Inference Technical Lead in India

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. Okta’s Workforce Identity Cloud Security Engineering group is looking for an experienced and passionate Staff Site Reliability Engineer to join a team focused on designing and developing Security solutions to harden our cloud infrastructure. We embrace innovation and pave the way to transform bright ideas into excellent security solutions that help run large-scale, critical infrastructure. We encourage you to prescribe defense-in-depth measures, industry security standards and enforce the principle of least privilege to help take our Security posture to the next level. Our Infrastructure Security team has a niche skill-set that balances Security domain expertise with the ability to design, implement, rollout infrastructure across multiple cloud environments without adding friction to product functionality or performance. We are responsible for the ever-growing need to improve our customer safety and privacy by providing security services that are coupled with the core Okta product. This is a high-impact role in a security-centric, fast-paced organization that is poised for massive growth and success. You will act as a liaison between the Security org and the Engineering org to build technical leverage and influence the security roadmap. You will focus on engineering security aspects of the systems used across our services. Join us and be part of a company that is about to change the cloud computing landscape forever. Bring all the passion and dedicat

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. Okta’s Workforce Identity Cloud Security Engineering group is looking for an experienced and passionate Staff Site Reliability Engineer to join a team focused on designing and developing Security solutions to harden our cloud infrastructure. We embrace innovation and pave the way to transform bright ideas into excellent security solutions that help run large-scale, critical infrastructure. We encourage you to prescribe defense-in-depth measures, industry security standards and enforce the principle of least privilege to help take our Security posture to the next level. Our Infrastructure Security team has a niche skill-set that balances Security domain expertise with the ability to design, implement, rollout infrastructure across multiple cloud environments without adding friction to product functionality or performance. We are responsible for the ever-growing need to improve our customer safety and privacy by providing security services that are coupled with the core Okta product. This is a high-impact role in a security-centric, fast-paced organization that is poised for massive growth and success. You will act as a liaison between the Security org and the Engineering org to build technical leverage and influence the security roadmap. You will focus on engineering security aspects of the systems used across our services. Join us and be part of a company that is about to change the cloud computing landscape forever. As a Staff Engineer, you should be able

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. Okta’s Workforce Identity Cloud Security Engineering group is looking for an experienced and passionate software security engineer to join a team focused on designing and developing Security solutions to harden our frameworks & infrastructure. We embrace innovation and pave the way to transform bright ideas into excellent security software solutions that help run large-scale, mission-critical software. We encourage you to prescribe defense-in-depth measures, industry security standards, enforce the principle of least privilege to help take our Security posture to the next level. Our Security engineering team has a niche skill-set that combines Security domain expertise with the ability to design, implement and rollout security features and functionalities without adding friction to product functionality or performance. We are responsible for the ever-growing need to improve our customer safety and privacy by providing security services that are coupled with the core Okta product. This is a high-impact role in a security-centric, fast-paced organization that is poised for massive growth and success. You will act as a liaison between the Security org and the engineering org to build technical leverage and influence the security roadmap and direction. You will focus on engineering security and privacy aspects of the systems used across our services while working on a weekly release cadence. You will be empowered to propose stimulating new

