Low Latency Fpga Developer in India

NK Securities Research is a leading financial firm that leverages cutting edge technology and sophisticated algorithms to trade the financial markets. Founded in 2011, we have gained invaluable experience in the field of High Frequency Trading across different asset classes. With a focus on innovation, entrepreneurship, and collaboration, we aim to foster a dynamic work environment that reflects a startup culture. Role Overview As an FPGA Developer, you will design, implement, and rigorously test RTL (Register-Transfer Level) designs to power our high-frequency trading strategies. Your contributions will play a pivotal role in reducing system latency and enhancing performance, directly impacting trading outcomes. Key Responsibilities Design and Implementation: Develop high-performance RTL designs using VHDL or Verilog for FPGA-based systems. Optimize hardware implementations for ultra-low latency and high throughput. Testing and Debugging: Perform thorough functional and timing testing of RTL designs, ensuring adherence to specifications. Debug and resolve issues using FPGA debugging tools such as SignalTap, ChipScope, or ModelSim. Collaboration and Documentation: Work closely with hardware and software teams to ensure seamless integration of FPGA solutions with the Software Trading Stack. Maintain clear and comprehensive documentation of designs, test cases, results and benchmarks Qualifications Technical Skills: RTL Development: Strong fundamentals in digital logic design, Boolean algebra, FSMs and synchronous design. Proficiency in VHDL or Verilog/SystemVerilog, with a strong focus on efficient and optimized designs. FPGA Tools: Hands-on experience with industry-standard tools such as Xilinx Vivado. Testing and Verification: Expertise in writing testbenches and conducting simulation-based verification. Familiarity with static timing analysis and achieving timing closure. Familiar with CocoTB or any similar testing setup. Debugging: Proficiency in GHDL synthesis a

Role: Network Engineer Location: Gurgaon Graviton is a privately funded quantitative trading firm striving for excellence in financial markets' research. We are seeking a Network Engineer for our team in Gurgaon. Graviton trades across a multitude of asset classes and trading venues using a gamut of concepts and techniques ranging from time series analysis, filtering, classification, stochastic models, pattern recognition to statistical inference analysing terabytes of data to come up with ideas to identify pricing anomalies in financial markets. Key Responsibilities Design, deploy, operate, and troubleshoot low-latency network infrastructure used by trading firms. Manage connectivity to global stock exchanges, brokers, market-data providers, and ISPs. Build and maintain colocation infrastructure including routers, switches, Layer-1 devices (added advantage), structured cabling and cross connects. Configure and support Cisco Nexus, Arista and similar platform devices. Design and troubleshoot Layer 2 and Layer 3 networks including: VLANs, VRFs, BGP, OSPF, Static routing, PIM, IGMP, Multicast, SSM, ACLs and QoS. Troubleshoot packet loss, multicast issues, duplicate packets, IGMP/PIM and multicast/BGP routing. Monitor and optimize latency, jitter, packet loss, interface errors, congestion, and network performance. Work with ultra-low-latency technologies including: Cut-through switching, Layer-1 switches, FPGA-based network devices, Kernel-bypass networking, ExaNIC/Solarflare NICs, Hardware timestamping. Configure and troubleshoot PTP and clock synchronization infrastructure. Perform server and network equipment installation in exchange and third-party data centres. Manage rack layout, patching, cable optimization, optics, DACs, cross-connects, and inventory. Coordinate network changes with exchanges, telecom providers, brokers, vendors, and data-centre teams. Plan and execute production changes during approved maintenance windows. Perform pre-change validation, c

