Job Title: Full Stack Engineer Location: Remote in India (EST Time Zone) Employment Type: Full-Time Department: Engineering Reports To: Director of Technology / Lead Engineer About the Role We are seeking skilled and self-motivated Full Stack Software Developers to join our fast-growing, fully remote engineering team. This is an exciting opportunity to be part of a mission-driven startup that is transforming how caregivers and administrators connect through modern scheduling, credentialing, and communication solutions. As part of a distributed team, you’ll be developing core features of our platform using cutting-edge Microsoft technologies in a high-impact, agile environment. The ideal candidate is passionate about delivering elegant, scalable solutions and thrives in a fast-paced, collaborative setting. Key Responsibilities Develop, test, and deploy features using Blazor , ASP.NET Core Web API , and .NET MAUI Build and maintain hybrid mobile applications for both iOS and Android platforms Work with Azure SQL Server and Dapper for data access Design secure and scalable solutions using Azure App Services , Azure Functions , and Service Bus Implement AI-driven features involving NLP , automation , and predictive analytics Integrate third-party services including Stripe , Checkr , and Plivo Collaborate closely with UI/UX designers using SyncFusion and Bootstrap Manage and support notification systems via Azure Push Notifications , AWS SMTP , and SMS gateways Participate in agile sprint planning , code reviews, and team discussions Required Qualifications Minimum 3 years of professional software development experience Proficiency in C# , .NET Core , and ASP.NET Core Hands-on experience with Blazor (Server or WebAssembly) Experience with .NET MAUI or other cross-platform mobile frameworks Working knowledge of AI/ML technologies , such as OpenAI , Azure AI , or NLP libraries Solid understanding of REST APIs , SQL , and cloud architecture (preferably Azure) Comfortable working independently in a remote, asynchronous team environment Preferred Qualifications (Nice to Have) Familiarity with Azure AI Services , OpenAI API , or custom ML model deployment Experience with Dapper , Azure Maps , and SyncFusion Understanding of CI/CD pipelines and DevOps workflows on Azure Background in healthcare tech , workforce scheduling , or gig-economy platforms Why Join Us? Work remotely in a flexible, async-friendly environment Be part of a purpose-driven team building real-world solutions that make a difference Opportunity to work with modern technologies and cloud-native architecture Collaborative team culture with room to grow, learn, and lead Show more Show less
Job Title: Quant/Data Scientist – Wealth Management Americas Technology Location: Pune, India Department: Data Analytics Foundational Platform (DAFP), Wealth Management Americas (WMA) Technology Employment Type: Contract About the Role We are looking for a highly motivated and innovative Quant/Data Scientist to join our Wealth Management Americas (WMA) Technology – Data Science Team in Pune. In this role, you will tackle complex, real-world challenges in wealth management using cutting-edge technologies, with a focus on machine learning , Generative AI , and large-scale data analysis . You will be part of a collaborative and global team that drives impactful insights and solutions for clients, advisors, and the business. Key Responsibilities Design and develop advanced statistical and machine learning models to derive actionable insights and improve business outcomes. Work with Generative AI (GenAI) technologies to create personalized insights for financial advisors, clients, and prospects. Leverage large datasets to conduct analysis, identify trends, and build predictive models. Integrate AI/ML models into wealth management workflows in partnership with cross-functional teams. Develop and implement solutions using LangChain, LangGraph , and Vector Databases to build scalable, intelligent applications. Contribute to the innovation of client-facing platforms through data science and automation. Required Qualifications & Skills Bachelor’s or higher degree in Machine Learning, Computer Science, Mathematics, Computational Linguistics , or related technical fields from a premier institution. Strong theoretical background in Probability, Statistics, Linear Algebra, Calculus , and Machine Learning . In-depth expertise in Deep Learning and Generative AI/LLM architectures. Practical experience with Large Language Models (LLMs) via platforms like Azure OpenAI , Anthropic , etc. Hands-on experience in cloud ecosystems such as Azure , AWS , GCP , or Databricks . Proficiency in LangChain , LangGraph , and working with Vector Databases . Strong programming skills in Python , with familiarity in libraries such as TensorFlow, PyTorch , or Hugging Face . Knowledge of financial products (e.g., mutual funds, ETFs) and client segmentation is a plus. Strong analytical and problem-solving abilities. Excellent communication skills to articulate complex ideas and insights clearly to both technical and non-technical stakeholders. About the Team You will join a global Data Science team within the Data Analytics Foundational Platform (DAFP) under Wealth Management Americas Technology . This team operates across the US, Poland, and India , driving AI and analytics innovation across the business.