About Us Oliv.AI is a SalesTech global startup headquartered in San Francisco, debuting the world's first team of AI Agents for sales. With our recent $5.2M Seed funding, we solve one of the biggest problems for revenue teams: unreliable deal data. Oliv captures Deal Intelligence from every meeting, call, and email—without any rep involvement. The result is a clear, detailed view of every deal, presented in scorecards built on trusted sales methodologies like MEDDICC, BANT, and SPICED. Our AI agents are built for sales teams—sales managers, AEs, and RevOps—handling the work that takes them away from selling. With Oliv AI, sales teams can bring back focus on deals, strategy and conversation. The role This is not a traditional marketing role, and it is not a pure engineering role either. You will decide which accounts matter, build the systems that research them, write the content that reaches them, build the partnerships that amplify it, and turn all of that into qualified pipeline. Two things have to be true about you at once. You are technically sharp enough to build your own workflows, wire up your own APIs, and ship a working system without waiting on engineering or anyone else. Nothing you own should be blocked on a single person, including us. And you are obsessed with distribution — content, syndication, social, and partnerships — because pipeline goes to whoever the buyer already trusts. That means newsletters, communities, podcasts, comparison pages, partner audiences, and the people who influence them. What you will own GTM strategy and experimentation Develop and continuously refine Oliv's ICP, market segments, buyer personas, and account-selection criteria. Translate company goals into specific growth hypotheses and campaign plans. Identify new audiences, buying signals, use cases, and distribution opportunities. Build a structured experimentation roadmap across content, social, syndication, partnerships, outbound, and ABM. Define success metric

Client Onboarding Manager – Inference & Agentic AI | Paytm (Noida) About the Role Paytm is a pioneer of digital payments in India, serving over 450 million consumers and 45 million merchants across payments, financial services, and commerce. Over the years, Paytm has built deep in-house capabilities across technology, data, and operations to operate at scale with high reliability. Paytm is building a full stack AI platform focussed on Inference and Agents, enabling large enterprises to deploy AI driven automation across sales, service, operations, and analytics. The Inference and Agentic AI team operates as a cross functional unit spanning engineering, product, data science, business management, and sales, and owns the full lifecycle of AI solutions from opportunity discovery to deployment and scale. Key Responsibilities Own client onboarding from sales handover to go-live. Understand client workflows, systems, and integration requirements. Coordinate with Product, Engineering, and Client teams for seamless deployment. Manage onboarding timelines, milestones, and stakeholder communication. Conduct client training sessions and drive product adoption. Track onboarding KPIs, client satisfaction, and implementation success. Gather client feedback and support continuous product improvements. Ideal Candidate 2–5 years of experience in Client Onboarding, Implementation, Customer Success, or Solutions Engineering. Experience in SaaS, Fintech, Enterprise Technology, or AI products preferred. Good understanding of APIs, integrations, CRM systems, and enterprise workflows. Strong project management, problem-solving, and stakeholder management skills. Excellent communication and client-facing abilities. Bachelor’s degree in Engineering, Business, or related field. Location: Noida Why Join? Be part of Paytm’s fast-growing AI business and work closely with enterprise clients to deliver cutting-edge AI-driven automation solutions at scale.

About Paytm Paytm is a pioneer of digital payments in India, serving over 450 million consumers and 45 million merchants across payments, financial services, and commerce. Over the years, Paytm has built deep in-house capabilities across technology, data, and operations to operate at scale with high reliability. Paytm is building a full stack AI platform focussed on Inference and Agents, enabling large enterprises to deploy AI driven automation across sales, service, operations, and analytics. The Inference and Agentic AI team operates as a cross functional unit spanning engineering, product, data science, business management, and sales, and owns the full lifecycle of AI. Role Overview Paytm is looking to hire Sales Operations Managers to drive financial and operational rigor across its AI Inference and Agentic AI business. This role sits at the core of sales operations, working closely with sales, business management, and central finance teams to ensure accurate billing, collections, and revenue recognition. The role involves owning the full order to cash lifecycle, strengthening revenue assurance, and managing procurement and vendor operations for the AI charter. The candidate will play a key role in building scalable, audit ready systems that improve financial control, reduce leakage, and enable efficient business growth. Key Responsibilities Order to Cash Operations Own end to end invoicing for enterprise AI deals from contract trigger to invoice generation, dispatch, and acknowledgement. Maintain a central invoicing tracker covering deal terms, billing milestones, invoice status, and collections. Coordinate with central finance and accounts receivable teams to ensure GST compliant, PO aligned, and accurately booked invoices. Drive collections follow ups with enterprise clients in partnership with business teams and escalate overdue receivables. Manage billing adjustments including credit notes, disputes, and corrections. Revenue Assurance and Financial Co