Job Overview: We are seeking a high-caliber Rust Systems Engineer to design, build, and optimize high-throughput, low-latency backend systems and infrastructure. In this role, you will go beyond web APIs—tackling low-level performance bottlenecks, complex state management, parallel compute algorithms, and concurrent data processing pipelines. If you thrive on deterministic memory management, zero-cost abstractions, and writing safe, blazingly fast concurrent systems, this role is for you. Key Responsibilities: High-Performance Architecture: Design and implement zero-cost, high-throughput, low-latency engine components and data processing pipelines in Rust. Concurrent & Thread-Safe Systems: Build thread-safe, lock-free, or fine-grained locked data structures and state machines capable of scaling across multi-core architectures without race conditions. Priority & Real-Time Threading: Design custom thread pools, task schedulers, and execution queues with priority-based task scheduling and resource allocation controls. Algorithmic Optimization: Implement complex computational logic, including high-efficiency recursive algorithms, tail-call optimizations, and dynamic cache-friendly data structures. Resource & Memory Management: Leverage Rust’s ownership model, lifetime annotations, custom allocators, and non-blocking I/O to achieve predictable low-latency profiling (minimizing allocations and cash misses). System Profiling & Benchmarking: Conduct continuous benchmarking (criterion), flame graph analysis, memory profiling (Val grind/heap track), and CPU SIMD/vectorization optimizations. Key Skills: Core Rust & Functional Programming: Advanced Rust Mastery: Deep experience with Rust internals (stdsync, stdcell, custom Drop, unsafe Rust boundaries, and macro systems). Closures & Higher-Order Functions: Mastery of Rust’s functional traits (Fn, FnMut, FnOnce), capturing environments, move semantics within closures, and passing unboxed closures for zero

NK Securities Research is a leading financial firm that leverages cutting-edge technology and sophisticated algorithms to trade the financial markets. Founded in 2011, we have gained invaluable experience in the field of High-Frequency Trading (HFT) across different asset classes. Role Overview We’re looking for engineers who can take AI work beyond experiments and make it hold up in production. You’ll work closely with quant researchers and infra engineers to build AI systems that actually get used improving research speed and internal tooling without slowing down the core stack. We value engineers who think about trade-offs, test what they build, and care about how things run in production. What You’ll Build Production AI Ship models that meet defined latency and reliability expectation Add monitoring, rollback, and guardrails before anything goes live Optimise inference across CPU/GPU environments when it matters Integration into Real Systems Plug AI into data-heavy workflows without hurting performance Work within existing low-latency architecture instead of fighting it Profile and remove bottlenecks rather than guessing AI for Engineers & Researchers Build tools that genuinely speed up research and development Improve code understanding, review workflows, and internal knowledge retrieval Keep systems auditable and predictable LLM & Retrieval Systems Implement structured RAG and embedding pipelines with validation in place Create safe integration layers between models and internal systems Performance & Standards Track latency, drift, and stability — not just accuracy Build observability into everything you ship Help raise the bar for how AI is engineered here What We’re Looking For Strong Python fundamentals Clear thinking around system design and performance trade-offs Experience deploying AI systems in production (1–5 years is typical) Familiarity with transformers, embeddings, or LLM deployment Nice to have: Exposure to C++ / Rust / Go E

Description: Graviton is a privately funded quantitative trading firm striving for excellence in financial markets' research. We are seeking a Senior Quantitative Trader for our team in Gurgaon. We trade across a multitude of asset classes and trading venues with significant market share and constantly seeking to replicate our successes to newer exchanges and products. As a Senior Quantitative Trader your responsibilities will include Develop and deploy completely automated systematic strategies with short holding periods and high turnover Typical strategies deployed include Alpha-seeking strategies and Market Making Rigorously back-test strategies on in-house research infrastructure Graviton can offer a successful Quantitative Trader Exceptional financial rewards Friendly and collegial working environment Access to advanced trading systems for low-latency execution of strateiges Excitement of being a part of a new expanding trading business Requirements : Deep experience in HF/UHF Trading Live HF Trading experience for at least 2 years. PnL Track record with excellent sharpe ratios. Programming experience in C++ or C Proficiency in using Python, R, or Matlab for statistical/data analysis of HFT tick data Possess a degree in a highly analytical field, such as Engineering, Mathematics, Computer Science Benefits: Our open and casual work culture gives you the space to innovate and deliver. Our cubicle free offices , disdain for bureaucracy and insistence to hire the very best creates a melting pot for great ideas and technology innovations. Everyone on the team is approachable, there is nothing better than working with friends! Our perks have you covered. Competitive compensation 4 Weeks of paid vacation Monthly after work parties Catered breakfast and lunch Fully stocked kitchen Gym membership International team outing

