2043 Inference Jobs - Page 15

Data Science @Dream Sports: Data Science at Dream Sports comprises seasoned data scientists thriving to drive value with data across all our initiatives. The team has developed state-of-the-art solutions for forecasting and optimization, data-driven risk prevention systems, Causal Inference and Recommender Systems to enhance product and user experience. We are a team of Machine Learning Scientists and Research Scientists with a portfolio of projects ranges from production ML systems that we conceptualize, build, support and innovate upon, to longer term research projects with potential game-changing impact for Dream Sports. This is a unique opportunity for highly motivated candidates to work on real-world applications of machine learning in the sports industry, with access to state-of-the-art resources, infrastructure, and data from multiple sources streaming from 250 million users and contributing to our collaboration with Columbia Dream Sports AI Innovation Center. Your Role: Implementing appropriate success metrics, driving rapid experimentation of new POCs and presenting the impacts to stakeholders Driving knowledge sharing sessions within and across teams while maintaining continuous feedback channels with teammates to ensure building growth paths Owning respective services by following best practices in service maintainability, understanding and acting on the risks and opportunities involved Prioritising roadmaps while balancing impact, effort, resources and team's requirements to complete initiatives within committed timelines Developing and evaluating predictive and prescriptive models using appropriate mathematical methods like supervised and unsupervised learning, frequentist statistics, estimation methods Designing large-scale ML systems with advanced ML frameworks like TensorFlow/Keras/PyTorch for training and inferencing at scale Ensuring cross team alignment towards business/project goals by driving visibility of initiatives, managing conflicts, and highlighting implementation blocks Qualifiers: 6 - 10 years of experience in building and maintaining ML solutions at scale Proficient in predictive modelling (ML,DL/RL) and experimentation/causal inference methods Atleast 1 year of experience in managing team of data scientists and handling cross functional stakeholders Proven track record of designing end to end ML systems which can handle the scale About Dream Sports: Dream Sports is India’s leading sports technology company with 250 million users, housing brands such as Dream11 , the world’s largest fantasy sports platform, FanCode , a premier sports content & commerce platform and DreamSetGo , a sports experiences platform. Dream Sports is based in Mumbai and has a workforce of close to 1,000 ‘Sportans’. Founded in 2008 by Harsh Jain and Bhavit Sheth, Dream Sports’ vision is to ‘Make Sports Better’ for fans through the confluence of sports and technology. For more information: https://dreamsports.group/ Dream11 is the world’s largest fantasy sports platform with 230 million users playing fantasy cricket, football, basketball & hockey on it. Dream11 is the flagship brand of Dream Sports, India’s leading Sports Technology company and has partnerships with several national & international sports bodies and cricketers.

We are looking for a highly skilled Python Developer with solid experience in Artificial Intelligence (AI), Machine Learning (ML) , and Generative AI . The ideal candidate will have hands-on experience working with GPT-4 , transformer models , and deep learning frameworks , and a strong understanding of model fine-tuning, deployment, and inference. Key Responsibilities: Design, develop, and maintain Python applications focused on AI/ML and generative AI. Build and fine-tune transformer-based models (e.g., GPT, BERT, T5) for various NLP and generative tasks. Work with large-scale datasets for training and evaluation. Implement model inference pipelines and scalable APIs using FastAPI, Flask, or similar. Collaborate with data scientists and ML engineers to build end-to-end AI solutions. Stay current with recent research and developments in the field of generative AI and ML. Required Skills and Experience: Strong proficiency in Python and relevant libraries (NumPy, Pandas, Scikit-learn, etc.) 3–7+ years of experience in AI/ML development. Hands-on experience with transformer-based models , especially GPT-4 , LLMs , or diffusion models . Familiarity with Hugging Face Transformers , OpenAI API , or similar frameworks. Experience with TensorFlow , PyTorch , or JAX . Experience deploying models using Docker, Kubernetes, or cloud platforms (AWS, GCP, Azure). Strong problem-solving and algorithmic thinking. Familiarity with prompt engineering, fine-tuning, and reinforcement learning with human feedback (RLHF) is a plus.

Job Title: Senior CV Engineer Location: Gurugram Experience: 6–10 Years CTC: Up to ₹ 60LPA Overview: We are hiring for our esteemed client, a Series-A funded deep-tech company building a first-of-its-kind app-based operating system for Computer Vision. The team specializes in real-time video/image inference, distributed processing, and high-throughput data handling using advanced technologies and frameworks. Key Responsibilities: Lead design and implementation of complex CV pipelines (object detection, instance segmentation, industrial anomaly detection). Own major modules from concept to deployment ensuring low latency and high reliability. Transition algorithms from Python/PyTorch to optimized C++ edge GPU implementations using TensorRT, ONNX, and GStreamer. Collaborate with cross-functional teams to refine technical strategies and roadmaps. Drive long-term data and model strategies (synthetic data generation, validation frameworks). Mentor engineers and maintain high engineering standards. Required Skills & Qualifications: 6–10 years of experience in architecting and deploying CV systems. Expertise in multi-object tracking, object detection, semi/unsupervised learning. Proficiency in Python, PyTorch/TensorFlow, Modern C++, CUDA. Experience with real-time, low-latency model deployment on edge devices. Strong systems-level design thinking across ML lifecycles. Familiarity with MLOps (CI/CD for models, versioning, experiment tracking). Bachelor’s/Master’s degree in CS, EE, or related fields with strong ML and algorithmic foundations. (Preferred) Experience with NVIDIA DeepStream, GStreamer, LLMs/VLMs, open-source contributions.

Job Title: Data Scientist – Agentic AI | Cloud AI | AR/VR Location: Gurgaon- 5 days WFO Experience: 3 to 5 Years Employment Type: Full-time ⸻ About the Role We’re looking for a hands-on Data Scientist who’s excited by the next frontier of AI — from Agentic AI systems and multi-agent collaboration to cloud-based AI services and immersive experiences in AR/VR. This is your chance to work on cutting-edge innovation across verticals such as retail, healthcare, gaming, and enterprise tech. ⸻ Key Responsibilities • Build, deploy, and optimize AI/ML models with a focus on Agentic AI and multi-agent coordination frameworks (e.g., AutoGen, LangChain, etc.) • Leverage Google Cloud AI and Azure AI Services (Vision AI, Vertex AI, Azure ML) for scalable training, inference, and deployment • Apply Computer Vision techniques for object detection, image classification, and spatial tracking in AR/VR contexts • Collaborate cross-functionally with product, engineering, and design teams to bring AI-driven AR/VR applications to life • Utilize Multi-Cloud Pipelines (MCP) for managing end-to-end workflows in a hybrid cloud setup • Continuously experiment with emerging AI techniques in the realm of generative agents, prompt engineering, and memory-based systems ⸻ Must-Have Skills • 2–5 years of hands-on experience in AI/ML model development and deployment • Strong Python skills with experience in frameworks like TensorFlow, PyTorch, or OpenCV

Job Title:AI/ML Engineer / Data Scientist - with Databricks focus Experience: 8+Years Work type: Remote (India) Key Responsibilities: • Develop, deploy, and maintain scalable MLOps pipelines for both traditional ML and Generative AI use cases leveraging Databricks (Unity Catalog, Delta Tables, Inference Tables, Mosaic AI). • Operationalize large language models (LLMs) and other GenAI models, ensuring efficient prompt engineering, fine-tuning, and serving. • Implement model tracking, versioning, and experiment management using MLflow. • Build robust CI/CD pipelines for ML and GenAI workloads to automate testing, validation, and deployment to production. • Use Vertex AI to manage training, deployment, and monitoring of ML and GenAI models in the cloud. • Integrate high-quality, governed data pipelines that enable ML and Generative AI solutions with strong lineage and reproducibility. • Design and enforce AI Governance frameworks covering model explainability, bias monitoring, data access, compliance, and audit trails. • Collaborate with data scientists and GenAI teams to productionize prototypes and research into reliable, scalable products. • Monitor model performance, usage, and drift — including specific considerations for GenAI systems such as hallucination checks, prompt/response monitoring, and user feedback loops. • Stay current with best practices and emerging trends in MLOps and Generative AI. Key Qualifications: Must Have Skills: • 3+ years of experience in MLOps, ML Engineering, or related field. • Hands-on experience with operationalizing ML and Generative AI models in production. • Proficiency with Databricks (Unity Catalog, Delta Tables, Mosaic AI, Inference Tables). • Experience with MLflow for model tracking, registry, and reproducibility. • Strong understanding of Vertex AI pipelines and deployment services. • Expertise in CI/CD pipelines for ML and GenAI workloads (e.g., GitHub Actions, Azure DevOps, Jenkins). • Proven experience in integrating and managing data pipelines for AI, ensuring data quality, versioning, and lineage. • Solid understanding of AI Governance, model explainability, and responsible AI practices. • Proficiency in Python, SQL, and distributed computing frameworks. • Excellent communication and collaboration skills. Nice to Have: • Experience deploying and monitoring Large Language Models (LLMs) and prompt-driven AI workflows. • Familiarity with vector databases, embeddings, and retrieval-augmented generation (RAG) architectures. • Infrastructure-as-Code experience (Terraform, CloudFormation). • Experience working in regulated industries (e.g., finance, Retail) with compliance-heavy AI use cases.

