Ai Ml Dev in India

Role Summary The AI Knowledge Analyst is a member of the Customer Care and Managed Services team, responsible for ensuring the knowledge ecosystems that power GHX's operations and AI platforms are accurate, well-governed, and continuously improving. This role works closely with leadership, SMEs, data scientists, and operational teams to identify content gaps, manage knowledge lifecycles, and translate business needs into structured, AI-ready information assets. The AI Knowledge Analyst is equally comfortable working through a detailed content audit and presenting a structured recommendation to leadership. Strong organizational skills, clear communication, and a bias for action are required. This is a role for someone who treats knowledge gaps as solvable problems and can move from gap identification to resolution with minimal direction. Core Focus Areas Knowledge Governance & Lifecycle Management Maintain, organize, and govern the knowledge assets that support Customer Care and Managed Services teams. This includes managing intake, triage, and routing of knowledge requests; driving SME review cycles; and ensuring content is accurate, current, and ready for both human use and AI ingestion. AI Knowledge Readiness Identify, structure, and groom content that feeds GHX's AI platform. Partner with AI and data teams to ensure knowledge assets are formatted, accurate, and optimized for ingestion. Monitor AI solution performance and drive content improvements that translate into measurable efficiency gains. Roles & Responsibilities Knowledge Management & Content Quality Manage the intake, triage, and routing of knowledge-related requests from operational teams. Maintain content lifecycle through SME review checkpoints — flagging material for update, review, or archival on a consistent cadence. Identify obsolete, duplicate, or conflicting content and drive resolution through appropriate stakeholders. Conduct knowledge audits and implement improvement c

Job Details: Job Description: The Role and Impact As a Development Tools Software Engineer, you will play a vital role in creating and optimizing cutting-edge software tools that support diverse engineering domains such as design, manufacturing, validation, silicon production, systems integration, and ecosystem enabling. On a day-to-day basis, you'll design, develop, debug, and validate algorithms, tools, and systems that empower internal and external engineering teams to deliver impactful products. Your contributions will directly enable the seamless integration of Intel silicon and software into innovative solutions, driving progress across industries. Business group You will join Intel Corporation, a leading global technology company dedicated to advancing semiconductor innovation and creating solutions that enrich the lives of people worldwide. The team focuses on developing robust software tools and methodologies that support Intel's engineering ecosystem, fostering excellence and driving high-quality results. This group plays a critical role in enabling Intel's broader mission of building world-class technologies and products that power the future of the digital world. Key Responsibilities - Design and implement software tools using modern software development methodologies and programming languages. - Debug, validate, and optimize algorithms and software systems for engineering applications, ensuring high performance and reliability. - Collaborate with cross-functional teams to create solutions that enable seamless integration of Intel silicon and software into impactful products. - Utilize secure coding practices to ensure the robustness and security of software tools across various engineering domains. - Continuously explore innovative solutions to enhance design, manufacturing, validation, and testing processes. <p st

Job Details: Job Description: Intel's Design Quality and Reliability organization is seeking an AI Platform Engineer to architect and build an enterprise-grade AI platform for mission-critical engineering work. This platform will enable Intel engineers to analyze complex design, qualification, and reliability data; automate engineering workflows; access organizational knowledge; and make faster, evidence-based decisions throughout the product lifecycle. The successful candidate will combine strong software engineering fundamentals with expertise in AI-native and agentic development. They will be highly proficient with Agentic AI coding assistants and able to use these tools responsibly to accelerate architecture, implementation, testing, debugging, and documentation. This role requires close collaboration with Design, Quality and Reliability, Product Engineering, Manufacturing, IT, Information Security, and other Intel stakeholders. Responsibilities 1. Architect and develop Intel's reusable AI platform for Design Quality and Reliability. 2. Build AI agents and workflows for engineering data analysis, qualification planning, risk assessment, knowledge retrieval, reporting, and process automation. 3. Apply Agentic AI coding assistants to accelerate software development while maintaining rigorous engineering review and validation. 4. Integrate AI capabilities with Intel engineering databases, quality-management systems, internal APIs, spreadsheets, documentation repositories, and workflow tools. 5. Develop production-grade backend services, APIs, data pipelines, model gateways, and agent-orchestration components. 6. Establish shared platform capabilities for identity, access control, tool authorization, memory, observability, evaluation, and auditability. 7. Implement human approval, deterministic validation, and rollback controls for consequential engineering actions. 8.

