666 Drift Jobs - Page 3

Key Responsibilities · Design, build, and deploy advanced ML models (regression, classification, NLP, etc.). · Architect and implement deep learning pipelines using PyTorch or TensorFlow. · Develop and fine-tune LLM-based applications (e.g., RAG pipelines, prompt engineering, embeddings). · Lead and mentor junior data scientists and drive code quality and reuse. · Apply MLOps practices: CI/CD for ML, model monitoring, reproducibility. · Write basic SQL queries to support data processing and feature engineering. · Collaborate cross-functionally with product, engineering, and data engineering teams. Requirements · 5+ years of experience in machine learning and AI. · Expert in Python, data science libraries, and deep learning frameworks. · Strong knowledge of regression, classification, optimization algorithms, and evaluation metrics. · Hands-on experience with PyTorch or TensorFlow (preferably both). · Proven experience working with LLMs and prompt-based models. · Experience in MLOps and deploying ML models to production. · Basic proficiency in SQL for querying structured data. · Proficient in using Git/GitHub for collaborative development. Good to Have · Experience building or integrating AI agents using LangChain, AutoGen, or similar tools. · Knowledge or experience with reinforcement learning algorithms. Activities: 1. Data Engineering -code optimization 2. Feature Eng -code optimization 3. Model training -code optimization 4. API creation, make it deployable 5. Audit, logging, perf & drift handling 6. Deployment and Support

Here’s a well-structured list of Roles & Responsibilities for a Senior Flutter Developer who can take your idea and turn it into a full-fledged app ready for Play Store and App Store deployment. This role assumes full-stack mobile app ownership and expertise across architecture, development, deployment, and maintenance. 🚀 Senior Flutter Developer - Roles & Responsibilities ✅ Core Responsibilities End-to-End App Development Translate product ideas, mockups, or wireframes into functional, high-performance Flutter apps. Build apps for both Android and iOS using a single codebase. Architecture & Project Planning Design app architecture: state management (e.g., Riverpod, Bloc), clean code structure, scalable folder structures. Set up modular codebases for maintainability and team collaboration. Break down high-level product requirements into technical tasks. API Integration & Backend Communication Consume RESTful APIs, GraphQL, or Firebase services. Implement error handling, loading states, and offline-first strategies where needed. Authentication & Security Implement login/signup with phone/email/Google/Apple. Setup Firebase Auth / AWS Cognito / custom auth flows. Secure data storage (e.g., SharedPreferences, Hive, EncryptedStorage). Database & Storage Local databases: Hive, Drift, SQLite. Cloud databases: Firebase Firestore, Realtime DB, Supabase, or custom backend. State Management Use and recommend best practices for scalable state management (Riverpod preferred for futureproofing). Third-party SDKs & Integrations Integrate SDKs: payments (e.g., Razorpay, Stripe), push notifications (Firebase Messaging), analytics, deep linking, maps, etc. UI/UX Implementation Create pixel-perfect, responsive UIs from Figma or other design tools. Add animations using Rive, Lottie, or Flutter’s native animation tools. Testing & Quality Assurance Write unit, widget, and integration tests. Ensure app stability using CI/CD and crash reporting tools (e.g., Sentry, Firebase Crashlytics). Deployment Prepare apps for Google Play Store and Apple App Store with all necessary compliance. Handle signing, provisioning profiles, and release builds. Setup CI/CD for automated builds (e.g., with Codemagic, Bitrise, GitHub Actions). 👨‍💼 Team & Communication Collaborate with product manager, UI/UX designer, and backend developers. Participate in agile sprints, daily standups, and sprint planning. Convert product vision into tech specs, timelines, and deliverables. 🧠 Required Expertise 3–5+ years Flutter experience (Dart, Widgets, CustomPainter, Platform Channels). Prior experience launching apps to both Play Store and App Store. Deep understanding of mobile architecture (clean architecture, MVVM, hexagonal, etc.). Familiarity with performance optimization, lazy loading, and memory management. Proficient in Git, GitHub, GitLab, Bitbucket workflows. Experience with cloud (Firebase, AWS Amplify) is a plus. 💡 Bonus Skills Native Android (Kotlin) / iOS (Swift) experience for bridging platform features. DevOps experience (CI/CD pipelines, release automation). Experience working in a startup or building MVPs from scratch. Familiarity with tools like Figma, Notion, Jira, Postman. 📦 Expected Deliverables Production-ready Flutter app (Android + iOS). Complete source code with documentation. Deployed app live on both stores. Basic analytics, crash reporting, and CI/CD setup. Post-release support for bug fixing and iteration.

Before you apply to a job, select your language preference from the options available at the top right of this page. Explore your next opportunity at a Fortune Global 500 organization. Envision innovative possibilities, experience our rewarding culture, and work with talented teams that help you become better every day. We know what it takes to lead UPS into tomorrow—people with a unique combination of skill + passion. If you have the qualities and drive to lead yourself or teams, there are roles ready to cultivate your skills and take you to the next level. Job Description Job Summary: We are seeking a highly skilled MLOps Engineer to design, deploy, and manage machine learning pipelines in Google Cloud Platform (GCP). In this role, you will be responsible for automating ML workflows, optimizing model deployment, ensuring model reliability, and implementing CI/CD pipelines for ML systems. You will work with Vertex AI, Kubernetes (GKE), BigQuery, and Terraform to build scalable and cost-efficient ML infrastructure. The ideal candidate must have a good understanding of ML algorithms, experience in model monitoring, performance optimization, Looker dashboards and infrastructure as code (IaC), ensuring ML models are production-ready, reliable, and continuously improving. You will be interacting with multiple technical teams, including architects and business stakeholders to develop state of the art machine learning systems that create value for the business. Responsibilities Managing the deployment and maintenance of machine learning models in production environments and ensuring seamless integration with existing systems. Monitoring model performance using metrics such as accuracy, precision, recall, and F1 score, and addressing issues like performance degradation, drift, or bias. Troubleshoot and resolve problems, maintain documentation, and manage model versions for audit and rollback. Analyzing monitoring data to preemptively identify potential issues and providing regular performance reports to stakeholders. Optimization of the queries and pipelines. Modernization of the applications whenever required Qualifications Expertise in programming languages like Python, SQL Solid understanding of best MLOps practices and concepts for deploying enterprise level ML systems. Understanding of Machine Learning concepts, models and algorithms including traditional regression, clustering models and neural networks (including deep learning, transformers, etc.) Understanding of model evaluation metrics, model monitoring tools and practices. Experienced with GCP tools like BigQueryML, MLOPS, Vertex AI Pipelines (Kubeflow Pipelines on GCP), Model Versioning & Registry, Cloud Monitoring, Kubernetes, etc. Solid oral and written communication skills and ability to prepare detailed technical documentation of new and existing applications. Strong ownership and collaborative qualities in their domain. Takes initiative to identify and drive opportunities for improvement and process streamlining. Bachelor’s Degree in a quantitative field of mathematics, computer science, physics, economics, engineering, statistics (operations research, quantitative social science, etc.), international equivalent, or equivalent job experience. Bonus Qualifications Experience in Azure MLOPS, Familiarity with Cloud Billing. Experience in setting up or supporting NLP, Gen AI, LLM applications with MLOps features. Experience working in an Agile environment, understanding of Lean Agile principles. Employee Type Permanent UPS is committed to providing a workplace free of discrimination, harassment, and retaliation.

Job Title: Data Engineer (Microsoft Fabric & Lakehouse) Location: Hybrid – Bangalore, India Experience: 5+ Years Joining: Immediate Key Responsibilities ● Design and build robust data pipelines using Microsoft Fabric components including Pipelines, Notebooks (PySpark), Dataflows, and Lakehouse architecture. ● Ingest and transform data from a variety of sources such as cloud platforms (Azure, AWS), on-prem databases, SaaS platforms (e.g., Salesforce, Workday), and REST/OpenAPI-based APIs. ● Develop and maintain semantic models and define standardized KPIs for reporting and analytics in Power BI or equivalent BI tools. ● Implement and manage Delta Tables across bronze/silver/gold layers using Lakehouse medallion architecture within OneLake or equivalent environments. ● Apply metadata-driven design principles to support pipeline parameterization, reusability, and scalability. ● Monitor, debug, and optimize pipeline performance; implement logging, alerting, and observability mechanisms. ● Establish and enforce data governance policies including schema versioning, data lineage tracking, role-based access control (RBAC), and audit trail mechanisms. ● Perform data quality checks including null detection, duplicate handling, schema drift management, outlier identification, and Slowly Changing Dimensions (SCD) type management. Required Skills & Qualifications- ● 5+ years of hands-on experience in Data Engineering or related fields. ● Solid understanding of data lake/lakehouse architectures, preferably with Microsoft Fabric or equivalent tools (e.g., Databricks, Snowflake, Azure Synapse). ● Strong experience with PySpark, SQL, and working with dataflows and notebooks. ● Exposure to BI tools like Power BI, Tableau, or equivalent for data consumption layers. ● Experience with Delta Lake or similar transactional storage layers. ● Familiarity with data ingestion from SaaS applications, APIs, and enterprise databases. ● Understanding of data governance, lineage, and RBAC principles. ● Strong analytical, problem-solving, and communication skills.