Description Are you fascinated with the idea of creating a digital representation of the world? What about building learning systems to create the most precise and accurate representation? Join the Geospatial team to build Maps for Amazon. We build learning systems to identify road networks, POIs, and geocodes of addresses worldwide. Our delivery operations use these systems to determine the locations and plan the routes for delivery. Drivers use these systems to navigate to the delivery locations. Our mission is to vend geospatial data (e.g. maps, traffic, addresses, and locations/geocodes) that is detailed and fresh through an intuitive experience that enables every driver – independent of tenure and affinity – to succeed in their delivery tasks. We are not creating another consumer-grade mapping solution, we are building systems that enable depth focused solutions. For example, we are interested in not only getting a person to an address like 300 Boren Ave N, we are also interested in guiding them where to park, where the building entrance, find out if there is a mailing room in the building that is open at that time, and guide them to alternative delivery location at the customer unit based on various factors. The level of detail we provide on the delivery journey is leading in the mapping industry. Our geocodes also dictate how to optimally group the packages for that stop based on proximity and walk times, which significantly impacts route plan and stop plan efficiencies. Several of these problems require us to build systems that can work with an ensemble of ML models as well as support the right segmentation of inputs to make good estimates on the outputs. There are several unsolved or partially solved problems in this space; such as parsing and managing both structured and unstructured addresses in various countries, modeling building entrances and unit access in multi-unit buildings, optimal polygonal geofence guardrails, and multiple delivery locations with business and transportation mode awareness. The technical domain is multi-faceted. We build low-latency, highly-available services, we build big data processing pipelines to refresh or produce new data, we train ML models, and we run science experiments. We also build solutions for these capabilities, ranging from state-of-the-art ML platforms (including generative AI) to modeling, storing, vending, and managing large amounts of data. Our key output metrics include location accuracy, coverage, and predictive accuracy of service and transit estimates. We also measure the operational impact of these inputs on delivery success and transporter experience. If you have an entrepreneurial spirit, know how to deliver, are deeply technical, highly innovative and long for the opportunity to build pioneering solutions to challenging problems, we want to talk to you. Key job responsibilities Participate in the design, implementation, and deployment of successful large-scale systems and services in support of our transportation operations and the businesses they support. Participate in the definition of secure, scalable, and low-latency services and efficient physical processes. Work in expert cross-functional teams delivering on demanding projects. Functionally decompose complex problems into simple, straight-forward solutions. Understand system inter-dependencies and limitations. Share knowledge in performance, scalability, enterprise system architecture, and engineering best practices. A day in the life Collaborate with engineering and science teams on building state-of-the-art scalable, big data pipelines, ML training and inference solutions, high-availability services with low latencies. Analyze nuanced metrics to understand system behavior and innovate on solutions to optimize our success metrics. Play a key role in the technology that empowers the delivery of millions of smiles every day around the world. About The Team The broader Geospatial organization covers Amazon Maps, driving and walking time estimation and the transporter navigation experience. This team focuses on destination related data and locations for parking, building entries, delivery locations and other waypoints throughout the transporter delivery journey, and how they relate to places, floors and building layouts. We build systems that learn, ingest, rank and vend data related to locations. Basic Qualifications 3+ years of non-internship professional software development experience 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience 3+ years of Video Games Industry (supporting title Development, Release, or Live Ops) experience Experience programming with at least one software programming language Preferred Qualifications 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience Bachelor's degree in computer science or equivalent Experience in Geoapatial domain or building and operation data-intensive systems. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. Company - ADCI HYD 13 SEZ Job ID: A2943520

Customers trust the Alation Data Intelligence Platform for self-service analytics, cloud transformation, data governance, and AI-ready data, fostering data-driven innovation at scale. With more than $340M in funding – valued at over $1.7 billion and nearly 600 customers, including 40% of the Fortune 100 — Alation helps organizations realize value from data and AI initiatives. Alation has been recognized in 2024 as one of Inc. Magazine's Best Workplaces for the fifth time, a testament to our commitment to creating an inclusive, innovative, and collaborative environment. Collaboration is at the forefront of everything we do. We strive to bring diverse perspectives together and empower each team member to contribute their unique strengths to live out our values each day. These are: Move the Ball, Build for the Long Term, Listen Like You’re Wrong, and Measure Through Customer Impact. Joining Alation means being part of a fast-paced, high-growth company where every voice matters, and where we’re shaping the future of data intelligence with AI-ready data. Join us on our journey to build a world where data culture thrives and curiosity is celebrated each day! Job Description About the Role Opportunity to own business critical components and services, powering key use cases for Alation’s customers. The role is one of high ownership, large business impact and executing on a future vision that will be loved by the customers. What you'll do! Design and implement moderately complex features with minimal supervision Write clean, efficient, and maintainable code that follows team best practices Debug and troubleshoot issues efficiently, providing well-reasoned solutions Implement and maintain unit and integration tests to ensure software quality Contribute to system design discussions and provide input on architecture decisions You should have 2+ years of professional experience designing, developing, and shipping software products and/or n-tier services Strong knowledge of TypeScript, including type inference, interfaces, and generics Proficiency in ReactJs, Zustland, Recoil, Redux Experience with unit and integration testing with tools like Jest, React Testing Library, Cypress, or Playwright Experience integrating with REST APIs Strong problem-solving and analytical skills Excellent communication and collaboration skills Ability to learn through collaboration and apply the knowledge to the assigned tasks Bachelor’s Degree in Computer Science or similar A Big Plus Working experience in Kubernetes and/or Docker Exposure to data modeling in RDBMS Alation, Inc. is an Equal Employment Opportunity employer. All qualified applicants will receive consideration for employment without regards to that individual’s race, color, religion or creed, national origin or ancestry, sex (including pregnancy), sexual orientation, gender identity, age, physical or mental disability, veteran status, genetic information, ethnicity, citizenship, or any other characteristic protected by law. The Company will strive to provide reasonable accommodations to permit qualified applicants who have a need for an accommodation to participate in the hiring process (e.g., accommodations for a job interview) if so requested. This company participates in E-Verify. Click on any of the links below to view or print the full poster. E-Verify and Right to Work.

Position: AI + Backend Engineer Location: Gurugram Experience Required: 7–8+ years We are looking for a highly capable and innovative AI + Backend Engineer to join our dynamic team in Gurugram. The ideal candidate should bring in-depth experience working with Large Language Models (LLMs), Natural Language Processing (NLP), and intelligent agent frameworks, combined with solid backend development skills. This role requires a strong grasp of machine learning operations, API-centric architectures, and distributed systems. Role & Responsibilities: Design and develop advanced AI solutions leveraging LLMs for tasks like content generation, entity extraction, summarization, and intelligent agent development. Fine-tune and implement models for dense retrieval, question answering, and semantic search use cases. Build and maintain high-performance backend systems and RESTful APIs that support AI model integration. Use vector databases and embedding-based retrieval methods to enhance model outputs (e.g., Pinecone, FAISS, Weaviate). Apply Retrieval-Augmented Generation (RAG) frameworks to support dynamic and context-aware responses. Work closely with ML engineers and researchers to streamline model training, deployment, and optimization processes. Monitor and enhance the performance of deployed models and inference pipelines in production environments. Set up and manage end-to-end data pipelines for preprocessing, training, and deployment workflows. Stay abreast of the latest research and industry developments in the field of LLMs, NLP, and AI agents to continuously improve solutions. Key Requirements: 7–8+ years of experience in AI/ML systems development and backend engineering, with a strong focus on NLP and LLM-based systems. Expertise in Python and deep learning libraries such as PyTorch, TensorFlow, and Hugging Face Transformers. Strong experience in model fine-tuning, prompt engineering, and building intelligent agent-based applications. Practical knowledge of working with vector databases and retrieval mechanisms. Proficiency in building and scaling backend platforms using frameworks like FastAPI, Flask, or Django. Solid experience with cloud platforms like AWS, Google Cloud Platform, or Azure for AI deployment. Skilled in using Docker, Kubernetes, and related tools for model containerization and orchestration. Familiarity with MLOps practices, CI/CD pipelines, and model version control. Excellent analytical, debugging, and communication skills, with the ability to work effectively in agile, cross-functional teams.