AI/ML – Investment Services A Career with Point72's AI/ML – Investment Services Team The AI/ML – Investment Services team at Point72 spearheads the development of cutting-edge AI solutions that seek to transform our business processes and enhance enterprise intelligence. The team aims to bridge the gap between business challenges and technological innovation, collaborating with stakeholders across the firm and leveraging expertise in generative AI, data engineering, and machine learning. WHAT YOU'LL DO Build and scale core backend services and platforms that power generative AI applications and data infrastructure used across the firm’s investment workflows Design and implement high-throughput, low-latency data pipelines to ingest, normalize, and serve both structured and unstructured data Develop robust APIs and microservices to support model inference, feature serving, and downstream applications Integrate generative AI tools and model-serving workflows into production, including embedding stores, retrieval components, and fine-tuning pipelines Optimize system performance, cost, and reliability through profiling, capacity planning, and architectural improvements Implement automated testing, continuous delivery pipelines, monitoring, and incident response practices to maintain production health Partner with data scientists, AI engineers, product owners, and operations to translate models and prototypes into scalable, production-grade solutions Mentor engineers, lead code reviews, and establish engineering best practices for maintainability, security, and observability Own end-to-end delivery, operational runbooks, and metrics-driven measurement of feature impact and system reliability WHAT'S REQUIRED Bachelor’s degree in computer science, software engineering, or a related technical field Minimum 5+ years of professional experience building backend systems and production services Demonstrated experience designing and operating large-scale data engineering pipelines

Who We Are Simpplr is the AI-powered intranet for unifying the digital workplace. It brings people, trusted knowledge, apps, and agents into a coherent digital experience. Powered by a proprietary EX Knowledge Graph, Simpplr synthesizes signals and context across connected systems to deliver personalized information and actions. The platform serves as a digital hub supporting communications, engagement, employee services, and work. With low-code extensibility and enterprise-grade security and governance, Simpplr enables confident operation at scale. More than 1,000 organizations — including AAA, the NHS, Penske, and Moderna — trust Simpplr to keep their workforce informed, aligned, and productive. Learn more at simpplr.com . About the role We are looking for a Lead Voice AI Engineer to build production-grade Voice Agents for frontline heavy verticals like healthcare, manufacturing, warehousing, retail, hospitality focusing on employee support, procurement, collections, logistics, ordering etc. You will lead the design of low-latency, real-time voice systems combining ASR, TTS, LLMs, conversational AI, enterprise workflows, knowledge retrieval, compliance, and human handoff. This is a hands-on technical leadership role for someone who can take Voice AI from architecture to production. Responsibilities Design and build the real-time voice runtime for live conversations. Build and optimize streaming ASR, TTS, VAD, endpointing, turn-taking, and barge-in. Build adaptive voice pipelines for high-noise frontline environments (60-112 dB), hospitals, factory floors, warehouses, including server-side noise cancellation, echo suppression, and dynamic ASR/TTS optimization for PSTN and mobile phone audio quality. Architect multi-provider speech routing across a broad multilingual matrix, including code-switching (e.g., Spanglish, Hinglish), where no single ASR or TTS provider covers all languages, and language detection, provider selection, and fallback chains must operate