Company Description OpenBlockAI is India’s first AI + Blockchain-powered compliance platform revolutionizing the fight against financial crimes. We are building a real-time AML (Anti-Money Laundering) infrastructure designed for banks, fintechs, and government ecosystems. Our hybrid AI + Blockchain solution enables real-time fraud detection, transaction monitoring, and regulatory intelligence—before money laundering happens. Backed by a product-first vision, OpenBlockAI is co-founded by experienced entrepreneurs and is in active conversations with leading banks and regulatory bodies. We are now looking for a CTO with deep tech expertise and vision to lead the engineering and innovation roadmap. Role Description We are seeking a Chief Technology Officer (CTO) to join our founding team and lead the end-to-end technology strategy of a next-gen AI and blockchain platform built for the financial sector. The ideal candidate is a hands-on technology leader with a strong engineering foundation, start-up experience, and a passion for building innovative, secure, and scalable products. Your Responsibilities Will Include: Define and execute the long-term technical vision and architecture. Build and lead a high-performing engineering and AI/ML team. Design and oversee a secure, scalable, and modular cloud-native infrastructure. Drive development and deployment of AI/ML systems, blockchain frameworks, and real-time APIs. Ensure robust implementation of MFA, IAM, authorization, and secure communication protocols. Collaborate cross-functionally with product, compliance, and business stakeholders. Stay abreast of evolving regulatory technologies and ensure tech compliance readiness. Qualifications: 5+ years of proven experience in AI/ML, Blockchain, or Fintech architecture. Strong hands-on background in: Node.js, PostgreSQL, MongoDB AWS infrastructure, Docker, Kubernetes Deep understanding of AI model lifecycle, including: Model training and deployment REST/GraphQL prediction APIs Feedback collection and versioning Model drift detection and explainability Hands-on expertise with blockchain frameworks such as Ethereum, Hyperledger, or similar. Familiarity with data security, compliance standards, and regulatory frameworks (e.g., RBI, GDPR, ISO/PCI). Strong grasp of system design, distributed architecture, and DevSecOps best practices. Excellent communication, leadership, and decision-making abilities. Preferred (Good to Have): Exposure to RegTech, AML/KYC compliance, or banking infrastructure. Experience scaling products in multi-tenant or SaaS environments. Contributions to open-source, patents, or published research in AI or blockchain. Compensation: Equity-based role

AI Engineer – Voice, NLP, and GenAI Systems Location : Sector 63, Gurgaon – 100% In-Office Working Days : Monday to Friday, with 2nd and 4th Saturdays off Working Hours : 10:30 AM to 8:00 PM Experience : 2–6 years in AI/ML, NLP, or applied machine learning engineering Apply at : careers@darwix.ai Subject Line : Application – AI Engineer – [Your Name] About Darwix AI Darwix AI is India’s fastest-growing GenAI SaaS platform transforming how enterprise sales, field, and support teams engage with customers. Our suite— Transform+ , Sherpa.ai , and Store Intel —powers real-time multilingual voice analytics, AI nudges, coaching systems, and computer vision analytics for major enterprises across India, MENA, and Southeast Asia. We work with some of the largest names such as Aditya Birla Capital, Sobha, GIVA, and Bank Dofar. Our systems process thousands of daily conversations, live call transcripts, and omnichannel data to deliver actionable revenue insights and in-the-moment enablement. Role Overview As an AI Engineer , you will play a key role in designing, developing, and scaling AI and NLP systems that power our core products. You will work at the intersection of voice AI, natural language processing (NLP), large language models (LLMs), and speech-to-text pipelines. You will collaborate with product, backend, and frontend teams to integrate ML models into production workflows, optimize inference pipelines, and improve the accuracy and performance of real-time analytics used by enterprise sales and field teams. Key ResponsibilitiesAI & NLP System Development Design, train, fine-tune, and deploy NLP models for conversation analysis, scoring, sentiment detection, and call summarization. Work on integrating and customizing speech-to-text (STT) pipelines (e.g., WhisperX, Deepgram) for multilingual audio data. Develop and maintain classification, extraction, and sequence-to-sequence models to handle real-world sales and service conversations. LLM & Prompt Engineering Experiment with and integrate large language models (OpenAI, Cohere, open-source LLMs) for live coaching and knowledge retrieval use cases. Optimize prompts and design retrieval-augmented generation (RAG) workflows to support real-time use in product modules. Develop internal tools for model evaluation and prompt performance tracking. Productionization & Integration Build robust model APIs and microservices in collaboration with backend engineers (primarily Python, FastAPI). Optimize inference time and resource utilization for real-time and batch processing needs. Implement monitoring and logging for production ML systems to track drift and failure cases. Data & Evaluation Work on audio-text alignment datasets, conversation logs, and labeled scoring data to improve model performance. Build evaluation pipelines and create automated testing scripts for accuracy and consistency checks. Define and track key performance metrics such as WER (word error rate), intent accuracy, and scoring consistency. Collaboration & Research Work closely with product managers to translate business problems into model design requirements. Explore and propose new approaches leveraging the latest research in voice, NLP, and generative AI. Document research experiments, architecture decisions, and feature impact clearly for internal stakeholders. Required Skills & Qualifications 2–6 years of experience in AI/ML engineering, preferably with real-world NLP or voice AI applications. Strong programming skills in Python , including libraries like PyTorch, TensorFlow, Hugging Face Transformers. Experience with speech processing , audio feature extraction, or STT pipelines. Solid understanding of NLP tasks: tokenization, embedding, NER, summarization, intent detection, sentiment analysis. Familiarity with deploying models as APIs and integrating them with production backend systems. Good understanding of data pipelines, preprocessing techniques, and scalable model architectures. Preferred Qualifications Prior experience with multilingual NLP systems or models tuned for Indian languages. Exposure to RAG pipelines , embeddings search (e.g., FAISS, Pinecone), and vector databases. Experience working with voice analytics, diarization, or conversational scoring frameworks. Understanding of DevOps basics for ML (MLflow, Docker, GitHub Actions for model deployment). Experience in SaaS product environments serving enterprise clients. Success in This Role Means Accurate, robust, and scalable AI models powering production workflows with minimal manual intervention. Inference pipelines optimized for enterprise-scale deployments with high availability. New features and improvements delivered quickly to drive direct business impact. AI-driven insights and automations that enhance user experience and boost revenue outcomes for clients. You Will Excel in This Role If You Love building AI systems that create measurable value in the real world, not just in research labs. Enjoy solving messy, real-world data problems and working on multilingual and noisy data. Are passionate about voice and NLP, and constantly follow advancements in GenAI. Thrive in a fast-paced, high-ownership environment where ideas quickly become live features. How to Apply Email your updated CV to careers@darwix.ai Subject Line: Application – AI Engineer – [Your Name] (Optional): Share links to your GitHub, open-source contributions, or a short note about a model or system you designed and deployed in production. This is an opportunity to build foundational AI systems at one of India’s fastest-scaling GenAI startups and to impact how large enterprises engage millions of customers every day. If you are ready to transform how AI meets revenue teams—Darwix AI wants to hear from you.

