production. In this role, you'll lead complex platform work from business context through production outcomes, combining hands-on engineering, architectural judgment, production ownership, and mentorship. In your first year, success means leading meaningful platform initiatives, improving reliability and developer experience, and becoming a trusted technical leader for the ML platform. At Oportun, we move fast and hold each other to a high bar. You'll partner across Data Science, Product, Risk, Fraud, and Engineering to solve ambiguous problems and move the needle for members and the business. What You'll Do Your day-to-day * You'll lead the design, implementation, deployment, and operation of complex platform capabilities that support the machine-learning lifecycle. * You'll design scalable systems for model deployment and serving, feature computation, data validation, workflow orchestration, monitoring, and production support. * You'll build reusable platform components, standards, and automation while improving reliability, scalability, observability, and operational readiness across ML systems. * You'll partner with Data Science, Product, Risk, Fraud, and Engineering teams to translate ambiguous business needs into practical technical solutions. * You'll own significant technical initiatives end to end and lead complex production investigations-clarifying requirements, leading design, delivering safely, measuring results, and implementing durable fixes. * You'll raise engineering quality through thoughtful code and design reviews, mentor engineers through pairing and technical guidance, and contribute to platform technical strategy. * You'll look for ways to use AI tools thoughtfully to work smarter, reduce manual work, and make better decisions faster. Who You Are The right fit looks like this You do not need detailed implementation direction to be effective. Given an ambiguous problem and sufficient context, you can define the technical approach, explain trade-offs, align stakeholders, lead delivery, and own the outcome after launch. You're comfortable navigating complexity and don't wait for perfect information to move forward. You communicate clearly, give direct feedback, mentor others, and connect engineering work to member, business, and operational outcomes.