Model Designer in Bengaluru

Title: Senior AI QA Engineer Location: Bengaluru (Bangalore) Opportunity: As a Senior AI QA Engineer for our Precision Patient Care Pipeline , you will go beyond traditional functional testing. You will be responsible for building the framework that ensures our clinical insights are accurate, safe, and reliable. This role requires a unique blend of high-level software testing and data engineering to validate complex, non-deterministic medical outputs using a hybrid of automated grading methodologies . Key Responsibilities: Architect Multi-Layered Validation Frameworks: Design and implement structured testing strategies that combine deterministic checks, semantic similarity metrics, and model-based evaluations. Automated Model Grading: Develop systems to evaluate clinical pipeline outputs for faithfulness, safety, and hallucination detection using various automated scoring techniques (e.g., BERTScore, ROUGE, or custom heuristics). Vibe-Driven Development: Leverage agentic AI tools to rapidly prototype complex test harnesses, "red-team" clinical logic, and build internal validation utilities at high velocity. Data Pipeline Integrity: Execute integration and regression tests for data-heavy backend processes, ensuring medical data remains consistent from ingestion to insight generation. Collaborative Strategy: Work closely with Data Scientists and Product Managers to define "Ground Truth" datasets and clinical evaluation rubrics. Root Cause Analysis: Deep-dive into complex system failures to identify whether issues stem from code logic, data drift, or model behavior. Requirements: 6+ years of technical experience in Quality Assurance, with a strong focus on system architecture and backend data validation. Advanced Python Proficiency: Expert-level skills in Python for building custom test scripts and working within AI/ML ecosystems. AI/ML Validation Experience: Proven experience testing model outputs using diverse metrics (e.g., Semantic Similarity, NLP metrics, an

MongoDB is always developing and innovating — not only in our technology, but also in our sales go-to-market strategy. Our sales leadership is committed to building the best salesforce in technology. This means, inspiring and enabling success for everyone on the team. We not only equip you to be successful and close deals, but we want your feedback and input on how we can continue to “ Think Big and Go Far .” As a crucial part of the Sales team at MongoDB, you will have access to a lucrative market and learn how to sell from some of the most successful sales leaders in the software industry. We are looking to speak to candidates who are based in Gurugram for our hybrid working model. What you’ll be doing Sales strategy and execution: Develop and implement strategic sales plan to achieve revenue goals in the Public Sector with strong focus in State Government Relationship management: Build and maintain strong, long-term relationships with key Government Stakeholders - Senior Government Officials, Consultants, GSIs and Partners Business development: Identify new opportunities, generate leads, and pursue new government clients while also expanding business with existing ones Tender and proposal management: Work closely with Government Departments to make sure MongoDB is part of Tech Stack in tenders. Also to Monitor and respond to government tenders, RFPs, and RFQs, coordinating with internal teams to ensure timely and accurate proposal submissions Sales cycle management: Lead the sales process from lead generation and qualification through to contract negotiation and closure Performance and reporting: Set sales targets, monitor sales performance metrics, analyse market trends, and provide regular reports on activities and forecasts to senior management Internal collaboration: Work with internal teams, such as solution architects and delivery teams, to ensure seamless execution from contract award to delivery Internal Development: Participate in our sales enablement tr

About the Role Adobe is seeking a Machine Learning Engineer to join the Adobe Genuine Engineering team. This group protects Adobe's ecosystem from fraud, abuse, and misuse using intelligent systems worldwide. In this position, you will build and develop machine learning models from scratch, including custom transformer-based frameworks, to identify fraudulent actions, stop account sharing, and protect the experience of hundreds of millions of users. You will manage the entire model lifecycle: raw behavioral data and feature engineering, architecture development, large-scale GPU training, deployment, and monitoring. The team is actively building in-house behavioral foundation models that learn identity-preserving representations from long sequences of user activity. This is a role for an engineer who wants to own deep learning systems end-to-end — not consume pre-built ones. Key Responsibilities Build and train deep learning models from scratch, including custom transformer and attention-based architectures for long behavioral event sequences. Own the full training stack: event tokenization, temporal and positional embeddings, self-supervised pretraining (e.g., masked modeling, contrastive learning), and downstream fine-tuning. Train large models efficiently on GPU infrastructure using mixed-precision training, gradient accumulation/checkpointing, efficient attention, and distributed strategies (DDP, FSDP, or equivalent). Build and optimize feature pipelines on Databricks and Spark, transforming raw behavioral events into high-quality model inputs. Translate prototypes into production ML systems — scalable, reliable, and observable — and drive inference performance through architectural and serving-side optimization. Contribute to MLOps practices: experiment tracking, model versioning, CI/CD, automated retraining, and