🧠 Job Title: Senior Machine Learning Engineer Company : Darwix AI Location : Gurgaon (On-site) Type : Full-Time Experience : 4–8 years Education : B.Tech / M.Tech / Ph.D. in Computer Science, Machine Learning, Artificial Intelligence, or related fields 🚀 About Darwix AI Darwix AI is India's fastest-growing GenAI SaaS startup, building real-time conversational intelligence and agent-assist platforms that supercharge omnichannel enterprise sales teams across India, MENA, and Southeast Asia. Our mission is to redefine how revenue teams operate by using Generative AI, LLMs, Voice AI , and deep analytics to deliver better conversations, faster deal cycles, and consistent growth. Our flagship platform, Transform+ , analyzes millions of hours of sales conversations, gives live nudges, builds AI-powered sales content, and enables revenue teams to become truly data-driven — in real time. We’re backed by marquee investors, industry veterans, and AI experts, and we’re expanding fast. As a Senior Machine Learning Engineer , you will play a pivotal role in designing and deploying intelligent ML systems that power every layer of this platform — from speech-to-text, diarization, vector search, and summarization to recommendation engines and personalized insights. 🎯 Role Overview This is a high-impact, high-ownership role for someone who lives and breathes data, models, and real-world machine learning. You will design, train, fine-tune, deploy, and optimize ML models across various domains — speech, NLP, tabular, and ranking. Your work will directly power critical product features: from personalized agent nudges and conversation scoring to lead scoring, smart recommendations, and retrieval-augmented generation (RAG) pipelines. You’ll be the bridge between data science, engineering, and product — converting ideas into models, and models into production-scale systems with tangible business value. 🧪 Key Responsibilities🔬 1. Model Design, Training, and Optimization Develop and fine-tune machine learning models using structured, unstructured, and semi-structured data sources. Work with models across domains: text classification, speech transcription, named entity recognition, topic modeling, summarization, time series, and recommendation systems. Explore and implement transformer architectures, BERT-style encoders, Siamese networks, and retrieval-based models. 📊 2. Data Engineering & Feature Extraction Build robust ETL pipelines to clean, label, and enrich data for supervised and unsupervised learning tasks. Work with multimodal inputs — audio, text, metadata — and build smart representations for downstream tasks. Automate data collection from APIs, CRMs, sales transcripts, and call logs. ⚙️ 3. Productionizing ML Pipelines Package and deploy models in scalable APIs (using FastAPI, Flask, or similar frameworks). Work closely with DevOps to containerize and orchestrate ML workflows using Docker, Kubernetes, or CI/CD pipelines. Ensure production readiness: logging, monitoring, rollback, and fail-safes. 📈 4. Experimentation & Evaluation Design rigorous experiments using A/B tests, offline metrics, and post-deployment feedback loops. Continuously optimize model performance (latency, accuracy, precision-recall trade-offs). Implement drift detection and re-training pipelines for models in production. 🔁 5. Collaboration with Product & Engineering Translate business problems into ML problems and align modeling goals with user outcomes. Partner with product managers, AI researchers, data annotators, and frontend/backend engineers to build and launch features. Contribute to the product roadmap with ML-driven ideas and prototypes. 🛠️ 6. Innovation & Technical Leadership Evaluate open-source and proprietary LLM APIs, AutoML frameworks, vector databases, and model inference techniques. Drive innovation in voice-to-insight systems (ASR + Diarization + NLP). Mentor junior engineers and contribute to best practices in ML development and deployment. 🧰 Tech Stack🔧 Languages & Frameworks Python (core), SQL, Bash PyTorch, TensorFlow, HuggingFace, scikit-learn, XGBoost, LightGBM 🧠 ML & AI Ecosystem Transformers, RNNs, CNNs, CRFs BERT, RoBERTa, GPT-style models OpenAI API, Cohere, LLaMA, Mistral, Anthropic Claude FAISS, Pinecone, Qdrant, LlamaIndex ☁️ Deployment & Infrastructure Docker, Kubernetes, GitHub Actions, Jenkins AWS (EC2, Lambda, S3, SageMaker), GCP, Azure Redis, PostgreSQL, MongoDB 📊 Monitoring & Experimentation MLflow, Weights & Biases, TensorBoard, Prometheus, Grafana 👨‍💼 Qualifications🎓 Education Bachelor’s or Master’s degree in CS, AI, Statistics, or related quantitative disciplines. Certifications in advanced ML, data science, or AI are a plus. 🧑‍💻 Experience 4–8 years of hands-on experience in applied machine learning. Demonstrated success in deploying models to production at scale. Deep familiarity with transformer-based architectures and model evaluation. ✅ You’ll Excel In This Role If You… Thrive on solving end-to-end ML problems — not just notebooks, but deployment, testing, and iteration. Obsess over clean, maintainable, reusable code and pipelines. Think from first principles and challenge model assumptions when they don’t work. Are deeply curious and have built multiple projects just because you wanted to know how something works. Are comfortable working with ambiguity, fast timelines, and real-time data challenges. Want to build AI products that get used by real people and drive revenue outcomes — not just vanity demos. 💼 What You’ll Get at Darwix AI Work with some of the brightest minds in AI , product, and design. Solve AI problems that push the boundaries of real-time, voice-first, multilingual enterprise use cases. Direct mentorship from senior architects and AI scientists. Competitive compensation (₹30L–₹45L CTC) + ESOPs + rapid growth trajectory. Opportunity to shape the future of a global-first AI startup built from India. Hands-on experience with the most advanced tech stack in applied ML and production AI. Front-row seat to a generational company that is redefining enterprise AI. 📩 How to Apply Ready to build with us? Send your resume, GitHub/portfolio, and a short write-up on: “What’s the most interesting ML system you’ve built — and what made it work?” Email: people@darwix.ai Subject: Senior ML Engineer – Application 🔐 Final Notes We value speed, honesty, and humility. We ship fast, fail fast, and learn even faster. This role is designed for high-agency, hands-on ML engineers who want to make a difference — not just write code. If you’re looking for a role where you own real impact , push technical boundaries, and work with a team that’s as obsessed with AI as you are — then Darwix AI is the place for you. Darwix AI – GenAI for Revenue Teams. Built from India, for the World.

Dreaming big is in our DNA. It’s who we are as a company. It’s our culture. It’s our heritage. And more than ever, it’s our future. A future where we’re always looking forward. Always serving up new ways to meet life’s moments. A future where we keep dreaming bigger. We look for people with passion, talent, and curiosity, and provide them with the teammates, resources and opportunities to unleash their full potential. The power we create together – when we combine your strengths with ours – is unstoppable. Are you ready to join a team that dreams as big as you do? AB InBev GCC was incorporated in 2014 as a strategic partner for Anheuser-Busch InBev. The center leverages the power of data and analytics to drive growth for critical business functions such as operations, finance, people, and technology. The teams are transforming Operations through Tech and Analytics. Do You Dream Big? We Need You. Job Description Job Title: Senior Data Scientist Location: Bangalore Reporting to: Senior Manager Analytics Purpose of the role We seek a highly skilled Senior Machine Learning Engineer / Senior Data Scientist to design, develop, and deploy advanced machine learning models and systems. The ideal candidate will have deep expertise in machine learning algorithms, data processing, and model deployment, with a proven track record of delivering scalable AI solutions in production environments. This role requires strong technical leadership, collaboration with cross-functional teams, and a passion for solving complex problems. Key tasks & accountabilities Model Development: Design, develop, and optimize machine learning models for various applications, including but not limited to natural language processing, computer vision, and predictive analytics. Data Pipeline Management: Build and maintain robust data pipelines for preprocessing, feature engineering, and data augmentation to support model training and evaluation. Model Deployment: Deploy machine learning models into production environments, ensuring scalability, reliability, and performance using tools like Docker, Kubernetes, or cloud platforms preferably Azure. Research and Innovation: Stay updated on the latest advancements in machine learning and AI, incorporating state-of-the-art techniques into projects to improve performance and efficiency. Collaboration: Work closely with data scientists, software engineers, product managers, and other stakeholders to translate business requirements into technical solutions. Performance Optimization: Monitor and optimize model performance, addressing issues like model drift, bias, and scalability challenges. Code Quality: Write clean, maintainable, and well-documented code, adhering to best practices for software development and version control (e.g., Git). Mentorship: Provide technical guidance and mentorship to junior engineers, fostering a culture of learning and innovation within the team. Qualifications, Experience, Skills Level Of Educational Attainment Required Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, or a related field. PhD is a plus. Previous Work Experience 5+ years of experience in machine learning, data science, or a related field. Proven experience in designing, training, and deploying machine learning models in production. Hands-on experience with cloud platforms (AWS, GCP, Azure) and containerization technologies (Docker, Kubernetes). Technical Skills Required Proficiency in Python and libraries/frameworks such as TensorFlow, PyTorch, Scikit-learn, or Hugging Face. Strong understanding of machine learning algorithms (e.g., regression, classification, clustering, deep learning, reinforcement learning, optimization). Experience with big data technologies (e.g., Hadoop, Spark, or similar) and data processing pipelines. Familiarity with MLOps practices, including model versioning, monitoring, and CI/CD for ML workflows. Knowledge of software engineering principles, including object-oriented programming, API development, and microservices architecture. Other Skills Required Strong problem-solving and analytical skills. Excellent communication and collaboration abilities. Ability to work in a fast-paced, dynamic environment and manage multiple priorities. Experience with generative AI models or large language models (LLMs). Familiarity with distributed computing or high-performance computing environments. And above all of this, an undying love for beer! We dream big to create future with more cheers