About Paytm Paytm is a pioneer of digital payments in India, serving over 450 million consumers and 45 million merchants across payments, financial services, and commerce. Over the years, Paytm has built deep in-house capabilities across technology, data, and operations to operate at scale with high reliability. Paytm is building a full stack AI platform focussed on Inference and Agents, enabling large enterprises to deploy AI driven automation across sales, service, operations, and analytics. The Inference and Agentic AI team operates as a cross functional unit spanning engineering, product, data science, business management, and sales, and owns the full lifecycle of AI solutions from opportunity discovery to deployment and scale. Role Overview Paytm is looking to hire an Enterprise GTM Lead to own the go to market charter for Paytm’s AI Inference and Agentic AI products across enterprise clients. This is a managerial role that will lead business managers and client onboarding managers, and will work closely with enterprise sales teams to drive pipeline, deal conversion, onboarding, and client success. The role sits at the center of Paytm’s enterprise AI charter and involves shaping GTM strategy, enabling sales teams, supporting client pitches, structuring commercials, and ensuring strong post sale execution. The candidate will be responsible for building a repeatable enterprise sales motion for Paytm AI agents, including Pi Commerce and future AI products. The role requires strong commercial judgment, enterprise stakeholder management, execution discipline, and ability to work across sales, product, technology, finance, and marketing teams. Key Responsibilities Enterprise GTM Strategy and Business Ownership Own the enterprise GTM strategy for Paytm AI agents across existing and new enterprise clients. Build and execute sales enablement, pipeline generation, deal conversion, onboarding, and account expansion plans. Work with leadership to define target segme

About the Role REMOTE IN INDIA We're looking for a software engineer to build the Kubernetes-native control plane that provisions and runs our GPU inference fleet. You'll design a manifest-driven API where the inference team declares what they need, whether that's a cluster, a model deployment, or a capacity change, and our controllers handle the reconciliation, provider/runtime selection, and lifecycle management underneath, so the inference team never has to know or care which specific serving stack, scheduler, or hardware pool is doing the work. You'll also build the systems that keep the fleet efficient, not just running, including defragmentation and rebalancing logic that consolidates scattered workloads back into contiguous capacity, and scheduling/bin-packing improvements that push GPU utilization up without hurting latency. The core value we're after is decoupling the people building on top of the platform from the operational and runtime complexity underneath, while squeezing more usable capacity out of the same hardware. You'll build the controllers, reconciliation loops, and self-service surface (API/CLI, not tickets) that make that decoupling real, plus the event-driven health, remediation, and utilization systems that keep it running and efficient without a human in the loop. Strong candidates have hands-on experience with Kubernetes controller/CRD patterns, have built or operated a platform API that abstracts multiple backends behind one interface, understand GPU scheduling and capacity efficiency (fragmentation, bin-packing, right-sizing), and think about GPU infrastructure as software to be engineered. A product mindset - you've built internal platforms or APIs consumed by other engineering teams and care about the developer experience of what you ship. You build it, you own it. You are not only responsible for delivering the software but also for operating and supporting it in production. Responsibilities Build the provisioning state machine