NVIDIA Inception is our free global programme for start-ups building with AI, data science and accelerated computing — now more than 40,000 companies worldwide, with over 2,000 of them based in India alone. South Asia is one of the fastest-moving corners of that network: a market whose density sits in applied and vertical AI — medical imaging, drug discovery, edge vision, agentic and sovereign AI, robotics, agri-tech, AI governance — rather than in frontier model labs. We are looking for an Inception Regional Lead to own that motion end to end. This is a builder’s role with a commercial edge. You will set the regional strategy, lead a team of Inception Partner and Community managers across India, Bangladesh, Sri Lanka and neighbouring markets, and be personally accountable for how much NVIDIA hardware, software and cloud the region’s start-ups design in and consume. You will spend real time on the ground in founders’ offices, because that is where stalled accounts turn into concrete asks. And you will act as the connective tissue between start-ups and the rest of NVIDIA — worldwide field operations, solution architects, developer marketing, the reseller and cloud partner ecosystem, and NVentures. What you’ll be doing: Own the South Asia Inception strategy and number. Set regional priorities, coverage model and account tiering across strategic, member, community and prospect accounts; forecast and report on pipeline, design wins and consumption to programme and field leadership. Lead and grow the team. Manage, coach and develop a team of Inception Partner and community programme managers. Set territory and vertical coverage, run the operating cadence, and raise the bar on technical fluency and commercial rigour across the team. Drive commercial outcomes with start-ups. Move accounts from awareness to technical discovery to a named

Data Engineer Description - Key Roles Designs and establishes secure and performant data architectures, enhancements, updates, and programming changes for portions and subsystems of data pipelines, repositories or models for structured/unstructured data. Analyzes design and determines coding, programming, and integration activities required based on general objectives and knowledge of overall architecture of product or solution. Writes and executes complete testing plans, protocols, and documentation for assigned portion of data system or component; identifies and debugs, and creates solutions for issues with code and integration into data system architecture. Collaborates within a project team of other data engineers to develop reliable, cost effective and high-quality solutions for assigned data system, model, or component. Analyzes data inaccuracies, identifies opportunities and supports the development of automated solutions to enhance overall quality of the enterprise data. Identifies problematic areas and conducts research to determine the best course of action to correct the data; identifies, analyzes and interprets trends and patterns in complex datasets. Works cross-functionally with different departments to assess, define, and develop report deliverables. Represents the software data engineering team for all phases of larger and more-complex development projects. Provides guidance and mentoring to less experienced staff members. Education & Experience Recommended Four-year or Graduate Degree in Computer Science, Information Technology, Software Engineering, Statistics/ Mathematics, or any other related di

About Bolna Bolna is Voice AI infrastructure built for India - and now for the world. We help businesses deploy intelligent voice agents that can call, converse, and convert in any language, at scale. From collections to customer support to sales, our agents handle millions of conversations so humans don’t have to. We’re a YC F25 company, backed by General Catalyst, with 1,050+ paying customers and growing fast. Our team of ~25 is based in Bengaluru. The Role Every voice AI agent Bolna deploys makes real-time judgment calls - when to speak, when to go silent, when a customer is done talking, when to hand off. We’re building automated systems to grade these calls at scale, using LLMs as judges of call quality. But before you trust a model’s judgment, you verify it against a human’s. That’s this role. You’ll listen to real calls, annotate what actually happened, and check whether our automated systems - LLM-as-judge evals and quantitative signal detection - got it right. It’s precise, high-attention work, and it sits right at the center of how we know our voice agents are actually working. This is an internship role for someone early in their career who wants hands-on exposure to how a voice AI company builds trust in its own AI. What You’ll Do Annotation Listen to and annotate real customer calls - transcription review, issue tagging, labeling - using tools like Label Studio Follow (and help sharpen) annotation guidelines for a multilingual environment (Hindi, English, Hinglish, ) Verifying LLM-as-Judge Evaluations For calls flagged by our automated eval pipeline, verify whether the model’s call was actually correct - for example, confirming whether a detected barge-in (agent/customer talking over each other) genuinely happened by listening to the audio Mark agreements and disagreements clearly, with reasoning, so we can measure and improve model accuracy over time All tools needed for this will be provided Verifying Quantitative Measures Check system-flagged quantit