Location: India Remote Employment Type: Full-time Experience Level: Mid to Senior (4-5+ years) Date of Joining : Required Immediate Joiners About UltraSafeAI UltraSafeAI is a US-based technology company at the forefront of developing secure, reliable, and explainable AI systems. We specialize in proprietary AI technologies including advanced LLMs, CNNs, VLLMs, intelligent agents, computer vision systems, and cutting-edge ML algorithms. Our focus is on B2B AI adoption, providing end-to-end integration using our proprietary technology stack to automate entire business processes. We create intelligent solutions that prioritize safety, transparency, and human alignment across various industries including healthcare, finance, legal, and enterprise services. Our mission is to enable seamless AI adoption while maintaining the highest standards of safety and ethical considerations. Position Overview We're seeking an experienced AI Research Engineer specializing in model training, fine-tuning, and optimization of large language models (LLMs), vision language models (VLMs), and convolutional neural networks (CNNs). The ideal candidate will have deep expertise in training and fine-tuning foundation models using advanced techniques and frameworks, with particular emphasis on reinforcement learning approaches for alignment. As an AI Research Engineer at UltraSafeAI, you'll work on developing and enhancing our proprietary models, creating domain-specific adaptations, and optimizing inference performance. You'll collaborate with our engineering team to build the core AI capabilities that power our enterprise solutions and set new standards for AI performance and safety in business applications. Key Responsibilities ● Train and fine-tune large language models (LLMs) and vision language models (VLMs) using state-of-the-art techniques ● Implement and improve reinforcement learning methods for model alignment, including DPO, PPO, and GRPO ● Develop and optimize CNNs for specialized computer vision tasks in enterprise contexts ● Work with distributed training frameworks for efficient model development ● Optimize models for inference using libraries like VLLM, SGLANG, and Triton Inference Server ● Implement techniques for reducing model size while maintaining performance (quantization, distillation, pruning) ● Create domain-specific adaptations of foundation models for vertical industry applications ● Design and execute experiments to evaluate model performance and alignment ● Develop benchmarks and metrics to measure improvements in model capabilities ● Collaborate with data science team on dataset curation and preparation for training ● Document model architectures, training procedures, and experimental results ● Stay current with the latest research in model training and alignment techniques Required Qualifications ● 4-5+ years of professional experience in AI/ML engineering with focus on model training ● Strong expertise in training and fine-tuning large language models ● Experience with major deep learning frameworks (PyTorch, TensorFlow, JAX) ● Hands-on experience with model training libraries and frameworks (Transformers, NeMo, Megatron-LM, TRL) ● Practical implementation of reinforcement learning techniques for model alignment (DPO, PPO, GRPO) ● Experience optimizing models for efficient inference ● Strong understanding of distributed training techniques for large models ● Background in computer vision model development (CNNs, vision transformers) ● Excellent programming skills in Python and related data science tools ● Experience with cloud infrastructure for ML workloads (AWS, GCP, or Azure) ● Strong problem-solving skills and scientific mindset ● Excellent documentation and communication abilities Highly Desirable ● Experience with multimodal models combining text, vision, and other modalities ● Knowledge of model quantization techniques (QLoRA, GPTQ, AWQ) ● Experience with VLLM, SGLANG, or Triton Inference Server for optimized inference ● Background in prompt engineering and instruction tuning ● Familiarity with RLHF (Reinforcement Learning from Human Feedback) ● Experience with model evaluation and red-teaming ● Knowledge of AI safety and alignment research ● Experience with domain-specific model adaptation for industries like healthcare, finance, or legal ● Background in research with publications or contributions to open-source ML projects ● Experience with MLOps tools and practices for model lifecycle management Why Join UltraSafeAI? ● Create Proprietary AI Models: Develop the core AI technologies that power our enterprise solutions ● 100% Remote Work: Work remotely with our US-based company with flexible hours ● B2B Impact: Help shape AI models that solve real business problems across industries ● Cutting-Edge Research: Work on the frontier of AI model development and alignment ● Continuous Learning: Regular knowledge sharing sessions and education stipend ● Collaborative Team: Work with talented researchers and engineers focused on innovation ● Work-Life Balance: Flexible PTO policy and respect for personal time ● Career Growth: Clear paths for advancement in a rapidly growing company ● Industry-Leading Infrastructure: Access to high-performance computing resources for model training

We are seeking a skilled and experienced Golang Developer to join our AI product engineering team. You will be responsible for building scalable backend systems and APIs that power intelligent applications and services. This is a high-impact role where you’ll work closely with data scientists, AI engineers, and frontend developers to integrate AI models into production-ready software. Key Responsibilities: Design, develop, and maintain high-performance backend services in Go. Develop RESTful APIs and microservices for AI-driven applications. Integrate with machine learning models, inference pipelines, and data processing tools. Optimize system performance and ensure low-latency, high-throughput APIs. Collaborate with DevOps teams to containerize and deploy applications (Docker, Kubernetes). Work closely with AI/ML teams to convert research prototypes into scalable services. Ensure code quality through unit testing, code reviews, and best practices. Contribute to architecture decisions and scalability planning. Required Skills & Qualifications: Strong proficiency in Go (Golang) and experience in building backend services. Hands-on experience with REST APIs, microservices architecture , and distributed systems. Familiarity with AI/ML model integration (e.g., via gRPC, REST, TensorFlow Serving, or ONNX). Experience with PostgreSQL / MongoDB / Redis or other databases. Understanding of containerization (Docker) and orchestration (Kubernetes). Familiarity with message brokers like Kafka, RabbitMQ, or NATS. Experience in working with Git, CI/CD pipelines , and cloud platforms (AWS, GCP, Azure). Good understanding of concurrency patterns , performance tuning, and memory management in Go. What We Offer: Opportunity to work on cutting-edge AI solutions. Flexible and collaborative work environment. Competitive salary and benefits. Career growth and continuous learning opportunities. This is a work-from-office position. Only candidates who are willing to relocate to Trivandrum should apply.

AI Developer/Lead Position Overview Lead the development and implementation of AI-powered solutions to enhance nonprofit operational efficiency. This role combines technical leadership with hands-on development, driving our aggressive 6-week implementation cycles and multi-modal development approach. Key Responsibilities Technical Leadership Lead technical design and architecture decisions for AI applications across all classification categories Oversee PoC development, bug fixes, iteration, and production builds Implement and maintain open-source AI foundations (Llama, Haystack, LlamaGuard) Design and manage synthetic data pipelines for training and analytics Ensure deployment and go-live support for all AI applications Development Strategy Execution Drive accelerated creation using AI-powered development tools (Replit, Windsurf, Cursor) for rapid prototyping Manage complete development lifecycle: initial AI-assisted development ? manual code refinement ? user feedback integration ? production deployment Deploy applications directly on organizational servers with robust CI/CD processes Collaborate with global contributor network through GitHub Contribute insights back to the nonprofit technology community Integrate OSINT information into research and analytics workflows Application Development Focus Areas Basic automation for meeting reports, eCourts monitoring, administrative workflows Custom data management platforms replacing Excel-based systems Specialized LLM chatbots with domain knowledge across multiple functions ? Multi-modal tracking solutions (image, video, audio, location data) ML/NLP tools for hotspot prediction, translation services, investigative tools Compliance applications with automated DPDP and regulatory adherence Cybersecurity integration with secure communication frameworks Required Qualifications 5+ years experience in AI/ML development and deployment Proficiency in Python, JavaScript, React and modern AI frameworks Experience with LLM integration, fine-tuning, and safety models Hands-on experience with inference engines (like Groq/Cerebras) and API integration Strong background in server deployment and infrastructure management Experience with AI-assisted development tools (Replit, Cursor, Windsurf) Strong background in open-source development and GitHub collaboration Experience transitioning from rapid prototypes to production-ready applications Proven ability to deliver production applications in aggressive timelines Experience working with distributed international teams across multiple time zones Preferred Qualifications Experience with multi-modal AI applications Knowledge of both cloud-based inference services and self-hosted model deployment DevOps experience with server management and deployment automation

About the role We’re looking for Senior Engineering Manager to lead our Data / AI Platform and MLOps teams at slice. In this role, you’ll be responsible for building and scaling a high-performing team that powers data infrastructure, real-time streaming, ML enablement, and data accessibility across the company. You'll partner closely with ML, product, platform, and analytics stakeholders to build robust systems that deliver high-quality, reliable data at scale. You will drive AI initiatives to centrally build AP platform and apps which can be leveraged by various functions like legal, CX, product in a secured manner This is a hands-on leadership role perfect for someone who enjoys solving deep technical problems while growing people and teams. What You Will Do Lead and grow the data platform pod focused on all aspects of data (batch + real-time processing, ML platform, AI tooling, Business reporting, Data products – enabling product experience through data) Maintain hands-on technical leadership - lead by example through code reviews, architecture decisions, and direct technical contribution Partner closely with product and business stakeholders to identify data-driven opportunities and translate business requirements into scalable data solutions Own the technical roadmap for our data platform including infra modernization, performance, scalability, and cost efficiency Drive the development of internal data products like self-serve data access, centralized query layers, and feature stores Build and scale ML infrastructure with MLOps best practices including automated pipelines, model monitoring, and real-time inference systems Lead AI platform development for hosting LLMs, building secure AI applications, and enabling self-service AI capabilities across the organization Implement enterprise AI governance including model security, access controls, and compliance frameworks for internal AI applications Collaborate with engineering leaders across backend, ML, and security to align on long-term data architecture Establish and enforce best practices around data governance, access controls, and data quality Ensure regulatory compliance with GDPR, PCI-DSS, SOX through automated compliance monitoring and secure data pipelines Implement real-time data processing for fraud detection and risk management with end-to-end encryption and audit trails Coach engineers and team leads through regular 1:1s, feedback, and performance conversations What You Will Need 10+ years of engineering experience, including 2+ years managing data or infra teams with proven hands-on technical leadership Strong stakeholder management skills with experience translating business requirements into data solutions and identifying product enhancement opportunities Strong technical background in data platforms, cloud infrastructure (preferably AWS), and distributed systems Experience with tools like Apache Spark, Flink, EMR, Airflow, Trino/Presto, Kafka, and Kubeflow/Ray plus modern stack: dbt, Databricks, Snowflake, Terraform Hands on experience building AI/ML platforms including MLOps tools and experience with LLM hosting, model serving, and secure AI application development Proven experience improving performance, cost, and observability in large-scale data systems Expert-level cloud platform knowledge with container orchestration (Kubernetes, Docker) and Infrastructure-as-Code Experience with real-time streaming architectures (Kafka, Redpanda, Kinesis) Understanding of AI/ML frameworks (TensorFlow, PyTorch), LLM hosting platforms, and secure AI application development patterns Comfort working in fast-paced, product-led environments with ability to balance innovation and regulatory constraints Bonus: Experience with data security and compliance (PII/PCI handling), LLM infrastructure, and fintech regulations Life at slice Life so good, you’d think we’re kidding: Competitive salaries. Period. An extensive medical insurance that looks out for our employees & their dependents. We’ll love you and take care of you, our promise. Flexible working hours. Just don’t call us at 3AM, we like our sleep schedule. Tailored vacation & leave policies so that you enjoy every important moment in your life. A reward system that celebrates hard work and milestones throughout the year. Expect a gift coming your way anytime you kill it here. Learning and upskilling opportunities. Seriously, not kidding. Good food, games, and a cool office to make you feel like home. An environment so good, you’ll forget the term “colleagues can’t be your friends”.