Marketing Director- Paytm (Inference and Agentic AI) Location: Noida Company: Paytm About Paytm: Paytm is a pioneer of digital payments in India, serving over 450 million consumers and 45 million merchants across payments, financial services, and commerce. Over the years, Paytm has built deep in-house capabilities across technology, data, and operations to operate at scale with high reliability. Paytm is building a full stack AI platform focussed on Inference and Agents, enabling large enterprises to deploy AI driven automation across sales, service, operations, and analytics. The Inference and Agentic AI team operates as a cross functional unit spanning engineering, product, data science, business management, and sales, and owns the full lifecycle of AI solutions from opportunity discovery to deployment and scale. Role Overview: Paytm is looking to hire a Marketing Director to own B2B marketing, demand generation, product marketing, and sales enablement for Paytm’s Inference and Agentic AI products. This is a managerial role that will lead a team of marketing managers and drive marketing across enterprise clients and mid market merchants. The role will be responsible for building market presence, qualified pipeline, product launches, agentic marketing initiatives, and sales enablement programs across Paytm AI products including Pi Commerce and future AI agents. The candidate will own positioning, messaging, GTM communication, lead generation, demand generation, account engagement, and customer marketing across digital, offline, and agentic channels. The role requires strong B2B SaaS marketing experience, product marketing judgment, demand generation depth, team leadership, and ability to convert AI product capabilities into clear business value. Key Responsibilities Own end-to-end marketing strategy for Paytm AI products across Enterprise and Mid-Market segments. Drive demand generation through digital campaigns, webinars, events, ABM, content, and partne

About the Role At Together AI, you’ll build and operate one of the world’s largest GPU fleets used for frontier model training and inference. This isn’t a traditional infrastructure role—we’re looking for engineers who love building systems, automating everything, and solving problems at massive scale. If you enjoy writing software more than clicking dashboards, obsess over eliminating manual work, and want to build infrastructure that manages tens of thousands of GPUs autonomously, we’d love to talk. Responsibilities Design and build fleet automation systems that provision, validate, deploy, upgrade, repair, and retire GPU clusters with minimal human intervention. Build AI Infrastructure Agents that automate deployment, root-cause failures, incident triage, and autonomous remediation. Develop Fleet Intelligence platforms that continuously monitor hardware health, firmware, networking, storage, thermals, and workload performance to predict failures before they impact customers. Build software that maximizes GPU availability, utilization, performance, and reliability across thousands of accelerators. Create automated validation systems for GPUs, InfiniBand/RoCE fabrics, NVLink/NVSwitch, storage, and distributed AI workloads. Build internal platforms and developer tools that allow infrastructure to be managed through software—not manual operations. Continuously improve deployment velocity, reliability, and operational efficiency through automation. Partner closely with hardware, networking, platform, and AI teams to push the limits of AI infrastructure. Requirements 3+ years building distributed systems, infrastructure platforms, or large-scale backend software. Strong software engineering skills in Python, Go, or Rust . Experience building platforms, automation systems, or developer infrastructure. Experience with Linux, Kubernetes, Terraform, Ansible, or similar infrastructure technologies. Strong systems thinking with the ability to understand problems across hardw

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

Role Purpose: At Jumio, you will work for one of the market leaders in the global identity verification space that is helping to make the digital world a safer place for everyone. As a Software Development Engineer in the MLOpsTeam, you will develop the blueprint for highly scalable and performant ML model serving. Role Value: As a Software Engineer (SDE III), you will drive the continuous improvement of the infrastructure and applications to manage the lifecycle of ML assets (data, models) to better developer experience and strengthen governance capabilities. Secondly, you will design and implement robust ML infrastructure for model deployment, serving, and optimization. You will work on efficient CI/CD pipelines for ML models and leverage advanced compilers or hardware optimization to maximize inference performance while optimizing costs. We welcome you to challenge us to impact our software development processes and tools. Example Responsibilities: Upgrade ML assets (models, data) management systems for better developer experience and robust governance capabilities Build and optimize model serving infrastructure with a focus on inference latency and cost optimization Architect efficient inference pipelines that balance latency, throughput, and cost across various acceleration options Implement cost-efficient, enterprise-scale solutions Collaborate in a cross-functional, distributed team for continuous system improvement Work with MLEs, QA Engineers, and DevOps Engineers Evaluate and implement new technologies and tools Contribute to architectural decisions for distributed ML systems Experience and Qualifications : 5+ years of experience in software engineering with Python Experience with model lifecycle management (MLFlow, Weights & Biases or equivalent) Experience with data management ecosystem (quality, transformation, catalog) Experience with ML frameworks, particularly PyTorch Experience optimizing ML models with hardwar