Everpure (NYSE: P) has evolved from storage pioneer to data platform, closing fiscal 2026 with $3.7 billion in revenue, its first billion-dollar quarter, and accelerating growth into FY27. Our strategic agenda spans the companies defining the next era of technology - hyperscalers, AI labs, the AI hardware supply chain, data platform providers, and the broader AI ecosystem. This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us. THE ROLE Join the Pipeline Engineering team at Everpure™ as a Full Stack Software Engineer to build and scale the pipeline visibility layer for FlashArray, FlashBlade, and Hyperscale — the core platform through which engineers and customers understand and act on CI results . In this high-impact position, you will own responsive web interfaces, API gateway architecture, and AI-assisted workflows that convert raw pipeline data into actionable signal, eliminating operational toil across our engineering organization. WHAT YOU'LL DO Build the Pipeline Visibility Layer: Architect and ship high-performance web applications using modern JavaScript/TypeScript frameworks to deliver real-time pipeline status, test results, and failure analytics at enterprise scale. Own Gateway & Backend Services: Develop and operate low-latency API gateways and backend microservices using typed systems languages (such as Go or Rust) to aggregate data across systems, enforce strict multi-tenant boundaries, and maintain reliable system contracts. Deliver Secure Access Controls: Implement robust authentication and authorization protocols (OAuth2/OIDC, SSO, RBAC) to ensure internal teams and external customers experience seamlessly scoped and fully audited access. Integrate AI Triage Workflows: Engineer retrieval-augmented generation (RAG) pipelines and LLM integrations over test metadata and failure logs to automate root-cause summaries, flak

Who we are At Twilio, we’re shaping the future of communications, all from the comfort of our homes. We deliver innovative solutions to hundreds of thousands of businesses and empower millions of developers worldwide to craft personalized customer experiences. Our dedication to remote-first work , and strong culture of connection and global inclusion means that no matter your location, you’re part of a vibrant team with diverse experiences making a global impact each day. As we continue to revolutionize how the world interacts, we’re acquiring new skills and experiences that make work feel truly rewarding. Your career at Twilio is in your hands. . Hiring and how we work We use Artificial Intelligence (AI) to help make our hiring process efficient. That said, every hiring decision is made by real Twilions! Also, while we are a remote-first company, you may be asked to report in person on an ad-hoc basis for team gatherings, functional off-sites or customer meetings. . See yourself at Twilio Join the team as our next Software Engineer Intern for a duration of 6 months, starting on January 12th 2027. About the job This position is needed to design, develop, deploy and operate software solutions and help Twilio deliver real-time, low latency capabilities for next-generation communications. Twilio Interns in Software Engineering are eager to learn and inspire and like to think at scale and meet high availability goals, bringing a focus to solving resiliency, latency and quality challenges in our virtualized cloud environment. Software Engineers want to develop technical skills and industry experience while working on complex distributed systems. Responsibilities As a Software Engineer Intern you will experience the following - Be a Software Engineer, not just an "intern". Ship many different projects during the 6 months. Learn from passionate engineers at Twilio who solve problems in distributed computing, real-time DSP (audio pr

About DevRev At DevRev, we're building the future of work with Computer – your AI teammate. Unlike traditional tools, Computer unifies all your data sources, tools, and workflows into a single AI-ready platform, giving employees real-time insights, proactive suggestions, and powerful agentic actions. It extends your existing software with AI-native apps and agents that work alongside your teams and customers – updating workflows, coordinating across teams, and eliminating repetitive work. We call this Team Intelligence: human-AI collaboration that breaks down silos, brings people back together, and frees you to solve bigger problems. Backed by Khosla Ventures and Mayfield with $150M+ raised, DevRev is trusted by global companies across industries. What You’ll Do: Architect the Future of AI Infrastructure: You will design, build, and own the end-to-end platform that supports the entire lifecycle of our ML models—from massive-scale distributed training to ultra-low-latency, highly-available inference. Optimize and Serve Cutting-Edge Models: You'll implement and scale sophisticated inference stacks for LLMs using frameworks like vLLM, TensorRT-LLM, or SGLang . You’ll solve complex challenges in throughput, latency, token streaming, and automated scaling to deliver a seamless user experience. Empower AI Innovation: You will act as a strategic partner to our AI Research and Data Science teams. You’ll create a seamless developer experience that accelerates their ability to experiment, fine-tune, and deploy groundbreaking models with velocity and confidence. Automate Everything: You'll develop robust CI/CD/CT (Continuous Training) pipelines using tools like Argo Workflows, ArgoCD, and GitHub Actions to automate model validation, deployment, and lifecycle management, ensuring our systems are both agile and rock-solid. What are we looking for Experience: 5+ years in infrastructure or software engineering, with at least 2+ years laser-focused on MLOps or ML infrastructu

