Learning Tools Manager in India

Job Description: Fintech Learning Consultant Company: Paytm Location: India (Open to Pan-India Travel) Experience Required: 5 to 15+ Years Employment Type: Full-Time / Contractual / Part-time About Paytm Paytm is India's leading digital ecosystem for consumers and merchants. We are redefining how people access financial services and how businesses grow through technology. As we expand our fintech footprint, we are investing in cutting-edge education, training, and innovation to upskill the future workforce. Role Overview We are seeking a seasoned Learning Consultant - Fintech to join our team in a full-time capacity. This role is ideal for a fintech domain expert who combines deep subject matter expertise with strong communication and content design skills. The individual will play a pivotal role in bridging industry practice with structured learning, working at the intersection of fintech innovation, academic collaboration, and capability development. Key Responsibilities Training & Enablement: Design and deliver high-impact training sessions for external partners and student cohorts at universities and colleges, enabling a strong understanding of fintech platforms, products, and emerging technologies. Research & Trend Analysis: Continuously track global fintech trends, regulatory developments, and technological advancements; translate these insights into relevant, future-focused learning interventions. Product & Business Support: Collaborate with product and business teams by providing domain expertise across the fintech lifecycle—including ideation, design validation, testing, and go-to-market readiness. Content Development: Develop structured, outcome-driven learning content including curriculum frameworks, case studies, playbooks, and technical guides tailored to diverse learner segments. Required Skills & Tools Must-Have: Strong verbal and written communication with the ability to translate complex concepts into understandable learning modules. Good to Ha

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

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. Cloud Support Engineer — AI/ML & Programmability (Night Shift) Location: Pune, India Snowflake's Support team is expanding. We're looking for a Cloud Support Engineer who enjoys working with data and solving a wide variety of problems, drawing on hands-on experience across operating systems, database technologies, big data, data integration, connectors, and networking. Our mission is to make Snowflake the preferred platform for running all AI, ML, data science, and data engineering workloads. You'll join a highly productive, fast-moving team supporting Snowflake Cortex and our ML product lines — work that is central to delivering on Snowflake's AI Data Cloud mission. Snowflake Support is committed to providing high-quality resolutions that help customers deliver data-driven business insights and results. We are a team of subject matter experts working collectively toward our customers' success, building partnerships by listening, learning, and connecting. Snowflake's values shape how we deliver world-class Support: putting customers first, acting with integrity, owning initiative and accountability, and getting it done. As a Cloud Support Engineer, you'll be the technical partner our customers turn to for guidance on using Snowflake effectively. You'll also be the voice

Role Purpose: At Jumio, the Software Engineer II (QA) will focus on ensuring the quality and performance of highly scalable web and backend applications. In this role, you will design and implement automated tests for web (Playwright/Selenium) and API-based solutions, leveraging your knowledge of Java or JavaScript. Collaborating closely with development and product teams, you will ensure Jumio's products meet the highest standards of quality and reliability. You’ll have an opportunity to learn and grow in a fast-paced environment while exploring new tools and methodologies. A problem-solving mindset, willingness to innovate, and attention to detail will make you successful in this role. T-Shaped Engineering Expectation: As part of Jumio’s engineering culture, you will adopt a T-shaped engineering approach. In addition to developing expertise in test automation and quality engineering, you will collaborate across the development lifecycle, including understanding software architecture, contributing to design discussions, and ensuring robust and scalable test solutions. Role Value: This role is critical to ensuring the reliability, scalability, and security of Jumio’s products. By building and maintaining automated testing frameworks, you will enable faster releases and higher confidence in the quality of our software. Example Responsibilities: Develop, maintain, and execute automated test scripts for web applications using Playwright, Selenium, or similar automation frameworks. Create and execute API test suites using tools such as Postman, REST Assured, or equivalent testing frameworks. Design and execute functional, regression, integration, and exploratory test cases based on business and technical requirements. Validate application functionality, backend services, APIs, and data flows across different environments. Identify, document, track, and verify defects, working closely with developers to ensure timely resolution. Execute automated test suites as part of C