Job Title: Generative AI Engineer Location: Pune, India Department: Data Analytics Foundational Platform (DAFP), Wealth Management Americas (WMA) Technology Employment Type: Full time About the Role We are looking for a highly motivated and innovative Generative AI Engineer to join our Wealth Management Americas (WMA) Technology – Data Science Team in Pune. In this role, you will tackle complex, real-world challenges in wealth management using cutting-edge technologies, with a focus on machine learning , Generative AI , and large-scale data analysis . You will be part of a collaborative and global team that drives impactful insights and solutions for clients, advisors, and the business. Key Responsibilities Design and develop advanced statistical and machine learning models to derive actionable insights and improve business outcomes. Work with Generative AI (GenAI) technologies to create personalized insights for financial advisors, clients, and prospects. Leverage large datasets to conduct analysis, identify trends, and build predictive models. Integrate AI/ML models into wealth management workflows in partnership with cross-functional teams. Develop and implement solutions using LangChain, LangGraph , and Vector Databases to build scalable, intelligent applications. Contribute to the innovation of client-facing platforms through data science and automation. Required Qualifications & Skills Bachelor’s or higher degree in Machine Learning, Computer Science, Mathematics, Computational Linguistics , or related technical fields from a premier institution. Strong theoretical background in Probability, Statistics, Linear Algebra, Calculus , and Machine Learning . In-depth expertise in Deep Learning and Generative AI/LLM architectures. Practical experience with Large Language Models (LLMs) via platforms like Azure OpenAI , Anthropic , etc. Hands-on experience in cloud ecosystems such as Azure , AWS , GCP , or Databricks . Proficiency in LangChain , LangGraph , and working with Vector Databases . Strong programming skills in Python , with familiarity in libraries such as TensorFlow, PyTorch , or Hugging Face . Knowledge of financial products (e.g., mutual funds, ETFs) and client segmentation is a plus. Strong analytical and problem-solving abilities. Excellent communication skills to articulate complex ideas and insights clearly to both technical and non-technical stakeholders. About the Team You will join a global Data Science team within the Data Analytics Foundational Platform (DAFP) under Wealth Management Americas Technology . This team operates across the US, Poland, and India , driving AI and analytics innovation across the business.