About DevRev At DevRev, we're building the future of work with Computer – your AI teammate. Unlike traditional tools, Computer unifies all your data sources, tools, and workflows into a single AI-ready platform, giving employees real-time insights, proactive suggestions, and powerful agentic actions. It extends your existing software with AI-native apps and agents that work alongside your teams and customers – updating workflows, coordinating across teams, and eliminating repetitive work. We call this Team Intelligence: human-AI collaboration that breaks down silos, brings people back together, and frees you to solve bigger problems. Backed by Khosla Ventures and Mayfield with $150M+ raised, DevRev is trusted by global companies across industries. About the role DevRev is hiring a Senior Product Manager for the Computer Data and Analytics Platform – a hands-on product leader who will own the trusted data foundation that makes Computer precise, useful, and safe across every experience. Computer should not merely report on work. It should understand customer, product, and operational context; reason across it; and help people and agents take the right action. The Computer Data and Analytics Platform makes that possible through a unified, governed, low-latency data layer that turns data from DevRev and connected systems into durable context for humans, applications, analytics experiences, and AI agents. You will define how data is captured, modeled, governed, queried, and activated across DevRev. The platform will support operational reporting and embedded analytics, while also enabling grounded, context-rich agentic conversations in Computer – helping users ask questions, investigate work, receive trusted answers, and take safe actions in the flow of work. This is a unique opportunity to build the foundation for an AI-native operating system – where customer context, product telemetry, structured records, events, and machine reasoning converge. What y

Everpure (NYSE: P) has evolved from storage pioneer to data platform, closing fiscal 2026 with $3.7 billion in revenue, its first billion-dollar quarter, and accelerating growth into FY27. Our strategic agenda spans the companies defining the next era of technology - hyperscalers, AI labs, the AI hardware supply chain, data platform providers, and the broader AI ecosystem. This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us. THE ROLE Join the Pure Solutions team as a Senior MLOps Solutions Engineer to architect and build high-scale, enterprise-grade AI/ML solutions. You will be instrumental in integrating Pure Storage platforms with the evolving open-source MLOps ecosystem (Kubeflow, MLflow, Ray) to operationalize the complete machine learning lifecycle. This role requires a creative technologist with deep Python expertise to drive innovation and enable our customers and partners to achieve production AI success. WHAT YOU'LL DO Design and Automate MLOps Pipelines: Lead the development of end-to-end MLOps workflows using CI/CD tools (Git/Jenkins) and orchestration platforms (MLflow/Kubeflow), specifically integrating Pure Storage's FlashBlade, FlashArray, and Portworx as the high-performance data plane for data ingestion, training, and inference. Build High-Performance AI/ML Reference Architectures: Create validated, repeatable deployment models using Infrastructure as Code (e.g., Ansible, Terraform) for AI/ML environments spanning bare metal, virtual machines, and GPU-accelerated Kubernetes clusters, ensuring optimal performance for distributed training. Optimize and Operationalize GPU Inference: Architect and implement solutions for high-throughput, low-latency model serving, utilizing technologies like NVIDIA Triton Inference Server and advanced optimization techniques (quantization, model sharding like DeepSpeed/Megatron-LM, and dynamic bat

Bloomreach is building the world’s premier agentic platform for personalization .We’re revolutionizing how businesses connect with their customers, building and deploying AI agents to personalize the entire customer journey. We're taking autonomous search mainstream, making product discovery more intuitive and conversational for customers, and more profitable for businesses. We’re making conversational shopping a reality, connecting every shopper with tailored guidance and product expertise — available on demand, at every touchpoint in their journey. We're designing the future of autonomous marketing , taking the work out of workflows, and reclaiming the creative, strategic, and customer-first work marketers were always meant to do. And we're building all of that on the intelligence of a single AI engine — Loomi — so that personalization isn't only autonomous…it's also consistent.From retail to financial services, hospitality to gaming, businesses use Bloomreach to drive higher growth and lasting loyalty. We power personalization for more than 1,400 global brands, including American Eagle, Sonepar, and Pandora. About the Team: AI Search The AI Search team owns Bloomreach’s core search platform, serving hundreds of millions of queries per day across enterprise customers. We build and operate highly scalable, low-latency systems that combine traditional information retrieval with modern ML-driven ranking and semantic understanding — all in production at scale. This team sits at the intersection of systems engineering, search relevance, and applied ML , with direct impact on customer revenue and experience. The Role: As a Senior Staff Engineer , you will be a technical leader responsible for shaping the architecture and long-term evolution of Bloomreach’s Search platform. You will lead complex initiatives, set technical direction, and mentor engineers, while remaining deeply hands-on. This role is ideal for someone