Artefact is a new generation of data service providers specialising in data consulting and data-driven digital marketing. It is dedicated to transforming data into business impact across the entire value chain of organisations. We are proud to say we’re enjoying skyrocketing growth. The backbone of our consulting missions, today our Data consulting team has more than 400 consultants covering all Artefact's offers (and more): data marketing, data governance, strategy consulting, product owner… What you will be doing? As a Data Scientist, your primary role revolves around leveraging Python and SQL to conduct data science modelling, employing statistical and machine learning algorithms to derive actionable insights. Your responsibilities will encompass: Data Modeling: Developing and implementing sophisticated data science models to extract valuable insights from complex datasets. Algorithm Implementation: Applying statistical and machine learning algorithms to solve business problems and enhance decision-making processes. Visualization: Utilizing visualization tools like Tableau and PowerBI to present findings in a compelling and understandable manner. Cloud-Based Deployment: Deploying models on cloud platforms such as MS Azure, GCP, and AWS, optimizing their functionality and scalability. What we are looking for? Proficiency in Python, SQL, data science modeling, and statistical analysis. Strong grasp of ML algorithms and their implementation in real-world scenarios. Experience in visualization tools like Tableau and PowerBI, along with knowledge of deploying models on cloud platforms (MS Azure, GCP, AWS). Proven problem-solving skills and a solution-oriented mindset. Excellent communication skills to collaborate effectively within teams and with stakeholders. Strong business acumen with an interest in business-facing roles. Adaptability and a start-up mentality to thrive in a dynamic environment. Candidates with similar skill sets and experiences have e

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

About Us Pearl is AI for professional services at global scale, combining advanced AI with verified human expertise to deliver help that is accurate, accountable, and fast. Since 2003, our network has connected millions of customers with licensed professionals across 196 countries, making real expertise available anytime, anywhere. Our Values Data driven: Start with truth, measure what matters. Courageous: Bias to action; run toward hard problems. Innovative: Seek novel, elegant solutions. Lean: Do more with less. Build, ship, learn fast. Humble: Strong opinions, lightly held. About the Role The future of analytics isn't dashboards. It's intelligent systems that anticipate questions, surface insights, and help people make better decisions. We're looking for a Senior Analytics Engineer to help build that future at Pearl. In this role, you'll design and develop AI-powered analytics experiences that combine trusted enterprise data with modern AI capabilities, enabling business users to interact with data conversationally and uncover insights faster than ever before. You'll build production AI agents, create scalable semantic data models, develop intelligent analytics applications, and establish best practices for responsible AI across the Analytics organization. Working closely with Product, Engineering, and business leaders, you'll turn emerging AI technologies into real business capabilities that improve decision making across the company. This is an opportunity to help define how AI transforms analytics at Pearl while working on some of the most exciting technologies in data, LLMs, and agentic AI. What You’ll Do Build proactive analytics and AI solutions that surface actionable business insights, anticipate business needs, and enable smarter decision-making. Design and develop AI-powered analytics tools, including conversational interfaces that allow business users to query data using natural language. Build semantic data models and reusab