Job Purpose Manage Electro-mechanical and Fire & Safety operations to ensure the quality and deliverables in a timely and cost effective manner at all office locations of Bangalore; Role would be responsible to build, deploy, and scale machine learning and AI solutions across GMR’s verticals. This role will build and manage advanced analytics initiatives, predictive engines, and GenAI applications — with a focus on business outcomes, model performance, and intelligent automation. Reporting to the Head of Automation & AI, you will operate in a high-velocity, product-oriented environment with direct visibility of impact across airports, energy, infrastructure and enterprise functions ORGANISATION CHART Key Accountabilities Accountabilities Key Performance Indicators AI & ML Development Build and deploy models using supervised, unsupervised, and reinforcement learning techniques for use cases such as forecasting, predictive scenarios, dynamic pricing & recommendation engines, and anomaly detection, with exposure to broad enterprise functions and business Lead development of models, NLP classifiers, and GenAI-enhanced prediction engines. Design and integrate LLM-based features such as prompt pipelines, fine-tuned models, and inference architecture using Gemini, Azure OpenAI, LLama etc. Program Plan Vs Actuals End-to-End Solutioning Translate business problems into robust data science pipelines with emphasis on accuracy, explainability, and scalability. Own the full ML lifecycle — from data ingestion and feature engineering to model training, evaluation, deployment, retraining, and drift management. Program Plan Vs Actuals Cloud , ML & data Engineering Deploy production-grade models using AWS, GCP, or Azure AI platforms and orchestrate workflows using tools like Step Functions, SageMaker, Lambda, and API Gateway. Build and optimise ETL/ELT pipelines, ensuring smooth integration with BI tools (Power BI, QlikSense or similar) and business systems. Data compression and familiarity with cloud finops will be an advantage, have used some tools like kafka, apache airflow or similar 100% compliance to processes KEY ACCOUNTABILITIES - Additional Details EXTERNAL INTERACTIONS Consulting and Management Services provider IT Service Providers / Analyst Firms Vendors INTERNAL INTERACTIONS GCFO and Finance Council, Procurement council, IT council, HR Council (GHROC) GCMO/ BCMO FINANCIAL DIMENSIONS Other Dimensions EDUCATION QUALIFICATIONS Engineering Relevant Experience 5 - 8years of hands-on experience in machine learning, AI engineering, or data science, including deploying models at scale. Strong programming and modelling skills in some like Python, SQL, and ML frameworks like scikit-learn, TensorFlow, XGBoost, PyTorch. Demonstrated ability to build models using supervised, unsupervised, and reinforcement learning techniques to solve complex business problems. Technical & Platform Skills Proven experience with cloud-native ML tools: AWS SageMaker, Azure ML Studio, Google AI Platform. Familiarity with DevOps and orchestration tools: Docker, Git, Step Functions, Lambda,Google AI or similar Comfort working with BI/reporting layers, testing, and model performance dashboards. Mathematics and Statistics Linear algebra, Bayesian method, information theory, statistical inference, clustering, regression etc Collaborate with Generative AI and RPA teams to develop intelligent workflows Participate in rapid prototyping, technical reviews, and internal capability building NLP and Computer Vision Knowledge of Hugging Face Transformers, Spacy or similar NLP tools YoLO, Open CV or similar for Computer vision. COMPETENCIES Personal Effectiveness Social Awareness Entrepreneurship Problem Solving & Analytical Thinking Planning & Decision Making Capability Building Strategic Orientation Stakeholder Focus Networking Execution & Results Teamwork & Interpersonal influence

Staff Backend Engineer – Core AI Platform Location: India (Remote) Function: Engineering – AI Platform Level: Staff Reports to: VP of Engineering / CTO About the Company We’re hiring a Staff Engineer – AI Frameworks to architect and lead the development of the foundational multi-agent infrastructure powering the next generation of intelligent systems for financial institutions. This role is not about plugging in pre-built models—it’s about designing and scaling custom AI orchestration frameworks that bind language models, memory, judgment modules, and tool use into autonomous systems that are trustworthy, composable, and policy-aligned. You’ll work at the intersection of machine learning, distributed systems, and agentic reasoning, partnering with researchers, backend engineers, and product leaders to bring real-time, LLM-driven intelligence into production at scale. This is a rare opportunity to define and build the AI runtime and execution architecture for mission-critical agents in a high-regulation, high-trust industry. About the Role We’re hiring a Staff Engineer – AI Frameworks to architect and lead the development of the foundational multi-agent infrastructure powering the next generation of intelligent systems for financial institutions. Responsibilities Architect a multi-agent AI framework for orchestrating LLMs, tools, memory, and decision modules in live user-facing systems Build and optimize low-latency, distributed inference systems that meet real-time SLAs for transactional environments Develop modular components for task planning, reward routing, fallback handling, and multi-turn reasoning Design developer-facing APIs and tooling to allow AI product teams to safely extend and compose agentic functionality Integrate vector stores, custom retrieval pipelines, model evaluators, judgment layers, and auto-tuning workflows Drive the implementation of prompt tuning, reward modeling, and LLM-as-a-Judge techniques in production loops Collaborate with research to productionize new RL, planning, or alignment strategies Establish architectural best practices for extensibility, observability, and trust in AI-enabled systems Qualifications 8+ years of backend or platform engineering experience, with at least 2 years building or deploying AI/ML systems Deep experience with Node.js, asynchronous architecture, and performance-critical backend systems Prior hands-on experience building ML models or training pipelines —you know how models learn, behave, and break Expert knowledge of LLM system design, agent architectures, and Reinforcement Learning techniques Proven track record building distributed, event-driven systems in high-throughput environments Experience building real-time inference systems that integrate LLMs with retrieval, memory, or tool use Strong systems design skills: designing modular, fault-tolerant, observable software at scale Demonstrated ability to lead architectural design and cross-functional engineering initiatives Preferred Skills Experience building multi-agent systems or intelligent orchestration engines Familiarity with vector databases, semantic search, and prompt engineering techniques Comfort integrating ML eval frameworks and offline/online experimentation pipelines Open-source contributions to LLM tooling or infrastructure a plus

:-Job Title: Machine Learning Engineer – 2 Location: Onsite – Bengaluru, Karnataka, India Experience Required: 3 – 6 Years Compensation: ₹20 – ₹25 LPA Employment Type: Full-Time Work Mode: Onsite Only (No Remote) About the Company:- A fast-growing Y Combinator-backed SaaS startup is revolutionizing underwriting in the insurance space through AI and Generative AI. Their platform empowers insurance carriers in the U.S. to make faster, more accurate decisions by automating key processes and enhancing risk assessment. As they expand their AI capabilities, they’re seeking a Machine Learning Engineer – 2 to build scalable ML solutions using NLP, Computer Vision, and LLM technologies. Role Overview:- As a Machine Learning Engineer – 2, you'll take ownership of designing, developing, and deploying ML systems that power critical features across the platform. You'll lead end-to-end ML workflows, working with cross-functional teams to deliver real-world AI solutions that directly impact business outcomes. Key Responsibilities:- Design and develop robust AI product features aligned with user and business needs Maintain and enhance existing ML/AI systems Build and manage ML pipelines for training, deployment, monitoring, and experimentation Deploy scalable inference APIs and conduct A/B testing Optimize GPU architectures and fine-tune transformer/LLM models Build and deploy LLM applications tailored to real-world use cases Implement DevOps/ML Ops best practices with tools like Docker and Kubernetes Tech Stack & Tools Machine Learning & LLMs GPT, LLaMA, Gemini, Claude, Hugging Face Transformers PyTorch, TensorFlow, Scikit-learn LLMOps & MLOps Langchain, LangGraph, LangFlow, Langfuse MLFlow, SageMaker, LlamaIndex, AWS Bedrock, Azure AI Cloud & Infrastructure AWS, Azure Kubernetes, Docker Databases MongoDB, PostgreSQL, Pinecone, ChromaDB Languages Python, SQL, JavaScript What You’ll Do Collaborate with product, research, and engineering teams to build scalable AI solutions Implement advanced NLP and Generative AI models (e.g., RAG, Transformers) Monitor and optimize model performance and deployment pipelines Build efficient, scalable data and feature pipelines Stay updated on industry trends and contribute to internal innovation Present key insights and ML solutions to technical and business stakeholders Requirements Must-Have:- 3–6 years of experience in Machine Learning and software/data engineering Master’s degree (or equivalent) in ML, AI, or related technical fields Strong hands-on experience with Python, PyTorch/TensorFlow, and Scikit-learn Familiarity with ML Ops, model deployment, and production pipelines Experience working with LLMs and modern NLP techniques Ability to work collaboratively in a fast-paced, product-driven environment Strong problem-solving and communication skills Bonus Certifications such as: AWS Machine Learning Specialty AWS Solution Architect – Professional Azure Solutions Architect Expert Why Apply Work directly with a high-caliber founding team Help shape the future of AI in the insurance space Gain ownership and visibility in a product-focused engineering role Opportunity to innovate with state-of-the-art AI/LLM tech Be part of a fast-moving team with real market traction 📍 Note: This is an onsite-only role based in Bengaluru. Remote work is not available. Skills: mongodb,pytorch,aws,javascript,python,azure,llms and modern nlp techniques,computer vision,chromadb,tensorflow,docker,scikit-learn,mlops,ml ops,kubernetes,ml, ai,nlp,llm,software/data engineering,python, pytorch/tensorflow, and scikit-learn,pinecone,postgresql,machine learning,llms,llm technologies,sql,devops