About the Company: Crenovent Technologies is the developer of RevAi Pro — an AI-native revenue operations platform that brings together pipeline visibility, forecasting governance, AI-driven meeting intelligence, and CRM + communication integration. The platform serves large software, BFSI, and insurance companies with advanced automation and governance capabilities. Role Overview: We are hiring a Senior QA Automation Engineer to take end-to-end ownership of testing and quality assurance for our RevAi Pro platform. You will be responsible for developing and maintaining the automation test suite, validating our complex workflows, enforcing governance policies in test environments, and ensuring high confidence in every release. Key Responsibilities: Design and implement automation test suites using Cypress, Playwright, or Selenium. Build and maintain API test libraries using Postman, REST Assured, or Newman. Validate role-based access control (RBAC) and row-level security (RLS) functionality across multi-tenant user hierarchies. Automate core workflows including OrgImport, Cruxx task routing, Forecast module, and AI agent triggers. Integrate testing pipelines into GitHub Actions or Azure DevOps for pre-merge checks, ring-based rollouts, and regression runs. Create and maintain a traceability matrix mapping user stories to test cases and coverage reports. Perform non-functional testing including performance (using k6), accessibility (WCAG 2.1 with axe-core), and basic security scanning (OWASP ZAP, Trivy). Build test cases for CRM integration flows involving Salesforce, HubSpot, and Microsoft Teams with OAuth, webhook replay, and sync drift validation. Simulate AI-based workflows from meeting summary to Cruxx creation to governance-triggered escalations. Own regression coverage across modules including Action Center, Dashboard views, Compensation Planning, and Agent Orchestration. Provide reliable test data and stable test environments for feature development and UAT. Requirements: Minimum 5 years experience in quality engineering with at least 3 years in automation roles. Hands-on experience with Cypress or Playwright for UI automation. Strong API testing skills using Postman or REST Assured. Deep understanding of access control models (RBAC/RLS) and multi-tenant SaaS architecture. Experience with continuous integration pipelines and automated testing workflows. Clear communication, strong analytical thinking, and meticulous attention to edge cases and regression risks. Proven ability to build stable and scalable automated test frameworks across frontend, backend, and integration boundaries. Preferred Qualifications: Experience testing AI/ML-based workflows or LLM-driven product flows. Familiarity with CRM schema (Salesforce, HubSpot, Zoho) and communication platforms (Teams, Gmail). Knowledge of feature flag testing and progressive delivery. Exposure to infrastructure-level testing (Terraform plan validation, Kubernetes health). Tools and Technologies Used: Cypress, Playwright, Selenium Postman, REST Assured, Newman GitHub Actions, Azure DevOps Jira, Xray/Zephyr k6, axe-core, OWASP ZAP Mixpanel, Grafana, Sentry Success Metrics: ≥ 90% regression coverage across core workflows < 0.1 escaped critical bugs (P1/P2) per month ≥ 20 test stories automated per sprint 95%+ pipeline reliability across CI/CD stages

Company Description OpenBlockAI is India’s first AI + Blockchain-powered compliance platform revolutionizing the fight against financial crimes. We are building a real-time AML (Anti-Money Laundering) infrastructure designed for banks, fintechs, and government ecosystems. Our hybrid AI + Blockchain solution enables real-time fraud detection, transaction monitoring, and regulatory intelligence—before money laundering happens. Backed by a product-first vision, OpenBlockAI is co-founded by experienced entrepreneurs and is in active conversations with leading banks and regulatory bodies. We are now looking for a CTO with deep tech expertise and vision to lead the engineering and innovation roadmap. Role Description We are seeking a Chief Technology Officer (CTO) to join our founding team and lead the end-to-end technology strategy of a next-gen AI and blockchain platform built for the financial sector. The ideal candidate is a hands-on technology leader with a strong engineering foundation, start-up experience, and a passion for building innovative, secure, and scalable products. Your Responsibilities Will Include: Define and execute the long-term technical vision and architecture. Build and lead a high-performing engineering and AI/ML team. Design and oversee a secure, scalable, and modular cloud-native infrastructure. Drive development and deployment of AI/ML systems, blockchain frameworks, and real-time APIs. Ensure robust implementation of MFA, IAM, authorization, and secure communication protocols. Collaborate cross-functionally with product, compliance, and business stakeholders. Stay abreast of evolving regulatory technologies and ensure tech compliance readiness. Qualifications: 5+ years of proven experience in AI/ML, Blockchain, or Fintech architecture . Strong hands-on background in: Node.js , PostgreSQL , MongoDB AWS infrastructure, Docker , Kubernetes Deep understanding of AI model lifecycle , including: Model training and deployment REST/GraphQL prediction APIs Feedback collection and versioning Model drift detection and explainability Hands-on expertise with blockchain frameworks such as Ethereum , Hyperledger , or similar. Familiarity with data security , compliance standards , and regulatory frameworks (e.g., RBI, GDPR, ISO/PCI). Strong grasp of system design , distributed architecture , and DevSecOps best practices. Excellent communication, leadership, and decision-making abilities. Preferred (Good to Have): Exposure to RegTech, AML/KYC compliance, or banking infrastructure. Experience scaling products in multi-tenant or SaaS environments. Contributions to open-source, patents, or published research in AI or blockchain. Compensation: Equity-based role

The people here at Apple don’t just build products - we craft the kind of wonder that’s revolutionized entire industries. It’s the diversity of those people and their ideas that supports the innovation that runs through everything we do, from amazing technology to industry-leading environmental efforts. Join Apple, and help us leave the world better than we found it. The Global Business Intelligence team provides data services, analytics, reporting, and data science solutions to Apple’s business groups, including Retail, iTunes, Marketing, AppleCare, Operations, Finance, and Sales. These solutions are built on top of an end-to-end machine learning platform with sophisticated AI capabilities. We are looking for a competent, experienced, and driven machine learning engineer to define and build some of the best-in-class machine learning solutions and tools for Apple. Description As a Machine Learning Engineer, you will work on building intelligent systems to democratize AI across a wide range of solutions within Apple. You will drive the development and deployment of innovative AI models and systems that directly impact the capabilities and performance of Apple’s products and services. You will implement robust, scalable ML infrastructure, including data storage, processing, and model serving components, to support seamless integration of AI/ML models into production environments. You will develop novel feature engineering, data augmentation, prompt engineering and fine-tuning frameworks that achieve optimal performance on specific tasks and domains. You will design and implement automated ML pipelines for data preprocessing, feature engineering, model training, hyper-parameter tuning, and model evaluation, enabling rapid experimentation and iteration. You will also implement advanced model compression and optimization techniques to reduce the resource footprint of language models while preserving their performance. Have continuous focus to Brainstorm and Design various POCs using AI/ML Services for new or existing enterprise problems. YOU SHOULD BE ABLE TO: - Understand a business challenge - Collaborate with business and other multi-functional teams - Design a statistical or deep learning solution to find the needed answer to it. - Develop it by yourself or guide another person to do it. - Deliver the outcome into production, (v) Keep a good governance of your work. There are meaningful opportunities for you deliver impactful influences to Apple. Key Qualifications 4+ years of ML engineering experience in feature engineering, model training, model serving, model monitoring and model refresh management Experience developing AI/ML systems at scale in production or in high-impact research environments Passionate about computer vision, natural language processing, especially in LLMs and Generative AI systems Knowledge with the common frameworks and tools such as PyPorch or TensorFlow Experience with transformer models such as BERT, GPT etc. and understanding of their underlying principles is a plus Strong coding, analytical, software engineering skills, and familiarity with software engineering principles around testing, code reviews and deployment Experience in handling performance, application and security log management Applied knowledge of statistical data analysis, predictive modeling classification, Time Series techniques, sampling methods, multivariate analysis, hypothesis testing, and drift analysis. Proficiency in programming languages and tools like Python, R, Git, Airflow, Notebooks. Experience with data visualization tools like matplotlib, d3.js., Tableau would be a plus Education & Experience Bachelor’s Degree or Equivalent experience Submit CV