For over 20 years, Smartsheet has empowered teams to manage work seamlessly and scale solutions smarter. Now, in our most ambitious chapter yet, we are uniting human teams with AI agents. By orchestrating the work agents do best, automating manual tasks and uncovering insights at scale, we create the space for people to focus on what truly matters: judgment, creativity, and big thinking. That is magic at work, and it’s what we show up for every day. Job Description/ Responsibilities: Designing, developing and maintaining stable and reliable AI/ML Ops platforms / pipelines Model Deployment: Package and deploy AI/ML services to production, ensuring they are reproducible and interpretable CI/CD Pipeline Development: Design and implement automated CI/CD (Continuous Integration/Continuous Deployment) pipelines to accelerate model deployment using tools Infrastructure Management: Provision and optimize infrastructure for training and serving, utilizing Docker, Kubernetes, or serverless platforms Monitoring & Observability : Implement post-deployment monitoring for model performance, data drift, and latency using tools. Experience in Monte Carlo is preferable Automation: Automate retraining and data pipeline workflows to ensure models stay accurate over time. Manage the deployment of foundation models, fine-tuning workflows, and Retrieval-Augmented Generation (RAG) stacks (Vector DBs, Knowledge Graph. Experience with AWS Bedrock is preferable Resource Optimization: Manage GPU/CPU utilization to minimize cloud costs while maintaining low-latency inference for users Collaboration: Work closely with data scientists, data engineers, and software engineers to bridge the gap between model development and production. Version Control & Governance: Manage versioning for data, code, and models using tools like MLflow. Security & Compliance: Implementing data security measures, ensuring compliance with data governance policies, and protecting sensitive data Technology Eva

For over 20 years, Smartsheet has empowered teams to manage work seamlessly and scale solutions smarter. Now, in our most ambitious chapter yet, we are uniting human teams with AI agents. By orchestrating the work agents do best, automating manual tasks and uncovering insights at scale, we create the space for people to focus on what truly matters: judgment, creativity, and big thinking. That is magic at work, and it’s what we show up for every day. When was the last occasion you had the opportunity to contribute to a company that is shaping an industry and empowering individuals to translate ideas into tangible impact with speed? Smartsheet's core mission is to empower everyone to enhance their work processes. Our business model is founded on identifying exceptional talent and providing them with the autonomy to develop our acclaimed Software as a Service (SaaS) offering. With a user base exceeding 10 million, our platform is utilized across various industries, including construction, retail, and software development, presenting us with unique technical challenges. Smartsheet is seeking a Senior Business DevOps Engineer to join our Corporate Systems Development team in Bangalore. This role will focus on building and scaling our CI/CD pipelines, infrastructure automation, monitoring frameworks, and deployment processes supporting mission-critical integrations across Finance, People, Sales, Legal, IT, and Engineering systems. You’ll work across a variety of systems and platforms (AWS, GitLab, DataDog, Terraform, Boomi, UiPath) to streamline deployment of backend integrations and automation solutions. If you thrive on optimizing developer velocity, ensuring system reliability, and automating everything from build to deploy, this role is for you. The position reports to the Senior Manager, Systems Development and collaborates closely with global developers, architects, and application administrators to ensure our platform foundations are secure, efficient, and scalable

About Ema Ema is building the world’s leading Agentic AI platform to transform enterprise productivity. We enable organizations to delegate repetitive tasks to Ema, the Universal AI Employee, delivering 10x gains in workforce efficiency, across functions. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team includes engineers from premier tech companies and graduates of Stanford, MIT, UC Berkeley, CMU, and IITs. We are backed by industry leading investors including Accel, Naspers/Prosus, Section32, and angels like Sheryl Sandberg and Dustin Moskovitz. Headquartered in Silicon Valley and with offices in London, Bangalore and Vancouver, Ema is at the frontier of what Agentic AI can do in production — we ship real systems that run real business processes at scale. Role Overview & Key Responsibilities This is a high-leverage leadership role that spans architecture, execution, and org-building, and will shape the direction of our AI / ML initiatives at Ema. We are seeking an AI / ML technical leader who can take a vision and build it. As a Principal ML Engineer at Ema, you will be a senior technical leader responsible for shaping the machine learning roadmap, architecting large-scale ML systems, driving innovation, and ensuring our mixture of expert models (LLM + SLM + Custom Model) is accurate and performant at scale. You will collaborate across teams (research, product, infra, data, etc.), mentor senior engineers, and influence strategy and execution at company-wide levels. Responsibilities Lead the technical direction of GenAI and agentic ML systems that power enterprise-grade AI agents — spanning reasoning, retrieval, tool use, and integrations across various SaaS products. Architect, design, and implement scalable production pipelines for model training, fine-tuning, retrieval (RAG), agent orchestration, and evaluation — ensuring robustness, latency efficiency, and continuous learning. Define and own the multi-year ML roadmap for GenA