Job Title: Senior Test Automation Lead – Playwright (AI/ML Focus) Location: Hyderabad Job Type: Full-Time Experience Required: 8+ years in Software QA/Testing, 3+ years in Test Automation using Playwright, 2+ years in AI/ML project environments --- About the Role: We are seeking a passionate and technically skilled Senior Test Automation Lead with deep experience in Playwright-based frameworks and a solid understanding of AI/ML-driven applications. In this role, you will lead the automation strategy and quality engineering practices for next-generation AI products that integrate large-scale machine learning models, data pipelines, and dynamic, intelligent UIs. You will define, architect, and implement scalable automation solutions across AI-enhanced features such as recommendation engines, conversational UIs, real-time analytics, and predictive workflows, ensuring both functional correctness and intelligent behavior consistency. --- Key Responsibilities: Test Automation Framework Design & Implementation · Design and implement robust, modular, and extensible Playwright automation frameworks using TypeScript/JavaScript. · Define automation design patterns and utilities that can handle complex AI-driven UI behaviors (e.g., dynamic content, personalization, chat interfaces). · Implement abstraction layers for easy test data handling, reusable components, and multi-browser/platform execution. AI/ML-Specific Testing Strategy · Partner with Data Scientists and ML Engineers to understand model behaviors, inference workflows, and output formats. · Develop strategies for testing non-deterministic model outputs (e.g., chat responses, classification labels) using tolerance ranges, confidence intervals, or golden datasets. · Design tests to validate ML integration points: REST/gRPC API calls, feature flags, model versioning, and output accuracy. · Include bias, fairness, and edge-case validations in test suites where applicable (e.g., fairness in recommendation engines or NLP sentiment analysis). End-to-End Test Coverage · Lead the implementation of end-to-end automation for: o Web interfaces (React, Angular, or other SPA frameworks) o Backend services (REST, GraphQL, WebSockets) o ML model integration endpoints (real-time inference APIs, batch pipelines) · Build test utilities for mocking, stubbing, and simulating AI inputs and datasets. CI/CD & Tooling Integration · Integrate automation suites into CI/CD pipelines using GitHub Actions, Jenkins, GitLab CI, or similar. · Configure parallel execution, containerized test environments (e.g., Docker), and test artifact management. · Establish real-time dashboards and historical reporting using tools like Allure, ReportPortal, TestRail, or custom Grafana integrations. Quality Engineering & Leadership · Define KPIs and QA metrics for AI/ML product quality: functional accuracy, model regression rates, test coverage %, time-to-feedback, etc. · Lead and mentor a team of automation and QA engineers across multiple projects. · Act as the Quality Champion across the AI platform by influencing engineering, product, and data science teams on quality ownership and testing best practices. Agile & Cross-Functional Collaboration · Work in Agile/Scrum teams; participate in backlog grooming, sprint planning, and retrospectives. · Collaborate across disciplines: Frontend, Backend, DevOps, MLOps, and Product Management to ensure complete testability. · Review feature specs, AI/ML model update notes, and data schemas for impact analysis. --- Required Skills and Qualifications: Technical Skills: · Strong hands-on expertise with Playwright (TypeScript/JavaScript). · Experience building custom automation frameworks and utilities from scratch. · Proficiency in testing AI/ML-integrated applications: inference endpoints, personalization engines, chatbots, or predictive dashboards. · Solid knowledge of HTTP protocols, API testing (Postman, Supertest, RestAssured). · Familiarity with MLOps and model lifecycle management (e.g., via MLflow, SageMaker, Vertex AI). · Experience in testing data pipelines (ETL, streaming, batch), synthetic data generation, and test data versioning. Domain Knowledge: · Exposure to NLP, CV, recommendation engines, time-series forecasting, or tabular ML models. · Understanding of key ML metrics (precision, recall, F1-score, AUC), model drift, and concept drift. · Knowledge of bias/fairness auditing, especially in UI/UX contexts where AI decisions are shown to users. Leadership & Communication: · Proven experience leading QA/Automation teams (4+ engineers). · Strong documentation, code review, and stakeholder communication skills. · Experience collaborating in Agile/SAFe environments with cross-functional teams. --- Preferred Qualifications: · Experience with AI Explainability frameworks like LIME, SHAP, or What-If Tool. · Familiarity with Test Data Management platforms (e.g., Tonic.ai, Delphix) for ML training/inference data. · Background in performance and load testing for AI systems using tools like Locust, JMeter, or k6. · Experience with GraphQL, Kafka, or event-driven architecture testing. · QA Certifications (ISTQB, Certified Selenium Engineer) or cloud certifications (AWS, GCP, Azure). --- Education: · Bachelor’s or Master’s degree in Computer Science, Software Engineering, or related technical discipline. · Bonus for certifications or formal training in Machine Learning, Data Science, or MLOps. --- Why Join Us? · Work on cutting-edge AI platforms shaping the future of [industry/domain]. · Collaborate with world-class AI researchers and engineers. · Drive the quality of products used by [millions of users / high-impact clients]. · Opportunity to define test automation practices for AI—one of the most exciting frontiers in tech.

Description As a key member of our team, you will support our product development teams with insights gained from analyzing company data with respect to potential opportunities for product and process optimization. You must have strong experience using a variety of data mining/data analysis methods. The Senior Data Scientist II will lead data modeling and machine learning projects using a variety of data tools, modeling approaches and algorithms. You will also design experiments to evaluate models by conducting AB testing and simulations. Key Responsibilities Able to translate product design requirements into pipeline of heuristic and stochastic algorithms Understand exploratory data analysis for product feasibility studies and ground truth testing Execute SQL queries and/or python scripts to manipulate, analyze and visualize data Able to implement explainable AI solutions and rationalize model inferences Follows SDLC processes, Adopt agile-based processes/meetings and peer code-reviews Works with Machine learning engineer/architect to deploy data products into production Follows and understands legal data use restrictions Contributes to algorithm library development and design for ML, NLP and XAI Delivers product pipelines for deployment to production Builds applications that integrate third party and self-hosted foundation models. Fine tunes open source foundation models (LLMs, VLMs) with proprietary data Develops autonomous AI inference and tool use orchestration using ReAct AI agents Provides root cause analysis for machine learning model inference Completes data analysis or processing tasks as directed Documents data product end to end design and development Data annotation, labeling and other related data generation activities Provides thought leadership for rest of team and seeks out opportunities to mentor more junior team members Presents and holds data product updates and trainings Updates team on data product performance Education & Experience Strong problem solving skills with an emphasis on product development. 6+ years of experience developing data science products Strong experience using and optimizing common python machine and deep learning libraries such as Scikit learn, PyTorch, TensorFlow, Keras, MXNet and Spark MLlib Experience using statistical computer languages (Python, R, Scala, SQL, etc.) to manipulate data and draw insights from large data sets. Hands-on generative AI development Experience using foundation models (LLMs, VLMs) Experience with model fine tuning of open source foundation models with proprietary data Experience leveraging AI metrics for monitoring and value tracking Knowledge of AI Agent frameworks with recent hands-on experience building an AI agent able to autonomously use data stores, tools and other AI models to solve inquiries. Deep knowledge of data science concepts and related product development lifecycle Experience using machine learning libraries such as TensorFlow, Keras, SparkML etc. Working knowledge of machine learning tuning optimization procedures Experience working with and creating data architectures. Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications. Excellent written and verbal communication skills for coordinating across teams. A drive to learn and master new technologies and techniques. Preferred Experience with big data analytical frameworks such as Spark/PySpark Experience analyzing data from 3rd party providers: Google Knowledge Graph, Wikidata, etc. Experience visualizing/presenting data for stakeholders using: Looker, PowerBI, Tableau, etc.