Position: Senior Staff Engineer, Risk Job Type: Full-Time (General Recruiting) Location: Remote Working Hours: 9:00 PM / 10:00 PM – 5:00 AM / 6:00 AM (PST) Interview Rounds: 5 Role Overview The Senior Staff Engineer, Risk, will play a pivotal role in driving the technical vision, strategy, and architecture of the company’s Risk Platform. This role will partner closely with leaders in Risk Engineering, Product, Data, AI, and Compliance to design, develop, and operate high-performance, reliable, and flexible risk solutions. The successful candidate will be an innovative technical leader with a proven track record in large-scale software engineering, risk platform architecture, and the application of data and AI to risk management. Key Responsibilities Technical Leadership & Strategy • Lead the technology development of the company’s Risk Platform to ensure functional depth, performance, reliability, and scalability. • Partner with the Senior Director of Risk Engineering to define and execute both short- and long-term technical strategies. • Own the technology architecture of the Risk Platform and ensure seamless integration with products, systems, and LOB engineering teams. • Drive continuous innovation, challenging the status quo to deliver superior technical solutions for diverse risk management needs. Collaboration & Stakeholder Engagement • Collaborate with Risk Product, Risk & Compliance, Data, and AI teams to translate business needs into robust technical solutions. • Partner with Security and SRE teams to meet security requirements, SLOs, and error budgets while enhancing system reliability. • Influence cross-functional stakeholders to align on technical direction and strategy. Team Development & Coaching • Attract, hire, and retain top engineering talent to build a world-class global risk engineering team. • Mentor engineers of varying seniority, fostering a culture of technical excellence, productivity, and innovation. • Set and uphold high standards for engineering principles, best practices, automation, and code quality. Operational Excellence • Ensure the stability and observability of production risk systems, providing clear operational visibility to stakeholders. • Maintain strong DORA metrics and promote continuous improvement in software delivery processes. Qualifications & Experience Technical Expertise: • 10+ years in software design and development at large scale. • Hands-on expertise in architecture, development, deployment, and operations. • Strong background in risk systems, data platforms, and AI/ML applications for risk management. • Deep knowledge of cloud architectures (AWS and/or Azure), Kubernetes, S3, EMR, and Lambda. • Full SDLC experience, including production monitoring and agile methodologies. Leadership & Collaboration: • Proven ability to lead technical teams in a matrixed organization. • Skilled in mentoring and fostering a culture of transparency, innovation, and inclusion. • Strong decision-making ability with a test-and-learn mindset. Additional Skills: • Payments industry experience is a plus. • Excellent written and verbal communication skills. • Bachelor’s degree in Computer Science or related field (Master’s/PhD preferred). Leadership & Personal Characteristics: • Mission-driven, collaborative, and empathetic leadership style. • Champions high standards, embraces change, and challenges the status quo with integrity. • Skilled in managing diverse teams and promoting inclusion, transparency, and trust. • Talent magnet who nurtures and develops top performers. • High learning agility, adaptability, and stakeholder management skills
Job Title: Generative AI Engineer Location: Pune, India Department: Data Analytics Foundational Platform (DAFP), Wealth Management Americas (WMA) Technology Employment Type: Full time About the Role We are looking for a highly motivated and innovative Generative AI Engineer to join our Wealth Management Americas (WMA) Technology – Data Science Team in Pune. In this role, you will tackle complex, real-world challenges in wealth management using cutting-edge technologies, with a focus on machine learning , Generative AI , and large-scale data analysis . You will be part of a collaborative and global team that drives impactful insights and solutions for clients, advisors, and the business. Key Responsibilities Design and develop advanced statistical and machine learning models to derive actionable insights and improve business outcomes. Work with Generative AI (GenAI) technologies to create personalized insights for financial advisors, clients, and prospects. Leverage large datasets to conduct analysis, identify trends, and build predictive models. Integrate AI/ML models into wealth management workflows in partnership with cross-functional teams. Develop and implement solutions using LangChain, LangGraph , and Vector Databases to build scalable, intelligent applications. Contribute to the innovation of client-facing platforms through data science and automation. Required Qualifications & Skills Bachelor’s or higher degree in Machine Learning, Computer Science, Mathematics, Computational Linguistics , or related technical fields from a premier institution. Strong theoretical background in Probability, Statistics, Linear Algebra, Calculus , and Machine Learning . In-depth expertise in Deep Learning and Generative AI/LLM architectures. Practical experience with Large Language Models (LLMs) via platforms like Azure OpenAI , Anthropic , etc. Hands-on experience in cloud ecosystems such as Azure , AWS , GCP , or Databricks . Proficiency in LangChain , LangGraph , and working with Vector Databases . Strong programming skills in Python , with familiarity in libraries such as TensorFlow, PyTorch , or Hugging Face . Knowledge of financial products (e.g., mutual funds, ETFs) and client segmentation is a plus. Strong analytical and problem-solving abilities. Excellent communication skills to articulate complex ideas and insights clearly to both technical and non-technical stakeholders. About the Team You will join a global Data Science team within the Data Analytics Foundational Platform (DAFP) under Wealth Management Americas Technology . This team operates across the US, Poland, and India , driving AI and analytics innovation across the business.