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

Backend Engineer (Senior Level) - SDE IV We're looking for a Senior Backend Engineer to lead the architecture and evolution of backend services that deploy and serve machine learning models in production. You'll work closely with ML Engineers, Platform, and Product teams to build scalable, reliable systems and drive technical direction across multiple teams. What You’ll Do Design and drive the long-term architecture of backend services for biometrics and ML model serving. Collaborate with core platform and backend teams on organization-wide architectural initiatives. Partner with business and engineering teams to design and deliver cross-cutting platform capabilities. Lead architectural reviews, mentor engineers, and promote engineering best practices. Build and maintain backend services for deploying and serving ML models Monitor service reliability, performance, and scalability in production Deploy and operate services on AWS using ECS + Fargate, SageMaker, or EC2 + Kubernetes Support real-time and batch inference workflows Contribute to CI/CD pipelines and deployment automation What We’re Looking For Strong expertise in backend development using Java and working knowledge of Python. Experience mentoring engineers and driving architectural decisions. Working knowledge of Python, especially for ML-related workflows Hands-on experience with AWS (e.g., DynamoDB, ECS, EC2, Redis, S3, SageMaker) Familiarity with Terraform or other infrastructure-as-code tools, and experience with CI/CD and production monitoring Experience with observability tools (Datadog, New Relic, etc.) Experience with containers and orchestration (Docker, ECS, etc.) Understanding of how ML models are deployed and served in production Experience with Kubernetes Nice to Have Experience with MLOps or ML platform engineering. Experience with asynchronous programming and event-driven systems. Jumio Values: IDEAL: Integrity, Diversity, Empowerment, Accountability, Leading Innovation Equal Opportunities :

DeepIntent is the leading healthcare marketing platform, purpose-built to help marketers plan, activate, and optimize data-driven campaigns with speed and precision. Trusted by the world’s top healthcare brands and their agencies, DeepIntent uniquely unites media, identity, and real-world clinical data to power privacy-safe, omnichannel marketing across every screen. Backed by patented technology and proven outcomes, DeepIntent’s platform delivers measurable audience quality and script lift at scale. Learn more at www.deepintent.com . What You’ll Do: We are looking for a Senior Software Engineer – Platform Operations based in Pune, India, who will play a key role in ensuring the reliability, performance, and operational excellence of DeepIntent's platform and data ecosystem. This role requires a strong engineering mindset with the ability to troubleshoot complex technical issues, understand distributed data architectures, and collaborate across Engineering, Product, Analytics, and Customer-facing teams to deliver timely and effective solutions. As part of the Operations organization, you will work closely with Engineering to support production systems, improve operational processes, and drive platform stability. The ideal candidate is a self-motivated problem solver who is passionate about learning new technologies, improving system reliability, and delivering exceptional customer outcomes through engineering excellence. Serve as the engineering interface between Customer-facing teams, Analytics, Product, and Engineering organizations. Partner with Platform Support, Client Success, and other customer-facing teams to investigate and resolve complex platform-related issues. Analyze application, API, and data pipeline issues to identify root causes and drive timely resolution. Develop and standardize operational tools, and interfaces to support analytical and operational use cases. Monitor data pipeline executions, investigate failures, and implement corrective and pre

Role: Application Reliability Engineer Location: Gurgaon Who we are Graviton Research Capital 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 diverse range of concepts, from time series analysis and stochastic models to machine learning and statistical inference. We analyse terabytes of data to identify pricing anomalies and drive innovation in financial markets. Key Responsibilities and Deliverables The ideal candidate will possess a strong background in technical support, with a passion for problem-solving and a commitment to excellence. As an Application Reliability Engineer, you will be responsible for: Monitor production services and respond quickly to alerts, incidents, and outages to ensure smooth operation and minimal downtime. Monitor trading systems and infrastructure., Triage issues across trading support services, databases, and infra; escalate and coordinate with the right owners, and drive root-cause analysis and ensure fixes are implemented for long-term stability. Serve as the first line of defense for trading operations. Proactively identify, address recurring issues, and build automation to reduce manual intervention. Improve observability by enhancing monitoring, logging, and alerting systems. Develop and maintain operational runbooks and SLO/SLA metrics. Eligibility and Required Skills Possess a degree in a highly analytical field, such as Engineering, or Computer Science 2-5 years of experience in Python, Shell/Bash scripting. Experience with Linux and shell/bash online tools. Hands-on experience with databases (SQL, NoSQL) Strong problem-solving and analytical skills Excellent communication skills Ability to remain calm and analytical under production pressure Good to have: Familiarity with monitoring/alerting stacks (Prometheus, Grafana, ELK, etc.) Familiarity with distributed messaging (Kafka) and caching systems (Red