QA Tester – Machine Learning Experience: 1–2 Years Location: Netaji Subhash Place, Delhi Employment Type: Full-time Job Summary: We are looking for a passionate and detail-oriented QA Tester with 1–2 years of experience to join our AI team. In this role, you will work closely with AI-ML engineers and software developers to ensure the quality and reliability of ML models, data pipelines, and model-integrated applications. Key Responsibilities: Design, develop, and execute test plans and test cases for ML models and data pipelines. Validate model outputs against ground truth datasets, with a focus on evaluating classification performance metrics like accuracy, precision, recall, F1-score, and ROC-AUC. Perform functional, regression, and integration testing for applications incorporating ML models. Collaborate with ML engineers to ensure testability and performance of models. Write scripts to automate model testing and data validation. Identify, record, document, and track bugs and model anomalies. Ensure data quality and consistency in training and inference pipelines. Test and validate APIs serving ML models in production. Contribute to continuous improvement of QA processes and tools. Required Skills & Qualifications: Bachelor’s degree in Computer Science, Engineering, or a related field. 1–2 years of experience in QA/testing roles, preferably in ML or data-heavy environments. Solid understanding of QA methodologies, tools, and processes. Experience in testing REST APIs and working with tools like Postman or Swagger. Basic knowledge of Python, with experience in test automation using PyTest or similar frameworks. Familiarity with ML concepts and Docker. Hands-on experience working with structured/unstructured datasets. Ability to write clear, concise, and comprehensive test cases and test reports. Preferred Qualifications: Experience with ML libraries like scikit-learn, TensorFlow, or PyTorch. Exposure to data annotation, labeling, or synthetic data generation tools. Familiarity with version control systems (e.g., Git) and CI/CD workflows. Knowledge of SQL or MongoDB for data validation. Understanding of data drift, model degradation, and ML lifecycle monitoring. Why Join Us? Work on real-world ML products with a measurable impact. Collaborate with a dynamic and skilled team. Opportunity to grow in both QA and ML domains. Flexible work environment and supportive culture. Job Type: Full-time Pay: ₹20,000.00 - ₹30,000.00 per month Benefits: Health insurance Provident Fund Work Location: In person Speak with the employer +91 8178295650

QA Tester – Machine Learning Experience: 1–2 Years Location: Netaji Subhash Place, Delhi Employment Type: Full-time Job Summary: We are looking for a passionate and detail-oriented QA Tester with 1–2 years of experience to join our AI team. In this role, you will work closely with AI-ML engineers and software developers to ensure the quality and reliability of ML models, data pipelines, and model-integrated applications. Key Responsibilities: Design, develop, and execute test plans and test cases for ML models and data pipelines. Validate model outputs against ground truth datasets, with a focus on evaluating classification performance metrics like accuracy, precision, recall, F1-score, and ROC-AUC. Perform functional, regression, and integration testing for applications incorporating ML models. Collaborate with ML engineers to ensure testability and performance of models. Write scripts to automate model testing and data validation. Identify, record, document, and track bugs and model anomalies. Ensure data quality and consistency in training and inference pipelines. Test and validate APIs serving ML models in production. Contribute to continuous improvement of QA processes and tools. Required Skills & Qualifications: Bachelor’s degree in Computer Science, Engineering, or a related field. 1–2 years of experience in QA/testing roles, preferably in ML or data-heavy environments. Solid understanding of QA methodologies, tools, and processes. Experience in testing REST APIs and working with tools like Postman or Swagger. Basic knowledge of Python, with experience in test automation using PyTest or similar frameworks. Familiarity with ML concepts and Docker. Hands-on experience working with structured/unstructured datasets. Ability to write clear, concise, and comprehensive test cases and test reports. Preferred Qualifications: Experience with ML libraries like scikit-learn, TensorFlow, or PyTorch. Exposure to data annotation, labeling, or synthetic data generation tools. Familiarity with version control systems (e.g., Git) and CI/CD workflows. Knowledge of SQL or MongoDB for data validation. Understanding of data drift, model degradation, and ML lifecycle monitoring. Why Join Us? Work on real-world ML products with a measurable impact. Collaborate with a dynamic and skilled team. Opportunity to grow in both QA and ML domains. Flexible work environment and supportive culture. Job Type: Full-time Pay: ₹20,000.00 - ₹30,000.00 per month Benefits: Health insurance Provident Fund Work Location: In person Speak with the employer +91 8178295650

Job Type: Contractual - Full-time (3-5 months) - Very high chances to a full-time transition. Location: Remote About us: At Kan’s Technologies Global, our mission is to develop the most advanced solutions, products, and platforms that drive business growth, solve real-world challenges, and catalyze innovation across industries worldwide. We specialize in building custom AI/NLP/ML solutions, including Conversational AI, Predictive Analytics, Demand Forecasting, and more empowering organizations to stay ahead in an increasingly digital world. What fuels us? Innovation and Value Creation Role Summary: We are seeking a dynamic and experienced Project Manager with a strong background in managing cross-functional technology teams within the healthcare domain. The ideal candidate will be responsible for overseeing the end-to-end planning, execution, and delivery of healthcare IT projects. This role involves leading a team comprising UI/UX designers, Machine Learning engineers, and Fullstack + Backend developers to ensure timely delivery, quality assurance, and alignment with client and organizational goals. The candidate should bring a structured and proactive approach, leveraging modern project management tools and healthcare domain knowledge to drive success. Roles & Responsibilities: Collaborate with product and engineering teams to identify, extract, and engineer relevant features from diverse datasets to enhance model performance. Research and recommend appropriate machine learning algorithms and statistical techniques for prediction, classification, and optimization tasks within the healthcare domain. Deploy trained models as scalable, low-latency inference endpoints using Azure Machine Learning. Work with DevOps to establish robust MLOps practices for model versioning, monitoring, and continuous retraining. Work closely with Full-Stack and DevOps Engineers to ensure efficient data ingestion from various sources into Azure databases. Perform exploratory data analysis (EDA) to uncover insights, identify trends, and understand data quality. Present findings and model performance clearly to technical and non-technical stakeholders. Monitor the performance and drift of deployed models, ensuring their continued accuracy and relevance. Recommend and implement strategies for model retraining and improvement. Actively contribute to the rapid development and iteration of the MVP, ensuring the ML components are robust, performant, and deliver tangible value. Maintain clear and comprehensive documentation for models, data pipelines, and algorithms. Mandatory Qualifications: Bachelor's degree in Computer Science, IT, Engineering, Healthcare Informatics, or related field Minimum 10 years of project management experience At least 3 years of experience in healthcare or healthtech domain Experience managing cross-functional tech teams (UI/UX, ML, Fullstack + Backend) Proficiency in Agile/Scrum methodologies Hands-on with Jira, Confluence, Slack, Trello/ClickUp, Figma, GitHub/GitLab, Google Workspace Strong communication skills (written and verbal) Strong documentation and reporting skills Preferred Qualifications: PMP, PRINCE2, or Scrum Master (CSM) certification Knowledge of HIPAA, HL7, FHIR, or GDPR in healthcare Basic technical understanding of APIs, ML models, UI/UX workflows, and DevOps, Microsoft Azure Experience in delivering healthcare IT projects (EHR/EMR, patient platforms) Direct client-facing experience in tech project delivery Comfortable managing teams across different time zones What you'll gain: Opportunity to work with international clients and real-world industry problems. Collaborative environment with a team focused on innovation and impact. Performance-based incentives and career growth opportunities. Flexible work structure (remote-first culture). Note: (Compensation Range: upto 13 Lakhs INR per annum), based on experience. At Kan's Technologies Global, we are committed to fostering a diverse and inclusive environment, where everyone is treated with respect and given equal opportunities, regardless of race, gender, religion, or any other characteristic. Discrimination of any kind is not tolerated, and we strive to create a workplace where all individuals can thrive.

