Engineer Jobs

ENGINEER, Tainan Warehouse — Tainan, Taiwan. Apply via Workday.

ENGINEER, F11 OPS PLANNING TACTICAL CAPACITY — 3 Locations. Apply via Workday.

ENGINEER - HBM VERIFICATION — Jalisco, Mexico. Apply via Workday.

ENGINEER, OMT HVM PROD.(Tongluo) — Miaoli - Tongluo, Taiwan. Apply via Workday.

ENGINEER, ID1 ME - WET PROCESS — Taoyuan - Fab 11, Taiwan. Apply via Workday.

Engineer - QEM CC — Fab 10N/X, Singapore. Apply via Workday.

Engineer, MRDA Process — Fab 10A, Singapore. Apply via Workday.

Engineer, HIG-HBM Product System & Engineering (Media Health Manufacturing) — Fab 10A, Singapore. Apply via Workday.

Engineer, Strategic Planning - Capital & Reuse — Fab 10N/X, Singapore. Apply via Workday.

Engineer, PIE RDA — Fab 10N/X, Singapore. Apply via Workday.

Engineering Manager –802.15.4 embedded wireless networking (10 to 13years of exp) — Hyderabad. Apply via Workday.

Razorpay is one of India’s leading full-stack financial technology companies, powering the way businesses move, manage, and grow money. Founded in 2014 by Harshil Mathur and Shashank Kumar with a simple vision - to simplify payments for Indian businesses - we’ve since grown into a fintech powerhouse driving India’s digital payment revolution. Razorpay powers millions of businesses with a smarter, scalable stack that goes beyond transactions to help them truly build and grow. From building AI-native agentic payments, to AI-assisted fraud detection and real-time risk intelligence to automated reconciliation, smart payouts, and predictive financial insights, we are embedding intelligence across our stack to make money movement faster, safer, and more efficient. In close collaboration with ecosystem partners - including banks, networks, regulators - we are pioneering industry-first solutions that are shaping the next era of fintech Across India, Singapore and Malaysia, our products span everything from seamless checkouts to payroll automation - powering a fintech ecosystem that’s redefining how money moves across Asia. Today, that ecosystem supports everyone from early-stage startups to some of India’s largest enterprises, enabling them to accept, process, and disburse payments at scale while expanding into new ways of managing money more efficiently. Our scale speaks volumes: Razorpay processes $180+ billion in annualized transactions, powering leading businesses like Airbnb, Facebook, WhatsApp, Airtel, CRED, BookmyShow, Zomato, Swiggy, Lenskart, Mirae Asset Capital markets, Indian Oil, National Pension Scheme - and over 100 of India’s unicorns. With strong roots in India and growing operations in Southeast Asia, we are shaping the next chapter of financial technology across the region. We are backed by global investors including GIC, Peak XV Partners (formerly Sequoia Capital India & SEA), Tiger Global, Ribbit Capital, Matrix Partners, MasterCard, and Salesforce V

Razorpay is one of India’s leading full-stack financial technology companies, powering the way businesses move, manage, and grow money. Founded in 2014 by Harshil Mathur and Shashank Kumar with a simple vision - to simplify payments for Indian businesses - we’ve since grown into a fintech powerhouse driving India’s digital payment revolution. Razorpay powers millions of businesses with a smarter, scalable stack that goes beyond transactions to help them truly build and grow. From building AI-native agentic payments, to AI-assisted fraud detection and real-time risk intelligence to automated reconciliation, smart payouts, and predictive financial insights, we are embedding intelligence across our stack to make money movement faster, safer, and more efficient. In close collaboration with ecosystem partners - including banks, networks, regulators - we are pioneering industry-first solutions that are shaping the next era of fintech Across India, Singapore and Malaysia, our products span everything from seamless checkouts to payroll automation - powering a fintech ecosystem that’s redefining how money moves across Asia. Today, that ecosystem supports everyone from early-stage startups to some of India’s largest enterprises, enabling them to accept, process, and disburse payments at scale while expanding into new ways of managing money more efficiently. Our scale speaks volumes: Razorpay processes $180+ billion in annualized transactions, powering leading businesses like Airbnb, Facebook, WhatsApp, Airtel, CRED, BookmyShow, Zomato, Swiggy, Lenskart, Mirae Asset Capital markets, Indian Oil, National Pension Scheme - and over 100 of India’s unicorns. With strong roots in India and growing operations in Southeast Asia, we are shaping the next chapter of financial technology across the region. We are backed by gl

At Bolna, we’re building tools that change the way teams leverage Voice AI. We’re looking for a Founding Machine Learning Engineer to own the end-to-end lifecycle of building, evaluating, deploying, and improving models that power millions of production conversations. This is a high-impact, high ownership role where you won’t just work on Bolna’s ML stack—you’ll help build the foundation it scales on. Our team includes IIT alumni with experience at Bain, Atlassian, Uber, Zomato, and LinkedIn, and is backed by leading investors. Responsibilities: Build the data engine - Design pipelines to source and clean conversational voice data across Indian languages, accents, and telephony conditions. Fine-tune models that ship - Fine tune and train models to improve accuracy, speed, and reliability across different use-cases. Define what "good" means - Build evaluation datasets and benchmarks for transcription accuracy, voice naturalness, interruption handling, latency, and end-to-end conversation quality. Set up human-in-the-loop pipelines to capture subjective quality at scale. Ship to production - Work with the engineering team to deploy models into a latency-sensitive, high-volume system. Monitor performance in the wild, debug regressions, and iterate fast. Required Skills: 3+ years of hands-on ML experience with deep practical real-world experience in training models. Strong Python and PyTorch fundamentals with exposure in distributed training, and modern fine-tuning techniques (LoRA, QLoRA, DPO, RLHF, etc.). Training data as a first-class problem. Experience designing data pipelines from collection, cleaning, labeling, deduplication, augmentation and treating data quality as a core engineering discipline. Rigorous about evaluation. You know that "looks good in a demo" is not a benchmark. You build the evals before you trust the model. Speech model experience is a plus with real-time / streaming inference experience where you would have contributed to latency optimization

At Bolna, we’re building tools that change how businesses leverage voice AI. We’re looking for a Software Engineer to build reliable, scalable systems that power millions of production conversations across languages, industries, and telephony environments. This is a high-impact, high-ownership role where you’ll work on core platform problems across distributed systems, real-time communication, developer infrastructure, and customer-facing products. Our team includes IIT alumni with experience at Bain, Atlassian, Uber, Zomato, and LinkedIn, and is backed by leading investors. Responsibilities Build systems that operate at scale: Design and build backend services that support high-volume, real-time voice AI conversations with strong reliability, performance, and fault tolerance. Own features end to end: Take problems from product requirements and technical design through implementation, testing, deployment, monitoring, and iteration. Improve platform reliability: Build systems that are observable, resilient, and easy to debug. Identify bottlenecks, reduce failure rates, and improve system availability. Work on real-time infrastructure: Solve problems across telephony, streaming audio, webhooks, queues, scheduling, concurrency, and low-latency communication. Build for developers and customers: Improve APIs, SDKs, integrations, dashboards, and internal tools that make the Bolna platform easier to use and operate. Raise the engineering bar: Contribute to technical design reviews, code quality, testing standards, documentation, incident response, and engineering best practices. Required Skills Strong engineering fundamentals: Solid understanding of data structures, algorithms, databases, networking, operating systems, and distributed systems. Backend development experience: 2+ years of experience building and operating production backend systems using Python, Go, Java, Node.js, or a similar language. Production ownership: Experience shipping software to production and own