A career in our Advisory Acceleration Centre is the natural extension of PwC’s leading class global delivery capabilities. We provide premium, cost effective, high quality services that support process quality and delivery capability in support for client engagements. To really stand out and make us fit for the future in a constantly changing world, each and every one of us at PwC needs to be an authentic and inclusive leader, at all grades/levels and in all lines of service. To help us achieve this we have the PwC Professional; our global leadership development framework. It gives us a single set of expectations across our lines, geographies and career paths, and provides transparency on the skills we need as individuals to be successful and progress in our careers, now and in the future. Responsibilities As a Senior Associate, you'll work as part of a team of problem solvers, helping to solve complex business issues from strategy to execution. PwC Professional skills and responsibilities for this management level include but are not limited to: Use feedback and reflection to develop self awareness, personal strengths and address development areas. Delegate to others to provide stretch opportunities and coach to help deliver results. Develop new ideas and propose innovative solutions to problems. Use a broad range of tools and techniques to extract insights from from current trends in business area. Review your work and that of others for quality, accuracy and relevance. Share relevant thought leadership. Use straightforward communication, in a structured way, when influencing others. Able to read situations and modify behavior to build quality, diverse relationships. Uphold the firm's code of ethics and business conduct. Edu qualifications: BE / B Tech / MCA/ MTech Experience range: 5 - 10 years Skill - GW Testing - Senior Associate Job Description - Reviewing requirements / specifications / technical design documents Designing detailed, comprehensive and well-structured Test Plans and Test Cases Setting up Test Environment & Test Data Executing tests as needed throughout the project. Analyzing and reporting test results. Identifying and tracking defects through their lifecycle. Understanding of Integration - Technical Design Document and Use Case Testing experience of any one of the Guidewire products: PolicyCenter Experience on policy transactions, workflow ,Audits, forms inference Performing thorough testing [Smoke / System / Integration / Regression / Stabilization Possessing expertise in Test Management Tools like ALM / Jira

Company Description 👋🏼 We're Nagarro. We are a Digital Product Engineering company that is scaling in a big way! We build products, services, and experiences that inspire, excite, and delight. We work at scale across all devices and digital mediums, and our people exist everywhere in the world (17500+ experts across 39 countries, to be exact). Our work culture is dynamic and non-hierarchical. We're looking for great new colleagues. That's where you come in! Job Description REQUIREMENTS: Total experience:10+years. Experience with LLMs (e.g., DeepSeek, LLaMA) and inference frameworks (Ollama, vLLM, llama.cpp). Proficiency in OpenCV, PyTorch, YOLO or TensorFlow, and model conversion workflows. Strong experience in Docker, DevOps, and CI/CD pipeline integration. Programming skills in Python, with solid experience in Linux and shell scripting. Understanding of edge AI hardware (Jetson/NXP/Qualcomm) and embedded deployment. Familiarity with Yocto OS and custom Linux builds. Strong grasp of model optimization and compression techniques. Experience with Langchain, AI agents, and RAG pipelines. Good knowledge of inference acceleration using CUDA and GPU-specific kernels. Excellent communication and collaboration skills. RESPONSIBILITIES: Understanding functional requirements thoroughly and analyzing the client’s needs in the context of the project Envisioning the overall solution for defined functional and non-functional requirements, and being able to define technologies, patterns and frameworks to realize it Determining and implementing design methodologies and tool sets Enabling application development by coordinating requirements, schedules, and activities. Being able to lead/support UAT and production roll outs Creating, understanding and validating WBS and estimated effort for given module/task, and being able to justify it Addressing issues promptly, responding positively to setbacks and challenges with a mindset of continuous improvement Giving constructive feedback to the team members and setting clear expectations. Qualifications Bachelor’s or master’s degree in computer science, Information Technology, or a related field.

Swirl AI turns every product page into a human-like sales conversation, blending LLMs, video understanding, real-time retrieval and agent orchestration. We’ve rocketed from 0 → Eight Figures of ARR in few months , and demand is outpacing our 7-person tech team. So, we need one extraordinary engineer to own the core of our platform and push it to Silicon Valley scale. What you’ll do First 90 days • Deep-dive into our multimodal stack (OpenAI-/Claude-based LLMs, custom SLMs, Azure Video Indexer, Pinecone/RAG, LangGraph) • Ship v2 of our SKU-specific “video-+-text” agent (latency < 500 ms, zero hallucinations). • Productionize auto-evaluation + guardrails (sentiment, brand safety) • Stand up voice & XR modalities and experiment with on-device inference. 6-12 months • Real-time GEO optimisation • Lead design of our “agent marketplace”: plug-and-play warranty, finance-offer & upsell agents. • Drive infra hardening to handle 10 M+ interactions / month across multiple Fortune-500 sites. Long term • Build and mentor an elite AI / ML/systems team. • Architect the path to: self-serve onboarding, global content network. You might be a fit if you Have 1-5+ yrs building production systems at scale Shipped deep-learning products end-to-end : data pipeline ➜ model training/fine-tuning ➜ safety/guardrails ➜ Serving (K8s, CUDA, Triton, Ray, or similar). Hands-on with multimodal (video, speech, vision) and agentic/RAG architectures. Fluent in Python/Typescript/Go; can debug distributed systems at 2 a.m. and still think product. Thrive in zero-to-one chaos: sketch, hack, iterate, talk to customers, then rewrite for scale. Believe ownership > titles , data-driven rigor > ego, and shipping weekly > polishing forever. What success looks like p50 latency < 500 ms for a multimodal query across 100k videos & 10M documents. Swirl AI becomes the reference “AI Sales Agent” demo in every Fortune-100 board deck. We out-innovate incumbents (Salesforce, Adobe, Shopify) by shipping features 4× faster with a team 10× leaner. Comp, stage & perks Top-of-market cash + meaningful founding equity (we’re an early-stage, venture-backed rocket). Choose your rig: M-series MacBook + 4k monitor or Linux workstation with RTX 6000. Remote-first (US / EU / India time overlap) with quarterly off-sites in Dubai, SF & Bangalore . Visa support, health + mental-wellness stipend, conference budget, unlimited books. Report directly to Kaizad Hansotia (Founder/CEO) & Akshil Shah (CTO) and shape the product that’s already trusted by BYD, Toyota, LG & Lennox. How to apply Send GitHub/LinkedIn + 2-3 sentences on the toughest system you’ve built to careers@goswirl.ai . Side-projects, papers, or a Loom walk-through of your favourite model-ops trick = huge plus. We move fast: expect a 48-hr reply → 1 technical deep-dive → paid take-home sprint → offer. Join us to make product pages talk, show & sell — at human level, globally.

Project Role : Full Stack Engineer Project Role Description : Responsible for developing and/or engineering the end-to-end features of a system, from user experience to backend code. Use development skills to deliver innovative solutions that help our clients improve the services they provide. Leverage new technologies that can be applied to solve challenging business problems with a cloud first and agile mindset. Must have skills : Data Science Good to have skills : NA Minimum 3 Year(s) Of Experience Is Required Educational Qualification : 15 years full time education Summary: As a Full Stack Engineer, you will be responsible for developing and engineering the end-to-end features of a system. Your typical day will involve collaborating with cross-functional teams to design and implement innovative solutions that enhance user experience and optimize backend processes. You will leverage new technologies to address complex business challenges while maintaining a cloud-first and agile approach, ensuring that the services provided to clients are continuously improved and aligned with their needs. Your role will require a balance of creativity and technical expertise to deliver high-quality software solutions that meet project requirements and client expectations. Roles & Responsibilities: - Expected to perform independently and become an SME. - Required active participation/contribution in team discussions. - Contribute in providing solutions to work related problems. - Collaborate with team members to design and implement new features. - Conduct code reviews to ensure quality and adherence to best practices. "• Experience with Hugging Face Transformers, LangChain, OpenAI APIs • Strong knowledge of machine learning libraries: scikit-learn, XGBoost, LightGBM • Experience with Retrieval-Augmented Generation (RAG): Faiss, Pinecone, Weaviate, ChromaDB • Training, fine-tuning, and optimizing transformer models (BERT, GPT, T5, LLaMA) • Deep understanding of self-attention, positional embeddings, sequence modeling • Strong NLP expertise: Named Entity Recognition (NER), topic modeling, text embeddings • Good grasp of linear algebra: vectors, matrices, eigenvalues, eigenvectors etc • Expertise in gradient descent, backpropagation, activation functions, loss functions • Experience with dimensionality reduction techniques for feature selection • Knowledge of time-series forecasting, anomaly detection, and probabilistic modeling • Understanding of model serving techniques, including REST APIs and real-time inference" "• Develop and fine-tune LLMs (GPT, BERT, T5, LLaMA, Mistral) for text generation, summarization, translation, and question-answering tasks. • Work with transformer-based architectures, understanding self-attention mechanisms, token embeddings, and model interpretability. • Implement custom tokenization techniques, text embedding models (Sentence-BERT, OpenAI Embeddings, Cohere, etc.), and efficient inference optimizations. • Apply prompt engineering and prompt tuning techniques to optimize model responses. • Work with LangChain and LLM orchestration frameworks to build AI-powered applications. • Build Retrieval-Augmented Generation (RAG) pipelines using vector databases like FAISS, Pinecone, Weaviate, ChromaDB. • Work with Hugging Face Transformers, spaCy, NLTK, and OpenAI APIs." Professional & Technical Skills: - Must To Have Skills: Proficiency in Python (Programming Language). - Good To Have Skills: Experience with JavaScript frameworks such as React or Angular. - Strong understanding of RESTful API design and development. - Familiarity with cloud platforms such as AWS or Azure. - Experience with database management systems like MySQL or PostgreSQL. "Must Have Skills: 1. Must have 5-7+ years of experience working as a Microsoft FED Angular. 2. Strong understanding of software development principles, design patterns, and best practices. 3. Develop, test, and maintain software applications using Angular and .NET. 4. Designing & developing user interfaces using angular best practices 5. Developing application code & unit tests in angular. 6. Experience in consuming Web API/ Rest API using Javascript. 7. Should have good troubleshooting and debugging skills Good to Have Skills: 1. Knowledge/Experience in Excel 2 Knowledge/Experience of Agile methodology and Sprint based project delivery Nice to Have Skills: 1. .Net Core 2. Agile Development Methodology 2. MySQL" "• Should be good team player. • Good Written & Verbal Communication skills • Good analytical and troubleshooting skills." Additional Information: - The candidate should have minimum 3 years of experience in Python (Programming Language). - This position is based at our Bengaluru office. - A 15 years full time education is required. Resource should be open to work in B Shift (Afternoon Shifts 12:30 to 10:30) during week days., 15 years full time education