We are a global team of innovators and pioneers dedicated to shaping the future of observability. At New Relic, we build an intelligent platform that empowers companies to thrive in an AI-first world by giving them unparalleled insight into their complex systems. As we continue to expand our global footprint, we're looking for passionate people to join our mission. If you're ready to help the world's best companies optimize their digital applications, we invite you to explore a career with us! Your opportunity AI is a top strategic priority for New Relic, and the Bengaluru design team is at the center of it. The team works across three closely related product clusters: autonomous incident response (SRE Agent, Autopilot, and Intelligent RCA), the intelligence and platform layer that powers them (Ground Truth, Agentic Platform, and New Relic AI), and AIOps for event correlation and incident management. These products share a common design challenge: users need to trust systems that act autonomously, and building that trust through good design is genuinely hard work. This is an on-site role in Bengaluru. Your designers are there, and many of your engineering and product partners are too. Being present — in standups, reviews, and the quick conversations before a decision gets made — is part of how you'll build the relationships that make design effective. You'll also collaborate with design, product, and engineering partners in the US and Spain, so operating across time zones and communicating well in writing are part of the job. You'll manage a small team of designers and own the quality of the work across these products. The design questions here don't have established answers — how do you make an autonomous system legible? How do you build user trust in AI-generated root cause analysis? How do you design a handoff from machine decision to human judgment? If you're already working in AI product design, or actively building toward it, and you want to lead a team

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

AI Tech Lead – Manager Experience- 8-12 years Job Overview: We are seeking a highly experienced AI Tech Lead to design, develop, and deliver scalable AI-driven applications while leading cross-functional teams. The role involves end-to-end ownership of AI solutions, including architecture design, deployment, and optimization, ensuring alignment with business objectives. The candidate will collaborate with stakeholders, data engineering teams, and product management to build enterprise-grade AI systems leveraging modern cloud and AI technologies. Key Responsibilities / (Person Specifications): Lead implementation and delivery of AI applications across teams. Design end-to-end AI architectures integrating open-source and enterprise tools. Translate business requirements into scalable AI solutions. Define architecture roadmaps and best practices. Build data pipelines, CI/CD, and monitoring systems. Deploy scalable systems using Docker and Kubernetes. Ensure performance, scalability, and security. Mentor teams and drive knowledge sharing. Key Skills / Job Specifications (Mandatory): AI frameworks: LangGraph, AutoGen, CrewAI. Strong Python with TensorFlow, PyTorch, Keras. Knowledge of NLP & Deep Learning (RNN, CNN, LSTM, Transformers). Cloud platforms: AWS / Azure / GCP. Docker, Kubernetes, CI/CD tools. Terraform / CloudFormation (IaC). SQL & NoSQL databases. Distributed systems, REST APIs, GraphQL, microservices.

Roles and Responsibilities Building templates, dashboards in Excel /Google Sheet / PowerBI for operational and management reporting Statistical and Analytical Models and methods for data analysis related to customer initiatives & growth hacks including issue diagnosis, problem dissection and tracking of results Running and maintaining the reporting system Data extraction as per business request for Ad hoc analysis Assisting the team in data analysis and mining Business analysis and understanding to highlight key lead indicator Qualifications & Experience Bachelors in Engineering, Computer Science, Math, Statistics, or related discipline from a reputed institute or an MBA from a reputed institute 2+ years of experience in working on reporting / business intelligence systems Strong database concepts and experience in SQL – can convert any business requirement into a SQL statement Expertise in Excel, PowerBI Working experience in R, Python, Tableau, QlikView, Data studio is a good to have Experience of working in a customer growth/customer analytics role is a plus Quick learner and ability to work in dynamic work environment Team player and comfortable interacting with people from multiple disciplines

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

MeltPlan is building the “planning engine” for the $14 Tn construction industry, an AI system designed specifically to optimize decisions before construction begins. While design software optimizes use and aesthetics and construction software optimizes execution and control, MeltPlan is building the missing layer - software that optimizes decisions and tradeoffs upstream, before scope is locked, procurement begins, and change orders become inevitable. MeltPlan’s long-term goal is to help teams make construction “boring” by making planning more intense: surfacing constraints and tradeoffs early, aligning stakeholders before plans are frozen, and reducing the need for late-stage redlines, rework, and change orders. MeltPlan is founded by operators who have built at scale. Kanav previously co-founded Innovaccer, a $3Bn healthtech company focused on making US healthcare more affordable and accessible. He’s now applying that systems-level thinking to construction.He’s joined by Tanmaya Kala, former Project Executive at DPR Construction, who led large commercial, healthcare, and life sciences projects. We combine deep tech scale with real construction execution. What This Role Really is : We are seeking a detail-oriented and technically strong AI QA Engineer to ensure the quality, reliability, and performance of Large Language Model (LLM)-based systems. In this role, you will be responsible for designing and executing test strategies, validating model outputs, and building evaluation frameworks to enhance the accuracy, safety, and overall performance of AI-driven applications.We would particularly value candidates who have hands-on experience in developing evaluation frameworks (evals) for AI systems, along with strong expertise in comprehensive system testing and quality assurance practices.You are responsible for making MeltPlan work in the real world. What You'll Do: Design, develop, and execute evaluation frameworks (Evals) for Large Language Models (LLMs) and AI syst