At ZoomInfo, we encourage creativity, value innovation, demand teamwork, expect accountability and cherish results. We value your take charge, take initiative, get stuff done attitude and will help you unlock your growth potential. One great choice can change everything. Thrive with us at ZoomInfo. About the role: The Solution Consulting team at ZoomInfo is made up of solution experts focused on enabling our customers and prospects to maximize the value that they get out of our solutions. We are problem solvers and strategic thinkers that are obsessed with making our customers successful. We sit at the intersection of Sales, Customer Success, Product Marketing, Product Management, and Engineering and work collaboratively with each to continue to drive value for our customers. We are a team of solution consultants that are customer centric and we believe in the value we can add and stay honest about it. We love to learn, are open to giving and receiving feedback and are passionate about making our clients successful. We build trust and confidence with customers by mapping use cases, business objectives, and requirements to innovative solutions to solve complex problems that significantly impact our customers' success. What You'll Do: Partner with AE’s and AM’s to discover customer needs and design solutions to solve complex customer challenges. Be the expert that articulates our solution capabilities through solution demonstrations anchored in the context of customer need and value Lead the technical aspects of the solution and customer evaluations while ensuring a memorable experience and delivering value to ensure the technical win Track and raise feature requests while collaborating closely with product management and engineering teams. Enhancements/capabilities and competitive intel What You Bring: Bachelors / Maters in Science Or Engineering 3 to 5 years of experience as presales solution consulting or technical sales experience in SaaS or enterprise technology space Shift : Mandatory to work in 5 PM to 2 AM IST Self-starter and team player that excels working in an unstructured environment and can quickly grasp technical concepts Customer obsessed mindset with a knack for understanding and solving problems using technology solutions Outstanding problem-solving skills, including the ability to meet a business requirement with a technical solution Proficient in delivering software demonstrations in-person and virtually Excellent interpersonal, communication, persuasion, presentation and writing skills Experience with technical business documentation like workflow diagrams, proposals, SOWs, RFPs and RFIs, etc. Proven experience working with employees at all levels of an organization Previous experience designing solutions in a platform/multi product environment Experience with Demo2Win and Value Selling Methodologies Experience selling into Sales/Marketing/Data Ops, Sales Leadership, Data Science, and Marketing Experience working in Conversation Intelligence (Chorus, Gong), Sales Automation (ZI Engage, Salesloft, Outreach), Chat (ZI Chat, Drift), or ABM/Marketing Automation (6Sense, DemandBase, Marketo, Eloqua, Pardot) Experience in selling SAAS sales or marketing technology platforms that are feature rich and have numerous use cases across different types of customers and prospects Prior experience using or integrating with CRM systems such as Salesforce.com, Microsoft Dynamics, Hubspot, or Marketing Automation systems such as Marketo, Eloqua, Pardot Experience with recommending and demonstrating software solutions that have numerous applications to business leaders, to solve critical business challenges About us: ZoomInfo (NASDAQ: GTM) is the Go-To-Market Intelligence Platform that empowers businesses to grow faster with AI-ready insights, trusted data, and advanced automation. Its solutions provide more than 35,000 companies worldwide with a complete view of their customers, making every seller their best seller. ZoomInfo may use a software-based assessment as part of the recruitment process. More information about this tool, including the results of the most recent bias audit, is available here. ZoomInfo is proud to be an equal opportunity employer, hiring based on qualifications, merit, and business needs, and does not discriminate based on protected status. We welcome all applicants and are committed to providing equal employment opportunities regardless of sex, race, age, color, national origin, sexual orientation, gender identity, marital status, disability status, religion, protected military or veteran status, medical condition, or any other characteristic protected by applicable law. We also consider qualified candidates with criminal histories in accordance with legal requirements. For Massachusetts Applicants: It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability. ZoomInfo does not administer lie detector tests to applicants in any location.

About The Role We are looking for a Senior Data Scientist to lead the design and development of intelligent, data-driven systems that power talent discovery, candidate-job matching, and workforce insights. In this role, you'll build and deploy models that process unstructured data at scale, extract actionable insights, and deliver real-time recommendations to enhance decision-making across the talent lifecycle. If you're passionate about building smart systems that solve real-world problems in the intersection of data, people, and technology this is your calling. Key Responsibilities Build and optimize machine learning models for use cases like candidate-job matching, resume parsing, talent ranking, recommendation systems, and profile enrichment. Apply NLP techniques to extract and analyze insights from large volumes of unstructured data (resumes, job descriptions, interviews, etc.). Lead experimentation efforts including A/B testing, model comparisons, and business metric evaluation. Collaborate with product, engineering, and data teams to productionize ML pipelines and ensure model reliability at scale. Develop interpretable models and frameworks that deliver explainable AI (XAI) capabilities. Identify and evaluate data sources (internal & external) for enhancing model performance and domain coverage. Design and maintain systems to monitor model drift, retraining workflows, and feature performance in production. Must-Have Skills 5+ years of hands-on experience in data science or machine learning roles, ideally in search, recommendation, or NLP-focused systems. Strong proficiency in Python, including packages like scikit-learn, spaCy, transformers, pandas, NumPy, TensorFlow, or PyTorch. Experience with natural language processing (NLP), including named entity recognition, embeddings, text classification, and semantic search. Solid experience working with structured and unstructured data, and building scalable data pipelines. Strong command over SQL and experience with distributed data systems (e.g., Snowflake, BigQuery). Demonstrated experience taking models from experimentation to production, with clear metrics and monitoring in place. Excellent problem-solving and communication skills with the ability to work Skills : Knowledge of recommendation engines, graph-based models, or search ranking algorithms. Exposure to cloud platforms like AWS, Azure, or GCP, and MLOps workflows (CI/CD for models). Experience in talent tech, HR tech, or recruitment intelligence platforms is a strong plus. Familiarity with vector databases, embeddings, and semantic similarity search. (ref:hirist.tech)

Candidates ready to join immediately can share their details via email for quick processing. 📌 CCTC | ECTC | Notice Period | Location Preference nitin.patil@ust.com Act fast for immediate attention! ⏳📩 Roles and Responsibilities: Architecture & Infrastructure Design Architect scalable, resilient, and secure AI/ML infrastructure on AWS using services like EC2, SageMaker, Bedrock, VPC, RDS, DynamoDB, CloudWatch . Develop Infrastructure as Code (IaC) using Terraform , and automate deployments with CI/CD pipelines . Optimize cost and performance of cloud resources used for AI workloads. AI Project Leadership Translate business objectives into actionable AI strategies and solutions. Oversee the entire AI lifecycle —from data ingestion, model training, and evaluation to deployment and monitoring. Drive roadmap planning, delivery timelines, and project success metrics. Model Development & Deployment Lead selection and development of AI/ML models, particularly for NLP, GenAI, and AIOps use cases . Implement frameworks for bias detection, explainability , and responsible AI . Enhance model performance through tuning and efficient resource utilization. Security & Compliance Ensure data privacy, security best practices, and compliance with IAM policies, encryption standards , and regulatory frameworks. Perform regular audits and vulnerability assessments to ensure system integrity. Team Leadership & Collaboration Lead and mentor a team of cloud engineers, ML practitioners, software developers, and data analysts. Promote cross-functional collaboration with business and technical stakeholders. Conduct technical reviews and ensure delivery of production-grade solutions. Monitoring & Maintenance Establish robust model monitoring , ing , and feedback loops to detect drift and maintain model reliability. Ensure ongoing optimization of infrastructure and ML pipelines. Must-Have Skills: 10+ years of experience in IT with 4+ years in AI/ML leadership roles. Strong hands-on experience in AWS services : EC2, SageMaker, Bedrock, RDS, VPC, DynamoDB, CloudWatch. Expertise in Python for ML development and automation. Solid understanding of Terraform, Docker, Git , and CI/CD pipelines . Proven track record in delivering AI/ML projects into production environments . Deep understanding of MLOps, model versioning, monitoring , and retraining pipelines . Experience in implementing Responsible AI practices – including fairness, explainability, and bias mitigation. Knowledge of cloud security best practices and IAM role configuration. Excellent leadership, communication, and stakeholder management skills. Good-to-Have Skills: AWS Certifications such as AWS Certified Machine Learning – Specialty or AWS Certified Solutions Architect. Familiarity with data privacy laws and frameworks (GDPR, HIPAA). Experience with AI governance and ethical AI frameworks. Expertise in cost optimization and performance tuning for AI on the cloud. Exposure to LangChain , LLMs , Kubeflow , or GCP-based AI services . Skills Enterprise Architecture,Enterprise Architect,Aws,Python