We’re the world’s leading data, insights, and consulting company; we shape the brands of tomorrow by better understanding people everywhere. Worldpanel provides brands and retailers with a unique, 360-degree understanding of consumer behaviour across the globe. We are shopper-centric, continuously monitoring the purchase and usage behaviour through the largest omnipanel in the world. With unparalleled datasets, pioneering technology and expert analysts, we partner with brands and retailers of all sizes, empowering them to reimagine what’s possible, and change the landscape to create a better, healthier, more sustainable and inclusive world. Job Details About Worldpanel By Numerator Global experts in shopper behaviour, we help brands, retailers and government organisations to make the right decisions. At Worldpanel, we turn purchase behaviour into competitive advantages through continuous monitoring, advanced analytics and delivering tailored solutions. Office Location: Mumbai Division: Worldpanel Unit: Household Panel Function: WP Analytics Purpose Of The Role A new role is being created by Kantar Worldpanel India team, who uses technology and analytical tools to link real purchase data with impactful and high- quality data which inspire successful decisions. We are looking for someone who aspires to the same growth as us and joins us in developing the Data Quality solution in a fast-changing market working alongside our commercial teams and internal research team to help our clients solve their business challenges. Playing a leading role in the delivery of strategic quality management is a critical part of the business to ensure consistent quality standards and methods, deliver strategic transformational projects and drive continuous improvement for the growth of the business and excellency of operations. This is a full-time, role based in Mumbai. What'd You Do On a day-to-day basis, Act as custodian of project quality in all strategic and operational plans through experience and knowledge on consumer panel research operations. Accountable for tasks such as panel health & stability, sample designs, impact and pick up analysis factor creation etc. Maintain a strong, collaborative relationship with Client Service through data-driven decision making. Quality Standards and Policies Implement and help define quality standards and policies, including KPI definitions for purchase quality management. Provide textual definitions and management standard information for Operations (OP) to implement. Data Quality Assurance Act as the quality guardian for all consumer panel research Ensure good data quality before sending it to clients or uploading it to systems. Efficiently and timely investigate and resolve client data queries. Investigate problematic root causes and process flaws and provide solutions. Panel Health and Sample Design Take responsibility for panel health, stability, sample design, and analysis factors. Own the sourcing and application of Universe data and its ongoing implementation. Provide annual Universe information and offer explanations for any changes. Performance Monitoring and Auditing Audit local operational processes, define and monitor monthly results, and forecast to achieve panel and delivery targets. Regularly review and provide feedback on KPIs to OP teams. Process and Improvement Maintain all procedures related to quality, including mechanisms for purchase management. Continuously identify areas for improvement and propose corrective actions. Monitor and review quality assurance. Training and Education Educate Client Service (CS) and Operations teams on statistical data limitations according to sample sizes and sample design. Provide regular, high-quality local training content. Collaboration and Communication Maintain strong collaborative relationships with customer service through data-driven decisions. Ensure all queries/issues are kept on track and solved on time, following local and regional processes. Long run, you will.. Implement and help define quality standards and policy. Own the local audits of operating procedures, define & monitor monthly results, and forecast to achieve panel & delivery targets. Troubleshoot, resolve, remedy and overhaul where needed process defects which result in under-performance or non-delivery. Own and deliver local quality content training regularly. Productions of the above data matching, fraud detection, and data inference, by putting it into a technological environment Develop algorithm as well as statistical models to match and maximize the current data usage/automation. What'd You Bring Personal traits: stimulated by creative problem solving, comfortable with number, comfortable with ambiguity, work well autonomously but also happy to sit as part of a team, can focus on one specific task and not getting bored by the task, willing to learn and able to learn fast. Professional skills: excellent analytical skills; strong communication as you’ll need to explain the complex technical issues to people who might not have the data analysis or quality background; influencing the others in a rational way; creative thinking and solution-oriented; familiar with SPSS, Python or R, SQL , analytical innovation and automation ; computer coding skill is a plus but definitely a must-have. Minimum 2 tools knowledge is required. Academic background: Bachelor degree or above. Those who majored in Mathematics, Statistics and have certification in data quality might find quicker assimilation to the role but we do not intend to limit the range at all. Fluent in both English and Hindi. Work experience: Mini 8 years of work experience is preferred. If you have customized research experience before, or worked in a data analytics and research or statistics role, that would be a preferential advantage. Ability to communicate clearly and confidently, spoken and written, to levels of business locally and with Regional Quality team and peers in other markets. Ability to be self-motivated and independent as well as teamwork. Able to work under pressure to tight deadlines. With the following qualities… Inquisitive, with critical thinking, and demonstrate a genuine passion for consumer behaviour. Enjoys actively looking for new and more efficient ways of improving processes, raising standards, reducing errors, and overcoming omissions. Is proactive, optimistic, and willing to get involved to achieve the team's goals and objectives. Is highly collaborative and adaptable with the ability to work effectively within different cultural and technical environments. Possesses outstanding communication and interpersonal skills in order to comfortably connect with partners at all levels across the organization and facilitates discussions in a constructive manner. Country India Why join Kantar? We shape the brands of tomorrow by better understanding people everywhere. By understanding people, we can understand what drives their decisions, actions, and aspirations on a global scale. And by amplifying our in-depth expertise of human understanding alongside ground-breaking technology, we can help brands find concrete insights that will help them succeed in our fast-paced, ever shifting world. And because we know people, we like to make sure our own people are being looked after as well. Equality of opportunity for everyone is our highest priority and we support our colleagues to work in a way that supports their health and wellbeing. While we encourage teams to spend part of their working week in the office, we understand no one size fits all; our approach is flexible to ensure everybody feels included, accepted, and that we can win together. We’re dedicated to creating an inclusive culture and value the diversity of our people, clients, suppliers and communities, and we encourage applications from all backgrounds and sections of society. Even if you feel like you’re not an exact match, we’d love to receive your application and talk to you about this job or others at Kantar.

About AstraZeneca AstraZeneca is a global, science-led, patient-focused biopharmaceutical company that focuses on the discovery, development and commercialization of prescription medicines for some of the world’s most serious diseases. But we’re more than one of the world’s leading pharmaceutical companies. Position Title: Insights Manager This position is responsible for using customer-level data, sales data, profiling data, and other information to perform analysis which helps the business in designing an effective customer engagement plan. Spearhead the segmentation and targeting process, driven by strategy definition for the Business. Leverage the analysis to generate insights and recommendations for optimizing sales efforts and effectively communicating those recommendations to key business stakeholders such as the marketing teams and sales leaders. This role will drive the SFE KPI and Business Performance Dashboard and support monthly Business Unit Performance Review Procedures and Quarterly RBM review Processes. This role would also require one to lead and analyse market trends, changes in market dynamics, coordinate analysis reports and proactively identify business opportunities for current and future therapy areas, Build and drive reporting analysis including reports on the market, therapy areas, and brands performance, leveraging on IQVIA, industry reports & in-market sales reports, Act as the subject matter expert to improve the quality, reliability, and availability of the data, provide insightful and actionable analytics. Valued Partner for business Collaborate and support in crafting Pre & Post strategy with Business Unit Identify SFE priorities by BU in consultation with the BU Head, Marketing manager and Sales Managers Highly Collaborative in nature with high interpersonal skill set for the best kind of stakeholder management Clarify and drive strategy execution to RBMs, ABMs and TBMs Demonstrate improvements through analytical insights and intervention in the planning/execution processes Develop/refine the analytics roadmap to address performance and insights needs and meet business priorities Drive data management and data processing of customer profiling and targeting, and field force calls and promotional activities Deep dive analysis of reasons of performing and non-performing territories Customer engagement journey tracking Insight generation, Profiling, Segmentation and Targeting Conceptualize profiling approach to identify key target segments for pre- and Post Launch Strategy Analyse opportunities@ HCP/Territories through profiling and insights Define sharp S&T based on outcome and insights of profiling for Sales force Develop a robust tracking mechanism Provide insights into call planning and messaging to doctors Monitor execution excellence and provide periodic feedback to cross function team with analytics and insights Engage with teams to close gaps in sales execution process Detailed understanding of doctors and alignment with the strategy Clear understanding of Segmentation & targeting and models Participation and understanding of sales force understanding Insight driven Business sales planning and review procedures Participate as a key contributor in the annual commercial planning process, specifically to leverage insights to optimize promotion Set KPI & drive Field force to comply with the KPIs Participate as a key contributor in the annual commercial planning process, specifically to leverage insights to optimize promotion Set KPI & drive Field force to comply with the KPIs Ensure availability of meaningful and accurate field force metrics (e.g. SFE “dashboards”) for management information Design Review templates, ensure timely completion of the templates and actively participate in Review meeting at RBM & ABM level Coordinate with the sales team & MIS/Database team so as to maintain data updating and reports submission from field force Define the Key timelines for activities such as profiling, dashboard publication and other key analyses Adhere to the timelines and highlight key challenges Develop mechanism of availability of Customer/Account sales & Non sales on periodical manner Existence of plans of each TBM Filled review template Essential Education, Qualifications, Skills and Experience MBA from a reputed institute (<30 Years of Age) Expert in Advanced Excel -Proficiency in using complex formulas (e.g., VLOOKUP, HLOOKUP, INDEX-MATCH, SUMIFS, COUNTIFS, etc.), Ability to create and understand nested formulas, Expertise in data cleaning, transformation, and manipulation, Ability to sort, filter, and extract relevant information from large datasets, Pivot Tables and Pivot Reporting, Proficient in creating various types of charts and graphs for data visualization, Ability to approach complex data-related problems with a logical and analytical mindset, keen eye for detail, especially when working with large datasets. Data Visualization Tools: Proficiency in Power BI tool for creating meaningful visualizations to communicate insights effectively. Additional knowledge of tools like Tableau, Matplotlib, Seaborn, or ggplot would be useful. Data Storytelling: The ability to communicate findings effectively through PowerPoint or other Visualization tools like Power BI Market Research Experience: Prior experience in market research or related roles is crucial. This may include positions such as Market Research Analyst, Data Analyst, or similar roles. Experience in pharma or consultancy such as IQVIA would be highly valued. Analytical Skills: The ability to analyze data and draw meaningful insights is fundamental. This includes proficiency in statistical analysis and data interpretation. Strategic Thinking: Able to think strategically and provide actionable recommendations based on data and market trends. Communication Skills: Strong written and verbal communication skills for presenting findings, creating reports, and interacting with cross-functional teams. Desirable Young and result-oriented individual, having a portfolio of personal or professional data science projects. Familiarity with market research tools and software can be useful. This could include tools for survey creation, data analysis, and visualization. Certifications in market research or related areas. For example, certifications from organizations like the Market Research Society (MRS) Statistical Modeling: Understanding of statistical concepts and proficiency in using statistical models for analysis and inference. Hypothesis Testing: Knowledge of hypothesis testing, and experimental design is important for drawing meaningful conclusions from data. Continuous Improvement Culture: Understanding and implementing of Six Sigma principles Why AstraZeneca? At AstraZeneca we’re dedicated to being a Great Place to Work. Where you are empowered to push the boundaries of science and unleash your entrepreneurial spirit. There’s no better place to make a difference to medicine, patients and society. An inclusive culture that champions diversity and collaboration, and always committed to lifelong learning, growth and development. We’re on an exciting journey to pioneer the future of healthcare. You can find alternative messaging to use in the ‘Global Talent Attraction Story messaging’ section of the Global Playbook on the Employer Brand Portal - try to use other examples in order to make it different for candidates! So, what’s next? Are you already imagining yourself joining our team? Good, because we can’t wait to hear from you. Are you ready to bring new ideas and fresh thinking to the table? Brilliant! We have one seat available and we hope it’s yours. If you’re curious to know more then please reach out to (contact person) We welcome with your application, no later than (Month) (XX) Where can I find out more? Our Social Media, Follow AstraZeneca on LinkedIn https://www.linkedin.com/company/1603/ Follow AstraZeneca on Facebook https://www.facebook.com/astrazenecacareers/ Follow AstraZeneca on Instagram https://www.instagram.com/astrazeneca_careers/?hl=en If you have site, country or departmental social media then feel free to switch any of the above links. Date Posted 16-Jul-2025 Closing Date 15-Aug-2025 AstraZeneca embraces diversity and equality of opportunity. We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills. We believe that the more inclusive we are, the better our work will be. We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics. We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorization and employment eligibility verification requirements.