Instawork is on a mission to create meaningful economic opportunities for skilled hourly professionals in communities around the globe. Our AI-powered labor marketplace helps local businesses scale, and enables global technology companies to push the frontiers of robotics and AI. Backed by world-class investors like Benchmark, Spark Capital, Craft Ventures, Greylock, Y Combinator, and others, we’re looking for exceptional talent to reimagine the way the world works. Location : Bengaluru (On-site) + multi-city coordination Instawork Robotics Lab (IRL) Robots are getting smarter, but they still can’t reliably do the everyday physical tasks people do — chopping vegetables, stocking shelves, assembling parts. The bottleneck is data. UC Berkeley’s Prof. Ken Goldberg calls it the “100,000-year data gap”: the chasm between the massive text datasets used to train language models and the tiny amount of real-world, physical-dexterity data available to train robots. The entire robotics industry collected only ~100,000 hours of training data in 2024 and ~1 million in 2025 — and even the ~20 million hours projected for 2026 is still less than 0.04% of what is ultimately needed. IRL exists to close that gap. Using Instacore — a wearable multi-camera and sensor system (head, chest, and wrist cameras plus IMUs and a compute pack) — our field teams capture synchronized, high-diversity egocentric data of real people doing real tasks across real commercial environments: kitchens, warehouses, hotels, retail, and light manufacturing. That data is quality-checked, anonymized, and delivered to the world’s leading robotics companies and foundation-model labs to teach robots how to operate in the messy physical world. In India, we run the on-ground engine of this mission — a growing fleet of Instacore rigs, Field Officers and Data Collectors, regional hubs, and the operations and finance backbone that keeps it

Instawork is on a mission to create meaningful economic opportunities for skilled hourly professionals in communities around the globe. Our AI-powered labor marketplace helps local businesses scale, and enables global technology companies to push the frontiers of robotics and AI. Backed by world-class investors like Benchmark, Spark Capital, Craft Ventures, Greylock, Y Combinator, and others, we’re looking for exceptional talent to reimagine the way the world works. Instawork Robotics Lab (IRL) Robots are getting smarter, but they still can’t reliably do the everyday physical tasks people do — chopping vegetables, stocking shelves, assembling parts. The bottleneck is data. UC Berkeley’s Prof. Ken Goldberg calls it the “100,000-year data gap”: the chasm between the massive text datasets used to train language models and the tiny amount of real-world, physical-dexterity data available to train robots. The entire robotics industry collected only ~100,000 hours of training data in 2024 and ~1 million in 2025 — and even the ~20 million hours projected for 2026 is still less than 0.04% of what is ultimately needed. IRL exists to close that gap. Using Instacore — a wearable multi-camera and sensor system (head, chest, and wrist cameras plus IMUs and a compute pack) — our field teams capture synchronized, high-diversity egocentric data of real people doing real tasks across real commercial environments: kitchens, warehouses, hotels, retail, and light manufacturing. That data is quality-checked, anonymized, and delivered to the world’s leading robotics companies and foundation-model labs to teach robots how to operate in the messy physical world. In India, we run the on-ground engine of this mission — a growing fleet of Instacore rigs, Field Officers and Data Collectors, regional hubs, and the operations and finance backbone that keeps it all running at quality and scale. Role Overview The Finance Associat