Gen-AI Tech Lead - Enterprise AI Applications About Us We're a cutting-edge technology company building enterprise-grade AI solutions that transform how businesses operate. Our platform leverages the latest in Generative AI to create intelligent applications for document processing, automated decision-making, and knowledge management across industries. Role Overview We're seeking an exceptional Gen-AI Tech Lead to architect, build, and scale our next-generation AI-powered enterprise applications. You'll lead the technical strategy for implementing Large Language Models, fine-tuning custom models, and deploying production-ready AI systems that serve millions of users. Key Responsibilities - AI/ML Leadership (90% Hands-on) Design and implement enterprise-scale Generative AI applications using custom LLMs or (GPT, Claude, Llama, Gemini) Lead fine-tuning initiatives for domain-specific models and custom use cases Build and optimize model training pipelines for large-scale data processing Develop RAG (Retrieval-Augmented Generation) systems with vector databases and semantic search Implement prompt engineering strategies and automated prompt optimization Create AI evaluation frameworks and model performance monitoring systems Enterprise Application Development Build scalable Python applications integrating multiple AI models and APIs Develop microservices architecture for AI model serving and orchestration Implement real-time AI inference systems with sub-second response times Design fault-tolerant systems with fallback mechanisms and error handling Create APIs and SDKs for enterprise AI integration Build AI model version control and A/B testing frameworks MLOps & Infrastructure Containerize AI applications using Docker and orchestrate with Kubernetes Design and implement CI/CD pipelines for ML model deployment Set up model monitoring, drift detection, and automated retraining systems Optimize inference performance and cost efficiency in cloud environments Implement security and compliance measures for enterprise AI applications Technical Leadership Lead a team of 3-5 AI engineers and data scientists Establish best practices for AI development, testing, and deployment Mentor team members on cutting-edge AI technologies and techniques Collaborate with product and business teams to translate requirements into AI solutions Drive technical decision-making for AI architecture and technology stack Required Skills & Experience Core AI/ML Expertise Python : 5+ years of production Python development with AI/ML libraries LLMs : Hands-on experience with GPT-4, Claude, Llama 2/3, Gemini, or similar models Fine-tuning : Proven experience fine-tuning models using LoRA, QLoRA, or full parameter tuning Model Training : Experience training models from scratch or continued pre-training Frameworks : Expert-level knowledge of PyTorch, TensorFlow, Hugging Face Transformers Vector Databases : Experience with Pinecone, Weaviate, ChromaDB, or Qdrant Technical StackAI/ML Stack Models : OpenAI GPT, Anthropic Claude, Meta Llama, Google Gemini Frameworks : PyTorch, Hugging Face Transformers, LangChain, LlamaIndex Training : Distributed training with DeepSpeed, Accelerate, or Fairscale Serving : vLLM, TensorRT-LLM, or Triton Inference Server Vector Search : Pinecone, Weaviate, FAISS, Elasticsearch Infrastructure & DevOps Containerization : Docker, Kubernetes, Helm charts Cloud : AWS (ECS, EKS, Lambda, SageMaker), GCP Vertex AI Databases : PostgreSQL, MongoDB, Redis, Neo4j Monitoring : Prometheus, Grafana, DataDog, MLflow CI/CD : GitHub Actions, Jenkins, ArgoCD Professional Growth Work directly with founders and C-level executives Opportunity to publish research and speak at AI conferences Access to latest AI models and cutting-edge research Mentorship from industry experts and AI researchers Budget for attending top AI conferences (NeurIPS, ICML, ICLR) Ideal Candidate Profile Passionate about pushing the boundaries of AI technology Strong engineering mindset with focus on production systems Experience shipping AI products used by thousands of users Stays current with latest AI research and implements cutting-edge techniques Excellent problem-solving skills and ability to work under ambiguity Leadership experience in fast-paced, high-growth environments Apply now and help us democratize AI for enterprise customers worldwide. Job Type: Full-time Pay: ₹900,000.00 - ₹1,600,000.00 per year Schedule: Monday to Friday Supplemental Pay: Performance bonus

Join our Team About this opportunity: At Ericsson, you can be a game changer! Because working here isn’t just a deal. It’s a big deal. This means that you get to leverage our 140+ years of experience & the expertise of more than 95,000 diverse colleagues worldwide. As part of our team, you will help solve some of society´s most complicated challenges, enabling you to be ‘the person that did that.’ We’ve never had a greater opportunity to inspire change; setting the bar for technology to be inclusive & accessible; empowering a hard-working, sustainable, & connected world. What you will do End-to-end administration and operations of CNIS platforms including Kubernetes, container runtimes, and cloud-native infrastructure components. Manage and optimize Cloud Container Distribution (CCD), covering provisioning, upgrades, backup/restore, lifecycle management, and disaster recovery readiness. Perform CCD health checks, configuration drift analysis, capacity tracking, and environment validation across clusters. Work closely with app and platform teams to onboard workloads and provide CCD-level support. Monitor system performance and availability using tools like Prometheus, Grafana, and other tools Ensure compliance with security, governance, and operational policies. Participate in and lead DR planning, execution, and RCA of major incidents. Maintain detailed runbooks, MOPs, and CNIS documentation for operational readiness. Monitor SDI health and performance, resolve bottlenecks, and ensure seamless integration with CNIS layers. Good troubleshooting experience with CNIS components Expertise in Red Hat Enterprise Linux (RHEL) system administration and troubleshooting. Hardware troubleshooting experience on HP ProLiant, Dell PowerEdge servers. Patch management, firmware upgrades, and OS-level tuning Strong hands-on experience with Juniper and Extreme Networks switches. Switch boot process, firmware upgrades, backup/restore, Border leaf switch management and troubleshooting Familiarity with traffic filtering, isolation, and multi-tenant CNIS network architecture. Configuration of VLANs, trunking, port profiles (access/trunk), and ACLs Strong knowledge on CEPH Storage administration and troubleshooting The skills you bring: 10+ years of Experience is supporting & managing business critical operations. In depth knowledge & working experience on Linux Administration. In depth knowledge & working experience on Dockers, Kubernetes & any other cloud platform. Troubleshooting & Debugging skills to find issues. Understanding of SDN and integration with container networking layers (e.g., Calico). Familiarity with traffic filtering, isolation, and multi-tenant CNIS network architecture. Switch boot process, firmware upgrades, backup/restore, Border leaf switch management and troubleshooting. Configuration of VLANs,trucking, port profiles (access/trunk), and ACLs Performance analysis, component replacement, switch stacking, and chassis management. Certifications Preferred: CKA / CKAD / CKS – Kubernetes certifications Red Hat Certified System Administrator (RHCSA/RHCE) Networking certifications (Juniper/Extreme/SDN) ITIL Foundation (preferred in process-driven environments) Why join Ericsson? At Ericsson, you´ll have an outstanding opportunity. The chance to use your skills and imagination to push the boundaries of what´s possible. To build solutions never seen before to some of the world’s toughest problems. You´ll be challenged, but you won’t be alone. You´ll be joining a team of diverse innovators, all driven to go beyond the status quo to craft what comes next. What happens once you apply? Click Here to find all you need to know about what our typical hiring process looks like. Encouraging a diverse and inclusive organization is core to our values at Ericsson, that's why we champion it in everything we do. We truly believe that by collaborating with people with different experiences we drive innovation, which is essential for our future growth. We encourage people from all backgrounds to apply and realize their full potential as part of our Ericsson team. Ericsson is proud to be an Equal Opportunity Employer. learn more. Primary country and city: India (IN) || Req ID: 770510

About the Role As a QA Intern, you will test and validate the behavior of GenAI bots. You'll work with our AI Agent that generates test scripts from PRDs and learn how to perform edge-case, adversarial, and regression testing for LLMs. Responsibilities Evaluate prompts across text, SQL, and voice bots Run test cycles for hallucination, drift, and response accuracy Create QA reports and feedback loops for agent behavior Work closely with the engineering team to flag issues Preferred Skills Passion for testing, precision, and quality Comfortable writing test cases or working with tools like Postman Familiarity with chatbots or LLMs a plus Preferred candidate profile Strong analytical & problem solving skill. Awareness of current trends in tech innovation & industry developments.

Company Description About Sutherland Artificial Intelligence. Automation.Cloud engineering. Advanced analytics.For business leaders, these are key factors of success. For us, they’re our core expertise. We work with iconic brands worldwide. We bring them a unique value proposition through market-leading technology and business process excellence. We’ve created over 200 unique inventions under several patents across AI and other critical technologies. Leveraging our advanced products and platforms, we drive digital transformation, optimize critical business operations, reinvent experiences, and pioneer new solutions, all provided through a seamless “as a service” model. For each company, we provide new keys for their businesses, the people they work with, and the customers they serve. We tailor proven and rapid formulas, to fit their unique DNA.We bring together human expertise and artificial intelligence to develop digital chemistry. This unlocks new possibilities, transformative outcomes and enduring relationships. Sutherland Unlocking digital performance. Delivering measurable results. Job Description We are looking for a proactive and detail-oriented AI OPS Engineer to support the deployment, monitoring, and maintenance of AI/ML models in production. Reporting to the AI Developer, this role will focus on MLOps practices including model versioning, CI/CD, observability, and performance optimization in cloud and hybrid environments. Key Responsibilities: Build and manage CI/CD pipelines for ML models using platforms like MLflow, Kubeflow, or SageMaker. Monitor model performance and health using observability tools and dashboards. Ensure automated retraining, version control, rollback strategies, and audit logging for production models. Support deployment of LLMs, RAG pipelines, and agentic AI systems in scalable, containerized environments. Collaborate with AI Developers and Architects to ensure reliable and secure integration of models into enterprise systems. Troubleshoot runtime issues, latency, and accuracy drift in model predictions and APIs. Contribute to infrastructure automation using Terraform, Docker, Kubernetes, or similar technologies. Qualifications Required Qualifications: 3–5 years of experience in DevOps, MLOps, or platform engineering roles with exposure to AI/ML workflows. Hands-on experience with deployment tools like Jenkins, Argo, GitHub Actions, or Azure DevOps. Strong scripting skills (Python, Bash) and familiarity with cloud environments (AWS, Azure, GCP). Understanding of containerization, service orchestration, and monitoring tools (Prometheus, Grafana, ELK). Bachelor’s degree in computer science, IT, or a related field. Preferred Skills: Experience supporting GenAI or LLM applications in production. Familiarity with vector databases, model registries, and feature stores. Exposure to security and compliance standards in model lifecycle management