Job Description 💰 Compensation Note: The budget for this role is fixed at INR 50–55 lakhs per annum (non-negotiable). Please ensure this aligns with your expectations before applying. 📍 Work Setup: This is a hybrid role , requiring 3 days per week onsite at the office in Hyderabad, India . Company Description: Blend is a premier AI services provider, committed to co-creating meaningful impact for its clients through the power of data science, AI, technology, and people. With a mission to fuel bold visions, Blend tackles significant challenges by seamlessly aligning human expertise with artificial intelligence. The company is dedicated to unlocking value and fostering innovation for its clients by harnessing world-class people and data-driven strategy. We believe that the power of people and AI can have a meaningful impact on your world, creating more fulfilling work and projects for our people and clients. Job Description : We are looking for an AI Engineer with experience in Speech-to-text and Text Generation to solve a Conversational AI challenge for our client based in EMEA. The focus of this project is to transcribe conversations and leverage generative AI-powered text analytics to drive better engagement strategies and decision-making. The ideal candidate will have deep expertise in Speech-to-Text (STT), Natural Language Processing (NLP), Large Language Models (LLMs), and Conversational AI systems. This role involves working on real-time transcription, intent analysis, sentiment analysis, summarization, and decision-support tools. Key Responsibilities: Conversational AI & Call Transcription Development Develop and fine-tune automatic speech recognition (ASR) models Implement language model fine-tuning for industry-specific language. Develop speaker diarization techniques to distinguish speakers in multi-speaker conversations. NLP & Generative AI Applications Build summarization models to extract key insights from conversations. Implement Named Entity Recognition (NER) to identify key topics. Apply LLMs for conversation analytics and context-aware recommendations. Design custom RAG (Retrieval-Augmented Generation) pipelines to enrich call summaries with external knowledge. Sentiment Analysis & Decision Support Develop sentiment and intent classification models. Create predictive models that suggest next-best actions based on call content, engagement levels, and historical data. AI Deployment & Scalability Deploy AI models using tools like AWS, GCP, Azure AI, ensuring scalability and real-time processing. Optimize inference pipelines using ONNX, TensorRT, or Triton for cost-effective model serving. Implement MLOps workflows to continuously improve model performance with new call data. Qualifications: Technical Skills Strong experience in Speech-to-Text (ASR), NLP, and Conversational AI. Hands-on expertise with tools like Whisper, DeepSpeech, Kaldi, AWS Transcribe, Google Speech-to-Text. Proficiency in Python, PyTorch, TensorFlow, Hugging Face Transformers. Experience with LLM fine-tuning, RAG-based architectures, and LangChain. Hands-on experience with Vector Databases (FAISS, Pinecone, Weaviate, ChromaDB) for knowledge retrieval. Experience deploying AI models using Docker, Kubernetes, FastAPI, Flask. Soft Skills Ability to translate AI insights into business impact. Strong problem-solving skills and ability to work in a fast-paced AI-first environment. Excellent communication skills to collaborate with cross-functional teams, including data scientists, engineers, and client stakeholders. Preferred Qualifications Experience in healthcare, pharma, or life sciences NLP use cases. Background in knowledge graphs, prompt engineering, and multimodal AI. Experience with Reinforcement Learning (RLHF) for improving conversation models.

Job Description 💰 Compensation Note: The budget for this role is fixed at INR 50–55 lakhs per annum (non-negotiable). Please ensure this aligns with your expectations before applying. 📍 Work Setup: This is a hybrid role , requiring 3 days per week onsite at the office in Hyderabad, India . Company Description: Blend is a premier AI services provider, committed to co-creating meaningful impact for its clients through the power of data science, AI, technology, and people. With a mission to fuel bold visions, Blend tackles significant challenges by seamlessly aligning human expertise with artificial intelligence. The company is dedicated to unlocking value and fostering innovation for its clients by harnessing world-class people and data-driven strategy. We believe that the power of people and AI can have a meaningful impact on your world, creating more fulfilling work and projects for our people and clients. Job Description : We are looking for an AI Engineer with experience in Speech-to-text and Text Generation to solve a Conversational AI challenge for our client based in EMEA. The focus of this project is to transcribe conversations and leverage generative AI-powered text analytics to drive better engagement strategies and decision-making. The ideal candidate will have deep expertise in Speech-to-Text (STT), Natural Language Processing (NLP), Large Language Models (LLMs), and Conversational AI systems. This role involves working on real-time transcription, intent analysis, sentiment analysis, summarization, and decision-support tools. Key Responsibilities: Conversational AI & Call Transcription Development Develop and fine-tune automatic speech recognition (ASR) models Implement language model fine-tuning for industry-specific language. Develop speaker diarization techniques to distinguish speakers in multi-speaker conversations. NLP & Generative AI Applications Build summarization models to extract key insights from conversations. Implement Named Entity Recognition (NER) to identify key topics. Apply LLMs for conversation analytics and context-aware recommendations. Design custom RAG (Retrieval-Augmented Generation) pipelines to enrich call summaries with external knowledge. Sentiment Analysis & Decision Support Develop sentiment and intent classification models. Create predictive models that suggest next-best actions based on call content, engagement levels, and historical data. AI Deployment & Scalability Deploy AI models using tools like AWS, GCP, Azure AI, ensuring scalability and real-time processing. Optimize inference pipelines using ONNX, TensorRT, or Triton for cost-effective model serving. Implement MLOps workflows to continuously improve model performance with new call data. Qualifications: Technical Skills Strong experience in Speech-to-Text (ASR), NLP, and Conversational AI. Hands-on expertise with tools like Whisper, DeepSpeech, Kaldi, AWS Transcribe, Google Speech-to-Text. Proficiency in Python, PyTorch, TensorFlow, Hugging Face Transformers. Experience with LLM fine-tuning, RAG-based architectures, and LangChain. Hands-on experience with Vector Databases (FAISS, Pinecone, Weaviate, ChromaDB) for knowledge retrieval. Experience deploying AI models using Docker, Kubernetes, FastAPI, Flask. Soft Skills Ability to translate AI insights into business impact. Strong problem-solving skills and ability to work in a fast-paced AI-first environment. Excellent communication skills to collaborate with cross-functional teams, including data scientists, engineers, and client stakeholders. Preferred Qualifications Experience in healthcare, pharma, or life sciences NLP use cases. Background in knowledge graphs, prompt engineering, and multimodal AI. Experience with Reinforcement Learning (RLHF) for improving conversation models.