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

At FourKites we have the opportunity to tackle complex challenges with real-world impacts. Whether it's medical supplies from Cardinal Health or groceries for Walmart, the FourKites platform helps customers operate global supply chains that are efficient, agile and sustainable. Join a team of curious problem solvers that celebrates differences, leads with empathy and values inclusivity. As a Senior Data Scientist, you will build and own machine learning models that power core prediction problems across the FourKites platform — including ETA/ATA forecasting and message-based status extraction. You will work end-to-end, from data pipeline to production deployment and monitoring, turning noisy real-world logistics data into models that run at scale and directly move the needle on customer outcomes. You will work closely with product, engineering, and operations teams, hands-on building and shipping models yourself while also guiding the technical direction of other data scientists on the team. What you'll be doing: Design, build, and productionize ML models for problems like ETA/ATA prediction, using regression, classification, and time-series forecasting techniques Develop NLP/LLM-based extraction pipelines for message-based ETA and status updates (text extraction, entity recognition) Own models end-to-end: data pipeline → training → deployment → monitoring → retraining Work with noisy, real-world logistics and supply chain data (GPS pings, check calls, carrier data) rather than clean, pre-processed datasets Diagnose gaps between offline evaluation performance and live production accuracy, and drive fixes Build and maintain automated training/retraining pipelines using orchestration tools such as Airflow Set up and maintain model monitoring and observability (e.g., Grafana) to catch drift and degradation proactively Replace manual or rule-based processes with ML-driven automation (e.g., automating manual check calls) Translate model performance improvements into busin

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. About the Team The Professional Services R&D team is a new, dynamic group at the forefront of innovation within Okta. Our mission is to design and build reusable, scalable assets and tools that empower our delivery teams and partners. By making customer engagements more efficient, streamlined, and cost-effective, we directly contribute to our customers' success and accelerate their time-to-value with Okta. This is a unique opportunity to join a strategic team from the ground up and shape the future of Okta's professional services. Position Summary As the Architect for the Professional Services R&D team, you will be the principal technical leader responsible for the high-level design and technical strategy of our entire portfolio of reusable assets. You will define the architectural vision and standards that ensure our solutions are robust, scalable, and secure. This role requires a blend of deep technical expertise, strategic thinking, and strong collaboration skills to guide the engineering team in building a cohesive ecosystem of tools on technologies like Java, React, Node, Python, and .NET. Responsibilities Define and own the end-to-end technical architecture for all reusable assets and solutions developed by the R&D team. Establish architectural standards, patterns, and best practices to guide the development team. Evaluate and select appropriate technologies, frameworks, and platforms to meet project requirements and long-term business goa

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. About the Team The Professional Services R&D team is a new, dynamic group at the forefront of innovation within Okta. Our mission is to design and build reusable, scalable assets and tools that empower our delivery teams and partners. By making customer engagements more efficient, streamlined, and cost-effective, we directly contribute to our customers' success and accelerate their time-to-value with Okta. This is a unique opportunity to join a strategic team from the ground up and shape the future of Okta's professional services. Position Summary As a QA Automation Engineer, you will be a critical guardian of quality for the R&D team. You will be responsible for designing, building, and maintaining the automated testing frameworks that ensure our reusable assets are robust, reliable, and bug-free. You will embed a "quality-first" mindset within the team, working closely with developers to implement comprehensive test strategies and integrate them into our CI/CD pipeline. Your work will directly ensure that the tools we provide to our field teams and partners are trusted and effective. Responsibilities Design, develop, and maintain scalable and reliable automated test frameworks for UI, API, and performance testing. Write and execute automated test cases to ensure comprehensive test coverage for all developed assets. Integrate automated testing into the CI/CD pipeline to enable continuous delivery and rapid feedback. Work closely with developers and