MeltPlan | Planning Engine for the Built Environment MeltPlan is building the “planning engine” for the $14 Tn construction industry, an AI system designed specifically to optimize decisions before construction begins. While design software optimizes use and aesthetics and construction software optimizes execution and control, MeltPlan is building the missing layer - software that optimizes decisions and tradeoffs upstream, before scope is locked, procurement begins, and change orders become inevitable. MeltPlan’s long-term goal is to help teams make construction “boring” by making planning more intense: surfacing constraints and tradeoffs early, aligning stakeholders before plans are frozen, and reducing the need for late-stage redlines, rework, and change orders. MeltPlan is founded by operators who have built at scale. Kanav previously co-founded Innovaccer, a $3Bn healthtech company focused on making US healthcare more affordable and accessible. He’s now applying that systems-level thinking to construction.He’s joined by Tanmaya Kala, former Project Executive at DPR Construction, who led large commercial, healthcare, and life sciences projects. We combine deep tech scale with real construction execution. What This Role Really Is We are looking for an AI Research Scientist – Computer Vision to enhance and manage the PlanGraph model, which transforms 2D drawings into structured graphical representations of building elements. The role involves solving downstream business use cases such as quantity takeoff, code compliance, value engineering, and constructability analysis.We are specifically looking for hands-on researchers with experience in solving real-world Computer Vision problems and building custom vision models, VLMs, or VLLMs for production-grade applications. What You’ll Do Build and optimize custom Computer Vision models, VLMs, and VLLMs for construction intelligence workflows. Solve downstream business use cases including quantity takeoff, code complianc

About Dialpad Dialpad is the AI platform for customer experience, built to resolve customer problems in real time across voice and digital. Our AI agents learn from your best human agents and improve with every interaction, helping organizations understand their customers, deliver better experiences, increase operational efficiencies, and build a lasting competitive advantage. Unlike legacy systems built to route and answer, or standalone agentic bot vendors built to deflect, Dialpad was built to resolve. Our AI agents and human agents operate on a single platform with shared context, allowing Agentic AI to resolve issues, advance deals, and eliminate busywork through automation while seamlessly handing conversations to humans when needed, with full context preserved. Market-leading brands, including Randstad, Motorola Solutions, Netflix, the San Diego Padres, the Colorado Rockies Baseball Club, and Cal Athletics, trust Dialpad. Dialpad is backed by Andreessen Horowitz, GV, ICONIQ Capital, and T-Mobile. Being a Dialer At Dialpad, AI isn’t just a feature; it’s how our teams do their best work every day. We put powerful AI tools in every employee’s hands so they can move faster, think bigger, and achieve more. We believe every conversation matters. And we’ve built the platform that turns those conversations into insight and action, for our customers and ourselves. We look for people who are intensely curious and hold themselves to a high bar. Our ambition is significant, and achieving it requires a team that operates at the highest level. We seek individuals who embody our core traits: Scrappy, Curious, Optimistic, Persistent, and Empathetic . Your role As an AI Engineer, the selected candidate will build and ship AI-powered tools alongside a small, technically focused team. This is a hands-on engineering role: the candidate will write Python, work with LLMs and agent frameworks, integrate APIs, and help deploy systems that real business teams depend on. Guidance will

About Glean: Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry’s most advanced enterprise search has evolved into a full-scale Work AI ecosystem, powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean gives organizations the infrastructure to govern, scale, and customize AI across their entire business - without vendor lock-in or costly implementation cycles. At its core, Glean is redefining how enterprises find, use, and act on knowledge. Its Enterprise Graph and Personal Knowledge Graph map the relationships between people, content, and activity, delivering deeply personalized, context-aware responses for every employee. This foundation powers Glean’s agentic capabilities - AI agents that automate real work across teams by accessing the industry’s broadest range of data: enterprise and world, structured and unstructured, historical and real-time. The result: measurable business impact through faster onboarding, hours of productivity gained each week, and smarter, safer decisions at every level. Recognized by Fast Company as one of the World’s Most Innovative Companies (Top 10, 2025), by CNBC’s Disruptor 50, Bloomberg’s AI Startups to Watch (2026), Forbes AI 50, and Gartner’s Tech Innovators in Agentic AI, Glean continues to accelerate its global impact. With customers across 50+ industries and 1,000+ employees in more than 25 countries, we’re helping the world’s largest organizations make every employee AI-fluent, and turning the superintelligent enterprise from concept into reality. If you’re excited to shape how the world works, you’ll help build systems used daily across Microsoft Teams, Zoom, ServiceNow, Zendesk, GitHub, and many more - deeply embedded where people get things done. You’ll ship agentic capabilities on an open, extensible stack, with the craf