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. ASIC IP STA Engineer (6-10 Years) | DDR PHY / ONFI PHY / IO Expander Location: Bengaluru, India Experience: 6-10 Years Enducational Qualification : BE/B-Tech/M-Tech (EEE, ECE, Micron Electronics, VLSI) Key Requirements Member of the AMS IP Physical Design team , responsible for post-layout STA signoff and timing closure of high-speed interface IPs, with close collaboration across IP Design, SoC Synthesis, and SoC Physical Design teams throughout IP development and SoC integration. 6-10 years of experience in Static Timing Analysis (STA) with a proven track record of 4 &#43; successful tapeouts . Strong hands-on expertise with Cadence Tempus (preferred). In-depth experience in MMMC timing analysis and closure across functional, scan, MBIST, and other DFT modes. Experience working on high-speed Memory Interface IPs such as DDR PHY, ONFI PHY, IO Expander (IOE) , or similar high-performance interface designs. Strong understanding of timing constraints development, validation, and debug , including clocks, generated clocks, timing exceptions, and mode-specific constraints. Experience in Liberty (.lib) and ETM timing model generation, validation, correlation, and quality assessment . <span

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. Job Overview: We are looking for a Senior Engineer to join the FGA DevEx team and help evolve our end to end developer experience across both OSS and SaaS. This team owns the SDKs in Go, JavaScript, .NET, Python, Java and other languages, along with CLI workflows, IDE integrations, GitHub automation, developer documentation, and release strategy. All development is done in the open as open source, and we actively welcome and review community contributions. Our guiding principle is One developer experience, many deployment models. As a Senior Engineer, you will take ownership of significant portions of the SDK and tooling ecosystem, ensure high quality implementations across languages, and contribute to a consistent and reliable developer experience. Responsibilities: Maintain and enhance existing SDKs for FGA in Go, JavaScript, .NET, Python, and Java, leveraging our SDK generator framework. Customize and refine SDK templates and wrappers to ensure consistency across languages and support configuration overrides such as store ID, authorization model ID, headers, and parallelization limits. Implement and improve core SDK features including client credentials authentication flows, robust error mapping, retry logic with jitter, and rate limiting safeguards. Implement advanced capabilities such as BatchCheck, ListRelations, and non transactional write operations with appropriate parallelization and performance considerations. Contribute to the SDK generator tool

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. Identity is the foundation of trust on the internet, and at Okta, we are building a world where anyone can safely use any technology. We are looking for a driven, curious, and empathetic product-minded engineering leader to expand Okta’s market footprint by growing our global integration ecosystem. As the Director of Engineering for the Okta Integration Ecosystem in Bangalore, you will lead, scale, and inspire a talented organization of engineering managers and engineers dedicated to evolving Okta-built integrations across our entire product portfolio. This is a high-impact, high-visibility role. If you are passionate about customer security, obsessed with developer experience, and love engaging with a vibrant technology community, we want to hear from you. What You’ll Do Lead and Scale the Team: Mentor, inspire, and grow a world-class engineering organization in Bangalore, directly managing engineering managers and senior individual contributors while fostering a high-performance culture. Drive Integration Strategy: Own the technical roadmap and execution for Okta’s integrations across a massive gamut of applications—spanning traditional Enterprise systems, SaaS, On-prem infrastructure, Active Directory (AD), Azure, and next-generation AI agents. Advance Modern Infra & Governance: Drive the development, rollout, and governance of the official Okta MCP (Model Context Protocol) Server. Streamline and enable partner integrations through robust Terraform P

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 The Senior Manager, Data & Analytics Products owns a portfolio of enterprise-critical Tier 1 products from strategy and discovery through delivery, adoption, service performance, and value realization. The role connects executive and business priorities to product roadmaps and leads across product, data engineering, analytics, governance, architecture, security, operations, and business teams. The ideal candidate is a data and analytics leader with strong product judgment: commercially grounded, technically fluent, practical in the application of AI, and skilled at aligning senior stakeholders and global delivery teams. Success requires the ability to make enterprise data trusted, analytics products useful, and complex strategic programs executable - without requiring hands-on engineering or model development. WHAT YOU'LL DO Tier 1 insights product portfolio strategy. Own the vision, value proposition, target users, product criticality, investment priorities, outcome metrics, and multi-horizon roadmaps for the company's most important data and analytics products. Balance run, grow, and transform priorities across the portfolio. Discovery and product lifecycle. Lead stakeholder interviews, user research, decision-journey and process analysis, and opportunity sizing. Translate important business questions into product requirements, priorities, roadmaps, success measures, and an ongoing improvement a