Role: VPN 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. Responsibilities Manage and support corporate network infrastructure across multiple locations, including routers, firewalls, switches, wireless access points, VPN gateways, Internet links, and LAN/WAN connectivity. Configure and troubleshoot VPN technologies such as IPsec, SSL VPN, site-to-site VPN, remote-access VPN, WireGuard, OpenVPN, and FortiClient/FortiGate VPN, including issues related to authentication, tunnels, routing, DNS, packet loss, performance, split tunnelling, and firewall policies. Manage secure connectivity between offices, data centres, cloud environments, and remote users. Configure and maintain office LAN infrastructure, including VLANs, trunk/access ports, inter-VLAN routing, DHCP, DNS, NAT, ACLs, static routing, BGP, and OSPF where required. Manage multiple ISP connections, including primary and backup Internet links, automatic failover, and monitoring of utilization, latency, jitter, packet loss, and link availability. Coordinate with ISPs and telecom providers for new circuits, link failures, bandwidth upgrades, routing issues, packet-loss investigations, and service escalations. Manage firewall policies, NAT rules, VPN policies, network objects, and routing, while regularly reviewing and removing unnecessary access. Implement network segmentation across user, server, management, guest, and other business networks, while maintaining secure administrative access to network equip

Description: Graviton is a privately funded quantitative trading firm striving for excellence in financial markets' research. We are seeking a Quant Analyst - Risk for our team in Gurugram. 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. As a Quant Analyst - Risk you will be responsible Work as a team with senior traders to operate and implement/improve our automated trading strategies. Analysing production trades and developing ideas to improve our trading strategies. Implement monitoring tools which highlight potential issues in the production strategies. Write comprehensive and scalable scripts in both C++ and python analysing production strategies for risk attribution, performance break-ups along various buckets and so on. Build ‘cool’ scalable post-trade systems analysing multitude of statistics across all production strategies. Implementing tools for analysing Market Data centrally across various exchanges. Managing deployments and release cycle, with working along with a senior trader. Requirements : Possess a degree in a highly analytical field, such as Engineering, Mathematics, or Computer Science from top-ranked universities 3+ years of experience in Python, Shell/Bash scripting. Basic knowledge of Linux and shell command-line tools Basic programming and scripting (Python/Shell) skills Strong problem-solving, and analytical skills Excellent communication skills Have a strong work ethics Mentorship experience in guiding junior developers. Benefits: Our open and collaborative work culture gives you the freedom to innovate and experiment. Our cubicle free offices, non-hierarchical work culture and insistence to hire the very best creates a melting pot for great idea

Who are we: Graviton is a privately funded quantitative trading firm striving for excellence in financial markets research. We trade 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 analyzing terabytes of data to come up with ideas to identify pricing anomalies in financial markets. As part of this team you will be tasked to apply machine learning and specifically deep learning techniques to trading problems while staying connected to broader research community. The researcher will put theory into practice and can immediately impact the global trading landscape with the expanding presence of Graviton in various markets. Description Lead research in applying machine learning to a wide variety of datasets and trading problems Follow latest developments in academic research and incorporating research techniques from different fields of applications to our problems Improve tick-by-tick order book based time series feature sets using latest preprocessing techniques Work on current and develop new deep learning models to exploit large pool of in-house features and computing infrastructure Develop scalable pipeline for building predictive models across global markets Discover and implement new sources of predictive alpha, verify that they improve existing models, and integrate them into the firm's strategy development pipeline Partner with quant researchers and software developers in implementation of conducted research to production using Python / C++ Advise infrastructure support team on latest developments on hardware and software to improve computing infrastructure for ML based research Qualifications Masters or PhD in Computer Science, Mathematics, Statistics, or a related field At least two years of demonstrated experience of ML/AI research in a professional setting or at a repu