Job Description: ML Engineer / Gen AI Engineer Client : UBS Location : Pune, India Position Overview We are seeking a highly skilled ML Engineer / Gen AI Engineer with a strong foundation in Machine Learning, Graph algorithms, SQL, and Generative AI. The ideal candidate will design, develop, and deploy robust, scalable solutions, collaborating with cross-functional teams to drive innovation in AI-driven applications for UBS. Key Responsibilities Develop and Optimize ML Models : Design, implement, and fine-tune machine learning models using Python libraries such as TensorFlow, PyTorch, or scikit-learn to solve real-world financial problems. Graph-Based Solutions : Build and optimize graph-based algorithms and data structures using libraries like NetworkX or PyG (PyTorch Geometric) for applications such as network analysis, fraud detection, or knowledge graphs. SQL and Data Management : Write complex SQL queries to manage, transform, and analyze large datasets, ensuring efficient data pipelines and integration with databases like PostgreSQL, MySQL, or SQLite. Generative AI Development : Design and implement generative AI models (e.g., LLMs, GANs, or VAEs) using frameworks like Hugging Face, LangChain, or custom solutions for tasks such as text generation, data augmentation, or synthetic data creation. Code Quality and Scalability : Write clean, modular, and maintainable Python code, adhering to best practices, and optimize for performance and scalability in production environments. Collaboration and Innovation : Work closely with data scientists, engineers, and business teams at UBS to translate requirements into technical solutions, contributing to architectural decisions and innovative AI strategies. Data Pipeline Development : Build and maintain ETL pipelines to preprocess and integrate data for machine learning and graph-based applications, using tools like Apache Airflow or Pandas. Model Deployment : Deploy machine learning and generative AI models to production environments using tools like Docker, Kubernetes, or cloud platforms (AWS, GCP, Azure). Research and Stay Current : Stay updated on advancements in machine learning, graph theory, and generative AI, applying cutting-edge techniques to enhance project outcomes. Required Qualifications Education : Bachelor’s or Master’s degree in Computer Science, Data Science, Mathematics, or a related field. PhD is a plus. Experience : 5+ years of professional Python programming experience. 3+ years of hands-on experience in machine learning model development and deployment. Proven expertise in graph algorithms, graph databases (e.g., Neo4j), or graph-based machine learning. Strong proficiency in SQL and relational database management. 2+ years working with generative AI models (e.g., LLMs, GANs, or diffusion models). Technical Skills : Expert-level Python programming (e.g., Pandas, NumPy, scikit-learn, TensorFlow, PyTorch). Experience with graph libraries (e.g., NetworkX, PyG, or DGL) and graph databases. Advanced SQL skills for querying and optimizing large datasets. Familiarity with generative AI frameworks (e.g., Hugging Face, LangChain, or OpenAI APIs). Proficiency in version control (Git), CI/CD pipelines, and containerization (Docker). Experience with cloud platforms (AWS, GCP, or Azure) for model deployment. Soft Skills : Strong problem-solving and analytical skills. Excellent communication and collaboration abilities. Ability to work in a fast-paced, innovative environment. Preferred Qualifications Experience with large-scale distributed systems and big data frameworks (e.g., Spark, Hadoop). Familiarity with MLOps tools (e.g., MLflow, Kubeflow) for model lifecycle management. Knowledge of advanced graph algorithms (e.g., community detection, shortest path, centrality measures). Contributions to open-source AI or graph-related projects. Experience with real-time or streaming data processing. Familiarity with financial services or banking domain challenges. Why Join Us? Work on cutting-edge AI and graph-based projects with real-world impact in the financial sector. Collaborate with a talented, global team in a supportive and innovative environment at UBS. Competitive salary, comprehensive benefits, and opportunities for professional growth. Access to state-of-the-art tools and technologies to fuel your expertise.