Role Purpose We’re looking for a Staff/Senior Machine Learning Engineer with deep expertise in computer vision and biometrics to lead the design and scaling of face recognition systems in production. You’ll build and train models, and own ML systems end-to-end on AWS. The final job level for this role will be determined following the interview process. What You’ll Do Lead the design and development of computer vision systems for biometrics (face attributes, detection, quality, and recognition) Rigorous fairness analysis and benchmarking of biometric models across various datasets and operating conditions. Architect, train, and optimize models using PyTorch, Tensorflow, and/or JAX Own and evolve end-to-end ML pipelines, from data ingestion to deployment. Design automated pipelines (Airflow) for data ingestion and cleaning. You will be responsible for curating balanced training sets and generating synthetic data to address both quality and diversity gaps. Production Engineering: Own the path to production. Optimize models for low-latency inference (quantization, distillation, TensorRT/ONNX) and manage deployment on AWS. Mentor ML engineers, conduct code/design reviews, and drive technical best practices across the Computer Vision team. What We’re Looking For Experience: 5+ years of industry experience in Machine Learning, with at least 3 years dedicated to Biometrics or Face Analysis. Deep expertise in computer vision and biometrics, especially face recognition. Fairness & Ethics: You understand the sources of algorithmic bias in Computer Vision and have practical experience measuring and mitigating disparate impact. Strong Engineering: Expert proficiency in Python (both machine learning and vision libraries such as Pillow, OpenCV, PyTorch, etc). You write clean, modular, production-ready code. Systems Architecture: Experience designing end-to-end ML pipelines (Data to Train to Deploy) and working with workflow orchestrators like Airflow. Cloud Native: Hands-on ex

Machine Learning Engineer IV – (Computer Vision) We’re looking for a Staff/Senior Machine Learning Engineer with deep expertise in computer vision and biometrics to lead the design and scaling of face recognition systems in production. You’ll build and train models, and own ML systems end-to-end on AWS. The final job level for this role will be determined following the interview process. What You’ll Do Lead the design and development of computer vision systems for biometrics (face attributes, detection, quality, and recognition) Rigorous fairness analysis and benchmarking of biometric models across various datasets and operating conditions. Architect, train, and optimize models using PyTorch, Tensorflow, and/or JAX Own and evolve end-to-end ML pipelines, from data ingestion to deployment. Design automated pipelines (Airflow) for data ingestion and cleaning. You will be responsible for curating balanced training sets and generating synthetic data to address both quality and diversity gaps. Production Engineering: Own the path to production. Optimize models for low-latency inference (quantization, distillation, TensorRT/ONNX) and manage deployment on AWS. Mentor ML engineers, conduct code/design reviews, and drive technical best practices across the Computer Vision team. What We’re Looking For Strong industry experience in Machine Learning, dedicated to Biometrics or Face Analysis. Deep expertise in computer vision and biometrics, especially face recognition. Fairness & Ethics: You understand the sources of algorithmic bias in Computer Vision and have practical experience measuring and mitigating disparate impact. Strong Engineering: Expert proficiency in Python (both machine learning and vision libraries such as Pillow, OpenCV, PyTorch, etc). You write clean, modular, production-ready code. Systems Architecture: Experience designing end-to-end ML pipelines (Data to Train to Deploy) and working with workflow orchestrators like Airflow. Cloud Native: Hands-on exper