Company Description About Sutherland Artificial Intelligence. Automation.Cloud engineering. Advanced analytics.For business leaders, these are key factors of success. For us, they’re our core expertise. We work with iconic brands worldwide. We bring them a unique value proposition through market-leading technology and business process excellence. We’ve created over 200 unique inventions under several patents across AI and other critical technologies. Leveraging our advanced products and platforms, we drive digital transformation, optimize critical business operations, reinvent experiences, and pioneer new solutions, all provided through a seamless “as a service” model. For each company, we provide new keys for their businesses, the people they work with, and the customers they serve. We tailor proven and rapid formulas, to fit their unique DNA.We bring together human expertise and artificial intelligence to develop digital chemistry. This unlocks new possibilities, transformative outcomes and enduring relationships. Sutherland Unlocking digital performance. Delivering measurable results. Job Description We are hiring a quality-focused AI Tester to design and execute validation frameworks for AI models and systems. Reporting to the AI Manager, this role ensures that AI solutions meet accuracy, performance, reliability, and ethical compliance benchmarks before production deployment. Key Responsibilities: Develop and execute test plans and cases for AI/ML models, GenAI solutions, and agent-based systems. Validate model outputs for accuracy, precision, recall, latency, and interpretability across diverse datasets. Conduct bias testing, data drift analysis, and adversarial robustness validation. Collaborate with AI developers, data scientists, and business analysts to define acceptance criteria. Automate testing pipelines and integrate with CI/CD environments where applicable. Maintain traceability matrices, defect logs, and model validation documentation. Qualifications Required Qualifications: 3–5 years of experience in software testing or QA, with at least 1–2 years in AI/ML or data-centric testing. Strong understanding of AI model evaluation metrics, data sampling, and validation techniques. Experience using testing frameworks (e.g., PyTest, Great Expectations) and visualization tools. Familiarity with Python, JSON, and REST APIs. Bachelor’s degree in Computer Science, Statistics, or a related field. Preferred Skills: Experience testing LLMs, GenAI prompts, or RAG workflows. Exposure to responsible AI frameworks and model audit practices. ISTQB or other QA certifications are a plus.

Join our Team About this opportunity: At Ericsson, you can be a game changer! Because working here isn’t just a deal. It’s a big deal. This means that you get to leverage our 140+ years of experience & the expertise of more than 95,000 diverse colleagues worldwide. As part of our team, you will help solve some of society´s most complicated challenges, enabling you to be ‘the person that did that.’ We’ve never had a greater opportunity to inspire change; setting the bar for technology to be inclusive & accessible; empowering a hard-working, sustainable, & connected world. What You Will Do End-to-end administration and operations of CNIS platforms including Kubernetes, container runtimes, and cloud-native infrastructure components. Manage and optimize Cloud Container Distribution (CCD), covering provisioning, upgrades, backup/restore, lifecycle management, and disaster recovery readiness. Perform CCD health checks, configuration drift analysis, capacity tracking, and environment validation across clusters. Work closely with app and platform teams to onboard workloads and provide CCD-level support. Monitor system performance and availability using tools like Prometheus, Grafana, and other tools Ensure compliance with security, governance, and operational policies. Participate in and lead DR planning, execution, and RCA of major incidents. Maintain detailed runbooks, MOPs, and CNIS documentation for operational readiness. Monitor SDI health and performance, resolve bottlenecks, and ensure seamless integration with CNIS layers. Good troubleshooting experience with CNIS components Expertise in Red Hat Enterprise Linux (RHEL) system administration and troubleshooting. Hardware troubleshooting experience on HP ProLiant, Dell PowerEdge servers. Patch management, firmware upgrades, and OS-level tuning Strong hands-on experience with Juniper and Extreme Networks switches. Switch boot process, firmware upgrades, backup/restore, Border leaf switch management and troubleshooting Familiarity with traffic filtering, isolation, and multi-tenant CNIS network architecture. Configuration of VLANs, trunking, port profiles (access/trunk), and ACLs Strong knowledge on CEPH Storage administration and troubleshooting The skills you bring: 10+ years of Experience is supporting & managing business critical operations. In depth knowledge & working experience on Linux Administration. In depth knowledge & working experience on Dockers, Kubernetes & any other cloud platform. Troubleshooting & Debugging skills to find issues. Understanding of SDN and integration with container networking layers (e.g., Calico). Familiarity with traffic filtering, isolation, and multi-tenant CNIS network architecture. Switch boot process, firmware upgrades, backup/restore, Border leaf switch management and troubleshooting. Configuration of VLANs,trucking, port profiles (access/trunk), and ACLs Performance analysis, component replacement, switch stacking, and chassis management. Certifications Preferred: CKA / CKAD / CKS – Kubernetes certifications Red Hat Certified System Administrator (RHCSA/RHCE) Networking certifications (Juniper/Extreme/SDN) ITIL Foundation (preferred in process-driven environments) Why join Ericsson? At Ericsson, you´ll have an outstanding opportunity. The chance to use your skills and imagination to push the boundaries of what´s possible. To build solutions never seen before to some of the world’s toughest problems. You´ll be challenged, but you won’t be alone. You´ll be joining a team of diverse innovators, all driven to go beyond the status quo to craft what comes next. What happens once you apply? Click Here to find all you need to know about what our typical hiring process looks like. Encouraging a diverse and inclusive organization is core to our values at Ericsson, that's why we champion it in everything we do. We truly believe that by collaborating with people with different experiences we drive innovation, which is essential for our future growth. We encourage people from all backgrounds to apply and realize their full potential as part of our Ericsson team. Ericsson is proud to be an Equal Opportunity Employer. learn more. Primary country and city: India (IN) || Req ID: 770510

We are building India's first commercial Scanning Electron Microscope (SEM) from the ground up. This is not an integration project. We will design our own electron optics, high-voltage systems, precision mechanics, and real-time control software. If the idea of turning first-principles physics into a manufacturable instrument excites you, read on. Your Mission Build the real-time beam controller on a Zynq Ultrascale+ (ARM+FPGA): Pixel clock ≤20 MHz with ±5 ns jitter; Blanking rise/fall <25 ns into 50 Ω Implement closed-loop stage control using high-resolution position feedback; update PID at 10 kHz. Stream 16-bit detector data at 250 MB/s over PCIe to host memory. Ship imaging algorithms: auto-focus, auto-stigmation, drift correction running at ≥5 fps. Provide a clean, documented Python API for scripting and automated metrology. Who You Are 6+ yrs C++17/C, Python, real-time Linux or RTOS; comfortable inside FPGA toolchains (Vivado, Verilog). Solid DSP & control theory background; not afraid of scope probes or logic analyzers. Bonus: prior work on SEM, TEM, or other charged-particle systems. Share the hardest technical problem you have solved and why Bharat Atomic's mission fires you up along with your CV and Portfolio.

We are building India's first commercial Scanning Electron Microscope (SEM) from the ground up. This is not an integration project. We will design our own electron optics, high-voltage systems, precision mechanics, and real-time control software. If the idea of turning first-principles physics into a manufacturable instrument excites you, read on. Your Mission Own the complete electron-optical column: thermionic source, condenser & objective lenses, SE/BSE detectors. Push a tungsten cathode to ≤10 nm resolution at 20 kV, while also delivering a stable, high-current beam (≥1 nA) for analytical work—among the best ever reported for a thermionic system. Minimise spherical and chromatic aberrations through iterative modelling (COMSOL / SIMION / Opera-3D) and hardware prototyping. Derive and flow down stability & alignment budgets to high-voltage and mechanical teams (≤1 µm source drift / 8 hr, ≤50 nm lens-to-lens decenter). Design modular, UHV-compatible lens stacks that can later accept a Schottky or cold-field upgrade without a full redesign. Who You Are PhD or 6+ yrs R&D in electron/ion optics, accelerator physics, or charged-particle instrumentation. Hands-on with high-vacuum hardware, electron guns, electrostatic/magnetic lens design. Fluent in at least one high-fidelity field solver (COMSOL, SIMION, CST). Comfort translating aberration theory into tolerance tables a machinist can hit. Share the hardest technical problem you have solved and why Bharat Atomic's mission fires you up along with your CV and Portfolio.