AI Software Engineer, Agent Harness Location: Bengaluru, Karnataka (or throughout India remote-friendly with travel) About EnCharge AI EnCharge AI is building the next generation AI platform. Our novel in-memory-computing architecture delivers a 10x step-function improvement in compute energy efficiency and performance for AI inference workloads. As the demands of artificial intelligence move beyond today's models, we believe fundamental underlying infrastructure must evolve. We are an experienced team of AI researchers, silicon & systems engineers, and architects backed by leading investors, poised to become the essential platform for the next wave of AI innovation. The Opportunity We serve open-weight models and our own bespoke checkpoints on EnCharge hardware. The models change often, and the harness around them needs to keep up. You own this layer that runs agents against files, tools, documents with permissions, memory, unattended execution, and real outputs. It will be assembled from a combination of open-source and bespoke code. Key Responsibilities Own the harness architecture end to end — agent loop, safe execution, context management, knowledge base, memory, permissions, orchestration, outputs, interfaces, observability — one component per layer, with clear interfaces so layers can be swapped. Build the pieces with no open-source equivalent e.g. session semantics, enforced permissions, memory in a human-editable file, orchestrator, and outputs. Keep pace with the models: adapters, prompt formats, tool-call schemas, stop conditions, benchmarking and evaluation. Make tool use reliable across models of uneven tool-calling quality — validation, repair, retries, fallbacks. Develop agents, tools, and MCP servers for internal and customer use cases, and review them for security before they ship. Build the evaluation harness: task suites, regression runs on every model or harness change, cost and latency per task alongside quality. Define the interfaces:

Title: AI Application Packaging Engineer Location: Andheri (East), Mumbai Reports to: Service Director ABOUT BLENHEIM CHALCOT: As part of the Blenheim Chalcot portfolio, we benefit from the expertise, infrastructure, and scale of the leading global venture builder. With over 25 years of experience creating and growing SaaS businesses powered by Generative AI, Blenheim Chalcot has built 60+ ventures across sectors such as financial services, education, health, and marketing. Our global ecosystem—including Scale Space in London, the Rajasthan Royals in Mumbai, and a go-to-market base in Austin—enables us to access world-class talent, tools, and support to accelerate our growth and build a market-leading business. THE ROLE: We’re looking for an AI-first ITS Engineer with strong Application Packaging expertise to join our growing team at Agilisys. In this role, you’ll work across Application Packaging, Endpoint Management, Cloud Deployment, and Automation, helping modernise IT operations through AI-driven and scalable solutions. This is an opportunity to work in a fast-paced environment where automation, innovation, and operational efficiency are at the core of what we do. ABOUT YOU: Must-Have's 5+ years of hands-on experience with SCCM and/or Microsoft Intune for application packaging, deployment, and endpoint management. Strong experience with PowerShell scripting and a good understanding of Windows Registry, File System internals, and deployment workflows. Experience managing application packaging, deployment, patching, and remediation processes in enterprise environments. Exposure to vulnerability management and patch lifecycle activities using tools such as WSUS, Active Directory, or endpoint security solutions. An AI-first mindset with interest or experience leveraging Generative AI tools to improve efficiency across packaging, testing, deployment, troubleshooting, and operational tasks. Hands-on experience using automation or AI-assisted tools

About AlphaSense: The world’s most sophisticated companies rely on AlphaSense to remove uncertainty from decision-making. With market intelligence and search built on proven AI, AlphaSense delivers insights that matter from content you can trust. Our universe of public and private content includes equity research, company filings, event transcripts, expert calls, news, trade journals, and clients’ own research content. The acquisition of Tegus by AlphaSense in 2024 advances our shared mission to empower professionals to make smarter decisions through AI-driven market intelligence. Together, AlphaSense and Tegus will accelerate growth, innovation, and content expansion, with complementary product and content capabilities that enable users to unearth even more comprehensive insights from thousands of content sets. Our platform is trusted by over 6,000 enterprise customers, including a majority of the S&P 500. Founded in 2011, AlphaSense is headquartered in New York City with more than 2,000 employees across the globe and offices in the U.S., U.K., Finland, India, Singapore, Canada, and Ireland. Come join us! About the Role We are building an AI Security and Governance capability and need an AI Security Analyst to be the front line for detecting, investigating, and containing risk across every AI tool, agent, and model touching AlphaSense's environment. You will monitor enterprise AI usage end to end, hunt for unauthorized ("shadow") AI and rogue agent activity, and turn raw AI telemetry into triaged findings the security and governance team can act on. Working alongside the Automation Engineer, Data Analyst, and Director, you will be a primary contributor to the evidence base underpinning our ISO 42001 certification and our broader AI risk posture. Key Responsibilities AI Tool Discovery & Shadow AI Monitoring Continuously monitor CASB/SWG, OAuth, and endpoint telemetry to discover unsanctioned AI tools, browser extensions, and API-level agents in u