Job Description: ML Engineer / Gen AI Engineer Client : UBS Location : Pune, India Position Overview We are seeking a highly skilled ML Engineer / Gen AI Engineer with a strong foundation in Machine Learning, Graph algorithms, SQL, and Generative AI. The ideal candidate will design, develop, and deploy robust, scalable solutions, collaborating with cross-functional teams to drive innovation in AI-driven applications for UBS. Key Responsibilities Develop and Optimize ML Models : Design, implement, and fine-tune machine learning models using Python libraries such as TensorFlow, PyTorch, or scikit-learn to solve real-world financial problems. Graph-Based Solutions : Build and optimize graph-based algorithms and data structures using libraries like NetworkX or PyG (PyTorch Geometric) for applications such as network analysis, fraud detection, or knowledge graphs. SQL and Data Management : Write complex SQL queries to manage, transform, and analyze large datasets, ensuring efficient data pipelines and integration with databases like PostgreSQL, MySQL, or SQLite. Generative AI Development : Design and implement generative AI models (e.g., LLMs, GANs, or VAEs) using frameworks like Hugging Face, LangChain, or custom solutions for tasks such as text generation, data augmentation, or synthetic data creation. Code Quality and Scalability : Write clean, modular, and maintainable Python code, adhering to best practices, and optimize for performance and scalability in production environments. Collaboration and Innovation : Work closely with data scientists, engineers, and business teams at UBS to translate requirements into technical solutions, contributing to architectural decisions and innovative AI strategies. Data Pipeline Development : Build and maintain ETL pipelines to preprocess and integrate data for machine learning and graph-based applications, using tools like Apache Airflow or Pandas. Model Deployment : Deploy machine learning and generative AI models to production environments using tools like Docker, Kubernetes, or cloud platforms (AWS, GCP, Azure). Research and Stay Current : Stay updated on advancements in machine learning, graph theory, and generative AI, applying cutting-edge techniques to enhance project outcomes. Required Qualifications Education : Bachelor’s or Master’s degree in Computer Science, Data Science, Mathematics, or a related field. PhD is a plus. Experience : 5+ years of professional Python programming experience. 3+ years of hands-on experience in machine learning model development and deployment. Proven expertise in graph algorithms, graph databases (e.g., Neo4j), or graph-based machine learning. Strong proficiency in SQL and relational database management. 2+ years working with generative AI models (e.g., LLMs, GANs, or diffusion models). Technical Skills : Expert-level Python programming (e.g., Pandas, NumPy, scikit-learn, TensorFlow, PyTorch). Experience with graph libraries (e.g., NetworkX, PyG, or DGL) and graph databases. Advanced SQL skills for querying and optimizing large datasets. Familiarity with generative AI frameworks (e.g., Hugging Face, LangChain, or OpenAI APIs). Proficiency in version control (Git), CI/CD pipelines, and containerization (Docker). Experience with cloud platforms (AWS, GCP, or Azure) for model deployment. Soft Skills : Strong problem-solving and analytical skills. Excellent communication and collaboration abilities. Ability to work in a fast-paced, innovative environment. Preferred Qualifications Experience with large-scale distributed systems and big data frameworks (e.g., Spark, Hadoop). Familiarity with MLOps tools (e.g., MLflow, Kubeflow) for model lifecycle management. Knowledge of advanced graph algorithms (e.g., community detection, shortest path, centrality measures). Contributions to open-source AI or graph-related projects. Experience with real-time or streaming data processing. Familiarity with financial services or banking domain challenges. Why Join Us? Work on cutting-edge AI and graph-based projects with real-world impact in the financial sector. Collaborate with a talented, global team in a supportive and innovative environment at UBS. Competitive salary, comprehensive benefits, and opportunities for professional growth. Access to state-of-the-art tools and technologies to fuel your expertise.